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INFLUENCE OF SEED PRIMING ON THE PERFORMANCE OF BARLEY VARIETIES UNDER LATE SOWN AND ABIOTIC
STRESS CONDITIONS
By
TAHIRA TABASSUMM.Sc. (Hons.) Agriculture (Agronomy)
2008-ag-2561
A thesis submitted in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
I N
A G R O N O M Y
DEPARTMENT OF AGRONOMY,FACULTY OF AGRICULTURE,
UNIVERSITY OF AGRICULTURE,FAISALABAD, PAKISTAN
2018
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Dedicated To
My Respected
MY LOVING PARENTS, MY CARING HUSBAND DR. ALI ZOHAIB AND MY KIND TEACHER DR.
RIAZ AHMAD
WHO ALWAYS SUPPORTED AND HELPED ME TO ACHIEVE MY GOALS
A C K N O W L E D G E M E N T
First of all, I would like to thank the grace of Allah Almighty for completing this
work at this final shape. All respects are for the Holy prophet Muhammad (Peace be upon
him and his family), for enlightening our conscience with the essence of faith in Allah,
and for giving us the golden principles of Islam.
I owe a great depth of gratitude and appreciation for my supervisor Dr. Riaz
Ahmad, Professor, Department of Agronomy, University of Agriculture, Faisalabad for
his sympathetic attitude, step to step guidance, his supervision and choosing of this
research, his scientific guidance, providing the possible laboratory materials and
unwavering support during my academic and research endeavors.
My deepest and warm gratitude to advisory committee: Dr. Muhammad Farooq,
Associate Professor, Department of Agronomy, University of Agriculture, Faisalabad and
Dr. Shahzad Maqsood Ahmed Basra, Professor, Department of Agronomy, University
of Agriculture, Faisalabad. I am also grateful to Dr. Lee Tarpley, Professor, Department
of Soil and Crop Sciences, Texas A&M University, USA, for supervising me during
IRSIP research work. I am thankful for the guidance they provided me during my work
and evaluation of the work I did.
I am also highly appreciative to Higher Education Commission (HEC),
Government of Pakistan for granting me Indigenous Ph.D. fellowship during my
doctoral study. I really appreciate such fellowships as it is source of hope for students of
Pakistan who want to do something for their homeland.
Special gratefulness and appreciation to my colleagues and friends for assistance
and advices provided during my work. Last but not least, I would like to offer my special
thanks to my family especially my husband Dr. Ali Zohaib Randhawa whose utmost
efforts, endless support, love and prayers enabled me to complete this work and without
their support and kindness I wouldn't have been able to achieve this work and I cannot
find any word to express my sincere appreciation and gratitude to them.
(Tahira Tabassum)
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2.3.1. Drought stress 212.3.2. Salt stress 222.3.3. Cadmium stress 232.3.4. Heat stress 242.4. Management of abiotic stresses 252.4.1. Selection of stress tolerant varieties 252.4.2. Seed priming in abiotic stress tolerance 272.4.2.1. Osmopriming with calcium salt and abiotic stress tolerance 282.4.2.2. Biopriming with PGPBs and abiotic stress tolerance 292.5. Conclusion 303 MATERIALS AND METHODS 323.1. Experiment 1: Potential role of seed priming in improving
the resistance against drought in barley32
3.1.1. Experimental site and design 323.1.2. Experimental material 323.1.3. Experimental treatments 323.1.4. Crop husbandry 323.1.5. Imposition of drought stress 333.1.6. Procedures for recording data 333.1.6.1. Stand establishment 33i Final emergence (%) 33ii Time taken to 50% emergence (days) 33iii Mean emergence time (days) 34iv Emergence index 343.1.6.2. Morphological and allometric traits 34i Plant height (cm) 34ii Leaf area (cm2) 343.1.6.3. Proteomics 34i Total soluble proteins (mg g-1 FW) 343.1.6.4. Biochemical traits 35i Chlorophyll contents (mg g -1 FW) 35ii Free leaf proline (µmol g-1 FW) 35iii Leaf glycine betaine (µmol g-1 FW) 36iv Malondialdehyde (µmol g-1 FW) 36v Total soluble phenolics (µg g-1 FW) 36vi Cell membrane stability (%) 373.1.6.5. Water relation traits 37i Leaf relative water content (%) 37ii Leaf water potential (-MPa) 37iii Leaf osmotic potential (-MPa) 37iv Leaf pressure potential (MPa) 373.1.6.6. Grain analysis 38i Zinc content (µg g-1 DW) 38
viii
ii Manganese content (µg g-1 DW) 38iii Boron content (µg g-1 DW) 383.1.6.7. Yield and related traits 39i Number of tillers per pot 39Ii Number of productive tillers per pot 39iii Spike length (cm) 39iv Number of spikelet’s per spike 39v Number of grains per spike 39vi 100-grain weight (g) 39vii Grain yield (g pot-1) 40viii Biological yield (g pot-1) 40ix Harvest index (%) 403.2. Experiment 2: Potential role of seed priming in improving
the salt resistance in barley40
3.2.1. Experimental site and design 403.2.2. Experimental material 403.2.3. Experimental details 403.2.4. Crop husbandry 403.2.5. Imposition of salinity stress 413.2.6. Procedures for recording data 423.2.6.1. Stand establishment 423.2.6.2. Morphological and allometric traits 423.2.6.3. Mineral analysis 423.2.6.4. Proteomics 423.2.6.5. Biochemical traits 423.2.6.6. Water relation traits 423.2.6.7. Grain analysis 433.2.6.8. Yield and related traits 433.3. Experiment 3: Potential role of seed priming in improving
the resistance against osmotic and salt stresses in barley43
3.3.1. Experimental site and design 433.3.2. Experimental material 433.3.3. Crop husbandry and experimental details 433.3.4. Imposition of osmotic and ionic stress in hydroponics 433.3.5. Procedures for recording data 443.3.5.1. Seedling vigor 44i Shoot length of seedling (cm) 44ii Root length of seedling (cm) 44iii Shoot fresh weight (mg) 44iv Root fresh weight (mg) 44v Shoot dry weight (mg) 44vi Root dry weight (mg) 443.3.5.2. Proteomics 44
ix
3.3.5.3. Biochemical traits 443.3.5.4. Mineral analysis 453.4. Experiment 4: Potential role of seed priming in improving
the resistance against cadmium stress in barley45
3.4.1. Experimental site and design 453.4.2. Experimental material 453.4.3. Crop husbandry and experimental details 453.4.4. Procedures for recording data 453.4.4.1. Seedling vigor 453.4.4.2. Proteomics 463.4.4.3. Biochemical traits 463.4.4.4. Mineral analysis 46i Tissue cadmium content (μg g−1 DW) 463.5. Experiment 5: Potential role of seed priming in improving
the resistance against terminal heat stress in barley46
3.5.1. Experimental site and design 463.5.2. Experimental material 463.5.3. Experimental treatments 473.5.4. Crop husbandry 473.5.5. Procedures for recording data 473.5.5.1. Stand establishment 473.5.5.2. Morphological traits 473.5.6.3. Leaf chlorophyll contents 473.5.5.4. Leaf gas exchange characteristics 473.5.5.5. Leaf chlorophyll fluorescence attributes 483.5.5.6. Leaf estimated oxidative stress 483.5.5.7. Total phenolics content (mg g-1 FW) 483.5.6.8. Yield and related traits 483.6. Experiment 6: Influence of seed priming on the
productivity of late sown barley48
3.6.1. Experimental site and design 483.6.2. Experimental material 483.6.3. Seedbed preparation 493.6.4. Experimental details and crop husbandry 493.6.5. Irrigation 493.6.6. Procedures for recording data 493.6.6.1. Stand establishment 493.6.6.2. Allometric, phenological and morphological traits 49i Plant height (cm) 49ii Leaf area index 49iii Total dry matter (g m-2) 50iv Crop growth rate (g m-2 d-1) 50
x
v Grain filling rate (g spike-1 d-1) 50vi Grain filling duration (days) 503.6.6.3. Yield and related traits 50i Number of productive tillers m-2 50ii Spike length (cm) 50iii Number of spikelet’s per spike 50iv Number of grains per spike 50v 1000-grain weight (g) 50vi Grain yield (t ha-1) 51vii Biological yield (t ha-1) 51viii Harvest index (%) 513.6.6.4. Biochemical traits 51i Chlorophyll contents (a, b) 513.6.6.5. Grain proximate analysis 51i Grain protein content (%) 51ii Grain starch content (%) 513.7. Economic Analysis 513.8. Meteorological data 523.9. Statistical analysis 524 RESULTS AND DISCUSSION 564.1. Influence of seed priming in improving the resistance
against drought in barley56
4.1.1. Stand establishment 564.1.1.1. Final emergence percentage 564.1.1.2. Time taken to 50% emergence 564.1.1.3. Mean emergence time 564.1.1.4. Emergence index 564.1.2. Discussion 594.1.3. Agronomic attributes 594.1.3.1. Plant height 594.1.3.2. Leaf area 604.1.3.3. Total number of tillers per pot 604.1.3.4. Number of productive tillers per pot 614.1.3.5. Spike length 614.1.3.6. Number of spikelets per spike 614.1.3.7. Number of grains per spike 664.1.3.8. 100-grain weight 664.1.3.9. Grain yield per pot 674.1.3.10. Biological yield 674.1.3.11. Harvest index 674.1.4. Discussion 684.1.5. Chlorophyll contents 734.1.5.1. Chlorophyll a content 73
xi
4.1.5.2. Chlorophyll b content 744.1.6. Osmolytes accumulation 744.1.6.1. Total soluble phenolics 744.1.6.2. Total soluble proteins 754.1.6.3. Free proline content 754.1.6.4. Glycine betaine content 794.1.7. Lipid peroxidation 794.1.7.1. Malondialdehyde content 794.1.7.2. Cell membrane stability 804.1.8. Discussion 804.1.9. Water relations 854.1.9.1. Leaf relative water content 854.1.9.2. Leaf water potential 854.1.9.3. Leaf osmotic potential 854.1.9.4. Leaf pressure potential 864.1.10. Discussion 864.1.11. Grain nutrient content 904.1.11.1. Grain zinc content 904.1.11.2. Grain manganese content 904.1.11.3. Grain boron content 914.1.12. Discussion 914.2. Influence of seed priming in improving the salt resistance
in barley95
4.2.1. Stand establishment 954.2.1.1. Final emergence percentage 954.2.1.2. Time taken to 50% emergence 954.2.1.3. Mean emergence time 954.2.1.4. Emergence index 954.2.2. Discussion 984.2.3. Agronomic attributes 984.2.3.1. Plant height 984.2.3.2. Leaf area 994.2.3.3. Total number of tillers per pot 994.2.3.4. Number of productive tillers per pot 994.2.3.5. Spike length 1024.2.3.6. Number of spikelets per spike 1024.2.3.7. Number of grains per spike 1034.2.3.8. 100-grain weight 1034.2.3.9. Grain yield per pot 1074.2.3.10. Biological yield per pot 1074.2.3.11. Harvest index 1074.2.4. Discussion 1084.2.5. Chlorophyll contents 111
xii
4.2.5.1. Chlorophyll a content 1114.2.5.2. Chlorophyll b content 1134.2.6. Osmolytes accumulation 1124.2.6.1. Total soluble phenolics 1124.2.6.2. Total soluble proteins 1164.2.6.3. Free proline content 1164.2.6.4. Glycine betaine content 1164.2.7. Lipid peroxidation 1174.2.7.1. Malondialdehyde content 1174.2.7.2. Cell membrane stability 1174.2.8. Mineral analysis 1184.2.8.1. Na content 1184.2.8.2. K content 1184.2.9. Discussion 1234.2.10. Water relations 1244.2.10.1. Leaf relative water content 1244.2.10.2. Leaf water potential 1244.2.10.3. Leaf osmotic potential 1254.2.10.4. Leaf pressure potential 1254.2.11. Discussion 1294.2.12. Grain nutrient contents 1294.2.12.1. Grain zinc content 1294.2.12.2. Grain manganese content 1304.2.12.3. Grain boron content 1304.2.13. Discussion 1314.3. Influence of seed priming in improving the resistance
against osmotic and salt stresses in barley135
4.3.1. Seedling growth 1354.3.2. Chlorophyll contents 1354.3.3. Osmolytes accumulation 1364.3.4. Lipid peroxidation and sodium accumulation 1364.3.5. Discussion 1374.4. Influence of seed priming in improving the resistance
against cadmium stress in barley147
4.4.1. Seedling growth 1474.4.2. Chlorophyll contents 1474.4.3. Osmolytes accumulation 1484.4.4. Lipid peroxidation and cadmium content 1484.4.5. Discussion 1494.5. Influence of seed priming in improving the resistance
against terminal heat stress in barley158
4.5.1. Stand establishment 1584.5.2. Agronomic attributes 158
xiii
4.5.3. Gas exchange attributes 1584.5.4. Chlorophyll a fluorescence attributes 1644.5.5. Chlorophyll contents 1684.5.7. Biochemical attributes 1684.5.7. Discussion 1724.6. Influence of seed priming on the productivity of late sown
barley175
4.6.1. Stand establishment 1754.6.1.1. Mean emergence time 1754.6.1.2. Time taken to 50% emergence 1754.6.1.3. Emergence index 1754.6.2. Discussion 1784.6.3. Allometric traits 1784.6.3.1. Leaf area index 1784.6.3.2. Total dry matter 1814.6.3.3. Crop growth rate 1814.6.3.4. Grain filling rate 1864.6.3.5. Grain filling duration 1864.6.4. Discussion 1904.6.5. Agronomic attributes 1914.6.5.1. Plant height 1914.6.5.2. Number of productive tillers m-2 1914.6.5.3. Spike length 1944.6.5.4. Number of spikelets per spike 1944.6.5.5. Number of grains per spike 1944.6.5.6. 1000-grain weight 1964.6.5.7. Grain yield 1964.6.5.8. Straw yield 1974.6.5.9. Biological yield 1974.6.5.10. Harvest index 1974.6.6. Discussion 1984.6.7. Chlorophyll contents 2034.6.7.1. Chlorophyll a content 2034.6.7.2. Chlorophyll b content 2034.6.8. Discussion 2044.6.9. Grain proximate analysis 2064.6.9.1. Grain crude protein content 2064.6.9.2. Grain starch content 2064.6.10. Discussion 2074.6.11. Economic and marginal analysis 2074.6.12. Discussion 2105 SUMMARY 213
Future research thrusts 218
xiv
LITERATURE CITED 219
xv
LIST OF TABLES
Table No. Title Page No.3.1 Properties of experimental soil (Experiments 1, 2 and 6) 533.2 Properties of experimental soil (Experiment 5) 54
3.3 Weather data during the growing seasons of wheat at experimental site (Experiments 1,2 and 6)
55
4.1 Analysis of variance for the influence of seed priming on final emergence percentage and time taken to 50% emergence of barley
57
4.2 Influence of seed priming on final emergence (%) of barley 57
4.3 Influence of seed priming on time taken to 50% emergence (days) of barley
57
4.4 Analysis of variance for the influence of seed priming on mean emergence time and emergence index of barley
57
4.5 Influence of seed priming on mean emergence time (days) of barley
58
4.6 Influence of seed priming on emergence index of barley 58
4.7 Analysis of variance for the influence of seed priming on plant growth of barley under drought stress
62
4.8 Influence of seed priming on plant height (cm) of barley under drought stress (2014-15)
62
4.9 Influence of seed priming on plant height (cm) of barley under drought stress (2015-16)
62
4.10 Influence of seed priming on leaf area (cm2) of barley under drought stress (2014-15)
62
4.11 Influence of seed priming on leaf area (cm2) of barley under drought stress (2015-16)
63
4.12 Analysis of variance for the influence of seed priming on number of total and productive tillers of barley under drought stress
63
4.13 Influence of seed priming on total number of tillers per pot of barley under drought stress (2014-15)
63
4.14 Influence of seed priming on total number of tillers per pot of barley under drought stress (2015-16)
63
4.15 Influence of seed priming on number of productive tillers per pot of barley under drought stress (2014-15)
64
4.16 Influence of seed priming on number of productive tillers per pot of barley under drought stress (2015-16)
64
4.17 Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under drought stress
64
xvi
4.18 Influence of seed priming on spike length (cm) of barley under drought stress (2014-15)
64
4.19 Influence of seed priming on spike length (cm) of barley under drought stress (2015-16)
65
4.20a Influence of seed priming on number of spikelets per spike of barley under drought stress (2014-15)
65
4.20b Influence of seed priming on number of spikelets per spike of barley under drought stress (2014-15)
65
4.21a Influence of seed priming on number of spikelets per spike of barley under drought stress (2015-16)
65
4.21b Influence of seed priming on number of spikelets per spike of barley under drought stress (2015-16)
65
4.22 Analysis of variance for the influence of seed priming on number of grains per spike and 100-grain weight of barley under drought stress
69
4.23 Influence of seed priming on number of grains per spike of barley under drought stress (2014-15)
69
4.24 Influence of seed priming on number of grains per spike of barley under drought stress (2015-16)
69
4.25 Influence of seed priming on 100-grain weight (g) of barley under drought stress (2014-15)
69
4.26 Influence of seed priming on 100-grain weight (g) of barley under drought stress (2015-16)
70
4.27 Analysis of variance for the influence of seed priming on grain yield, biological yield and harvest index of barley under drought stress
70
4.28 Influence of seed priming on grain yield (g per pot) of barley under drought stress (2014-15)
70
4.29 Influence of seed priming on grain yield (g per pot) of barley under drought stress (2015-16)
70
4.30a Influence of seed priming on biological yield (g per pot) of barley under drought stress (2014-15)
71
4.30b Influence of seed priming on biological yield (g per pot) of barley under drought stress (2014-15)
71
4.31 Influence of seed priming on biological yield (g per pot) of barley under drought stress (2015-16)
71
4.32 Influence of seed priming on harvest index (%) of barley under drought stress (2014-15)
71
4.33a Influence of seed priming on harvest index (%) of barley under drought stress (2015-16)
72
4.33b Influence of seed priming on harvest index (%) of barley under drought stress (2015-16)
72
4.34 Analysis of variance for the influence of seed priming on 76
xvii
chlorophyll contents of barley under drought stress4.35 Analysis of variance for the influence of seed priming on total
soluble proteins and total soluble phenolics contents of barley under drought stress
76
4.36 Analysis of variance for the influence of seed priming on free proline and glycine betaine contents of barley under drought stress
81
4.37 Analysis of variance for the influence of seed priming on malondialdehyde and cell membrane stability of barley under drought stress
81
4.38 Analysis of variance for the influence of seed priming on leaf relative water content and leaf water potential of barley under drought stress
87
4.39 Analysis of variance for the influence of seed priming on leaf osmotic potential and leaf pressure potential of barley under drought stress
87
4.40 Analysis of variance for the influence of seed priming on grain mineral contents of barley under drought stress
92
4.41a Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2014-15)
92
4.41b Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2014-15)
92
4.42a Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2015-16)
92
4.42b Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2015-16)
93
4.43a Influence of seed priming on grain manganese content (µg g-1
DW) of barley under drought stress (2014-15)93
4.43b Influence of seed priming on grain manganese content (µg g-1
DW) of barley under drought stress (2014-15)93
4.44a Influence of seed priming on grain manganese content (µg g-1
DW) of barley under drought stress (2015-16)93
4.44b Influence of seed priming on grain manganese content (µg g-1
DW) of barley under drought stress (2015-16)93
4.45a Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2014-15)
94
4.45b Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2014-15)
94
4.46a Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2015-16)
94
4.46b Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2015-16)
94
4.47 Analysis of variance for the influence of seed priming on final 96
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emergence percentage and time taken to 50% emergence of barley
4.48 Influence of seed priming on final emergence (%) of barley 96
4.49 Influence of seed priming on time taken to 50% emergence (days) of barley
96
4.50 Analysis of variance for the influence of seed priming on mean emergence time and emergence index of barley
96
4.51 Influence of seed priming on mean emergence time (days) of barley
97
4.52 Influence of seed priming on emergence index of barley 97
4.53 Analysis of variance for the influence of seed priming on plant growth of barley under salinity
100
4.54 Influence of seed priming on plant height (cm) of barley under salinity (2014-15)
100
4.55 Influence of seed priming on plant height (cm) of barley under salinity (2015-16)
100
4.56 Influence of seed priming on leaf area (cm2) of barley under salinity (2014-15)
100
4.57 Influence of seed priming on leaf area (cm2) of barley under salinity (2015-16)
101
4.58 Analysis of variance for the influence of seed priming on number of total and productive tillers of barley under salinity
101
4.59 Influence of seed priming on total number of tillers per pot of barley under salinity (2014-15)
101
4.60 Influence of seed priming on total number of tillers per pot of barley under salinity (2015-16)
101
4.61 Influence of seed priming on number of productive tillers per pot of barley under salinity (2014-15)
104
4.62 Influence of seed priming on number of productive tillers per pot of barley under salinity (2015-16)
104
4.63 Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under salinity
104
4.64 Influence of seed priming on spike length (cm) of barley under salinity (2014-15)
104
4.65 Influence of seed priming on spike length (cm) of barley under salinity (2015-16)
105
4.66 Influence of seed priming on number of spikelets per spike of barley under salinity (2014-15)
105
4.67 Influence of seed priming on number of spikelets per spike of barley under salinity (2015-16)
105
4.68 Analysis of variance for the influence of seed priming on 105
xix
number of grains per spike and 100-grain weight of barley under salinity
4.69 Influence of seed priming on number of grains per spike of barley under salinity (2014-15)
106
4.70 Influence of seed priming on number of grains per spike of barley under salinity (2015-16)
106
4.71 Influence of seed priming on 100-grain weight (g) of barley under salinity (2014-15)
106
4.72 Influence of seed priming on 100-grain weight (g) of barley under salinity (2015-16)
106
4.73 Analysis of variance for the influence of seed priming on grain yield, biological yield and harvest index of barley under salinity
109
4.74 Influence of seed priming on grain yield (g per pot) of barley under salinity (2014-15)
109
4.75 Influence of seed priming on grain yield (g per pot) of barley under salinity (2015-16)
109
4.76 Influence of seed priming on biological yield (g per pot) of barley under salinity (2014-15)
109
4.77 Influence of seed priming on biological yield (g per pot) of barley under salinity (2015-16)
110
4.78 Influence of seed priming on harvest index (%) of barley under salinity (2014-15)
110
4.79 Influence of seed priming on harvest index (%) of barley under salinity (2015-16)
110
4.80 Analysis of variance for the influence of seed priming on chlorophyll contents of barley under salinity
113
4.81 Analysis of variance for the influence of seed priming on total soluble proteins and total soluble phenolics contents of barley under salinity
113
4.82 Analysis of variance for the influence of seed priming on free proline and glycine betaine contents of barley under salinity
119
4.83 Analysis of variance for the influence of seed priming on malondialdehyde and cell membrane stability of barley under salinity
119
4.84 Analysis of variance for the influence of seed priming on leaf mineral contents of barley under salinity
119
4.85 Analysis of variance for the influence of seed priming on leaf relative water content and leaf water potential of barley under salinity
126
4.86 Analysis of variance for the influence of seed priming on leaf osmotic potential and leaf pressure potential of barley under salinity
126
xx
4.87 Analysis of variance for the influence of seed priming on grain mineral contents of barley under salinity
132
4.88a Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2014-15)
132
4.88b Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2014-15)
132
4.89a Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2015-16)
132
4.89b Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2015-16)
133
4.90a Influence of seed priming on grain manganese content (µg g-1
DW) of barley under salinity (2014-15)133
4.90b Influence of seed priming on grain manganese content (µg g-1
DW) of barley under salinity (2014-15)133
4.91a Influence of seed priming on grain manganese content (µg g-1
DW) of barley under salinity (2015-16)133
4.91b Influence of seed priming on grain manganese content (µg g-1
DW) of barley under salinity (2015-16)133
4.92a Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2014-15)
134
4.92b Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2014-15)
134
4.93a Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2015-16)
134
4.93b Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2015-16)
134
4.94 Analysis of variance for the influence of seed priming on seedling growth of barley under osmotic and salt stress
140
4.95 Analysis of variance for the influence of seed priming on chlorophyll and total soluble phenolics contents in barley under osmotic and salt stress
140
4.96 Analysis of variance for the influence of seed priming on osmolytes accumulation in barley under osmotic and salt stress
144
4.97 Analysis of variance for the influence of seed priming on malondialdehyde and Na contents in barley under osmotic and salt stress
144
4.98 Analysis of variance for the influence of seed priming on seedling growth of barley under cadmium stress
151
4.99 Analysis of variance for the influence of seed priming on chlorophyll and total soluble phenolics contents in barley under cadmium stress
151
4.100 Analysis of variance for the influence of seed priming on 155
xxi
osmolytes accumulation in barley under cadmium stress4.101 Analysis of variance for the influence of seed priming on
malondialdehyde and cadmium contents in barley under cadmium stress
155
4.102 Analysis of variance for the influence of seed priming on emergence of barley
159
4.103 Influence of seed priming on emergence attributes of barley 159
4.104 Analysis of variance for the influence of seed priming on growth and yield related traits of barley under terminal heat stress
159
4.105 Influence of seed priming on plant height and number of productive tillers per pot of barley under terminal heat stress
159
4.106 Influence of seed priming on spike length and number of spikelets per spike of barley under terminal heat stress
160
4.107 Analysis of variance for the influence of seed priming on yield related traits, yield and harvest index of barley under terminal heat stress
160
4.108 Influence of seed priming on number of grains per spike and 100-grain weight of barley under terminal heat stress
160
4.109 Influence of seed priming on grain yield and biological yield per pot of barley under terminal heat stress
160
4.110 Influence of seed priming on harvest index (%) of barley under terminal heat stress
161
4.111a Analysis of variance for the influence of seed priming on gas exchange attributes of barley under terminal heat stress
161
4.111b Analysis of variance for the influence of seed priming on gas exchange attributes of barley under terminal heat stress
161
4.112a Analysis of variance for the influence of seed priming on chlorophyll a fluorescence attributes of barley under terminal heat stress
165
4.112b Analysis of variance for the influence of seed priming on chlorophyll a fluorescence attributes of barley under terminal heat stress
165
4.113 Analysis of variance for the influence of seed priming on chlorophyll contents of barley under terminal heat stress
169
4.114 Analysis of variance for the influence of seed priming on total soluble phenolics, malondialdehyde and cell membrane stability of barley under terminal heat stress
169
4.115 Analysis of variance for the influence of seed priming on emergence of barley under optimum and late sowing time
176
4.116 Influence of seed priming on mean emergence time (days) of barley under optimum and late sowing time
176
4.117a Influence of seed priming on time taken for 50% (days) 176xxii
emergence of barley under optimum and late sowing time
4.117b Influence of seed priming on time taken to 50% emergence (days) of barley under optimum and late sowing time (2014-15)
177
4.118a Influence of seed priming on emergence index of barley under optimum and late sowing time
177
4.118b Influence of seed priming on emergence index of barley under optimum and late sowing time (2014-15)
177
4.119 Analysis of variance for the influence of seed priming on grain filling duration of barley under optimum and late sowing time
189
4.120 Influence of seed priming on grain filling duration (days) of barley under optimum and late sowing time (2014-15)
189
4.121 Influence of seed priming on grain filling duration (days) of barley under optimum and late sowing time (2015-16)
189
4.122 Analysis of variance for the influence of seed priming on plant height and number of productive tillers per m2 of barley under optimum and late sowing time
192
4.123a Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2014-15)
192
4.123b Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2014-15)
192
4.124 Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2015-16)
193
4.125 Influence of seed priming on number of productive tillers per m2 of barley under optimum and late sowing time
193
4.126 Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under optimum and late sowing time
195
4.127 Influence of seed priming on spike length (cm) of barley under optimum and late sowing time
195
4.128 Influence of seed priming on number of spikelets per spike of barley under optimum and late sowing time
195
4.129 Analysis of variance for the influence of seed priming on number of grains per spike and 1000-grain weight of barley under optimum and late sowing time
199
4.130 Influence of seed priming on number of grains per spike of barley under optimum and late sowing time
199
4.131a Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2014-15)
199
4.131b Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2014-15)
200
4.132 Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2015-16)
200
xxiii
4.133 Analysis of variance for the influence of seed priming on grain yield and straw yield of barley under optimum and late sowing time
200
4.134 Influence of seed priming on grain yield (t ha-1) of barley under optimum and late sowing time
201
4.135 Influence of seed priming on straw yield (t ha-1) of barley under optimum and late sowing time (2014-15)
201
4.136 Influence of seed priming on straw yield (t ha-1) of barley under optimum and late sowing time (2015-16)
201
4.137 Analysis of variance for the influence of seed priming on biological yield and harvest index of barley under optimum and late sowing time
202
4.138 Influence of seed priming on biological yield (t ha-1) of barley under optimum and late sowing time (2014-15)
202
4.139 Influence of seed priming on biological yield (t ha-1) of barley under optimum and late sowing time (2015-16)
202
4.140 Influence of seed priming on harvest index (%) of barley under optimum and late sowing time
202
4.141 Analysis of variance for the influence of seed priming on chlorophyll contents of barley under optimum and late sowing time
205
4.142 Influence of seed priming on leaf chlorophyll a content (mg g-
1 FW) of barley under optimum and late sowing time205
4.143 Influence of seed priming on leaf chlorophyll b content (mg g-
1 FW) of barley under optimum and late sowing time205
4.144 Analysis of variance for the influence of seed priming on grain crude protein and starch contents of barley under optimum and late sowing time
208
4.145 Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2014-15)
208
4.146a Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2015-16)
208
4.146b Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2015-16)
209
4.147 Influence of seed priming on grain starch content (%) of barley under optimum and late sowing time
209
4.148 Economic analysis 211
4.149 Marginal analysis 212
xxiv
LIST OF FIGURES
Figure No. Title Page No.4.1 Influence of seed priming on (a and b) chlorophyll a and (c
and d) chlorophyll b contents of barley under drought stress77
4.2 Influence of seed priming on (a and b) total soluble phenloics and (c and d) total soluble proteins contents of barley under drought stress
78
4.3 Influence of seed priming on (a and b) free proline and (c and d) glycine betaine contents of barley under drought stress
82
4.4 Influence of seed priming on (a and b) malondialdehyde content and (c and d) cell membrane stability of barley under drought stress
83
4.5 Influence of seed priming on (a and b) leaf relative water content and (c and d) leaf water potential of barley under drought stress
88
4.6 Influence of seed priming on (a and b) leaf osmotic potential and (c and d) leaf pressure potential of barley under drought stress
89
4.7 Influence of seed priming on (a and b) chlorophyll a and (c and d) chlorophyll b contents of barley under salinity
114
4.8 Influence of seed priming on (a and b) total soluble phenloics and (c and d) total soluble proteins contents of barley under salinity
115
4.9 Influence of seed priming on (a and b) free proline and (c and d) glycine betaine contents of barley under salinity
120
4.10 Influence of seed priming on (a and b) malondialdehyde content and (c and d) cell membrane stability of barley under salinity
121
4.11 Influence of seed priming on (a and b) Na content and (c and d) K content of barley under salinity
122
4.12 Influence of seed priming on (a and b) leaf relative water content and (c and d) leaf water potential of barley under salinity
127
4.13 Influence of seed priming on (a and b) leaf osmotic potential and (c and d) leaf pressure potential of barley under salinity
128
4.14 Influence of seed priming on (a) shoot length (b) root length and (c) shoot fresh weight of barley under osmotic and salt stress
141
4.15 Influence of seed priming on (a) root fresh weight (b) shoot dry weight and (c) root dry weight of barley under osmotic and salt stress
142
xxv
4.16 Influence of seed priming on (a) chlorophyll a content (b) chlorophyll b content and (c) total soluble phenolics content of barley under osmotic and salt stress
143
4.17 Influence of seed priming on (a) total soluble proteins content (b) free proline content and (c) glycine betaine content of barley under osmotic and salt stress
145
4.18 Influence of seed priming on (a) malondialdehyde content and (b) Na content of barley under osmotic and salt stress
146
4.19 Influence of seed priming on (a) shoot length (b) root length and (c) shoot fresh weight of barley under cadmium stress
152
4.20 Influence of seed priming on (a) root fresh weight (b) shoot dry weight and (c) root dry weight of barley under cadmium stress
153
4.21 Influence of seed priming on (a) chlorophyll a content (b) chlorophyll b content and (c) total soluble phenolics content of barley under cadmium stress
154
4.22 Influence of seed priming on (a) total soluble proteins content (b) free proline content and (c) glycine betaine content of barley under cadmium stress
156
4.23 Influence of seed priming on (a) malondialdehyde content and (b) cadmium content of barley under cadmium stress
157
4.24 Influence of seed priming on (a and b) photosynthesis (PN) (c and d) stomatal conductance (gs) and (e and f) intercellular CO2 concentration (Ci) of barley under terminal heat stress
162
4.25 Influence of seed priming on (a and b) transpiration (Tr) (c and d) stomatal limitation (Ls) and (e and f) carboxylation use efficiency (CUE) of barley under terminal heat stress
163
4.26 Influence of seed priming on (a and b) minimal fluorescence (Fo) (c and d) maximal fluorescence (Fm) and (e and f) variable fluorescence (Fv) of barley under terminal heat stress
166
4.27 Influence of seed priming on (a and b) maximum quantum yield (Fv/Fm) (c and d) quantum yield of PSII (φPSII) and (e and f) electron transport rate (ETR) of barley under terminal heat stress
167
4.28 Influence of seed priming on (a and b) chlorophyll a content (c and d) chlorophyll b content and (e and f) total chlorophyll content of barley under terminal heat stress. DAT: days after heat stress treatment
170
4.29 Influence of seed priming on (a and b) total soluble phenolics (c and d) malondialdehyde content and (e and f) cell membrane stability of barley under terminal heat stress
171
4.30 Influence of seed priming on leaf area index of barley under (a) optimum and (b) late sowing time (2014-15)
179
xxvi
4.31 Influence of seed priming on leaf area index of barley under (a) optimum and (b) late sowing time (2015-16)
180
4.32 Influence of seed priming on total dry matter accumulation in barley under (a) optimum and (b) late sowing time (2014-15)
182
4.33 Influence of seed priming on total dry matter accumulation in barley under (a) optimum and (b) late sowing time (2015-16)
183
4.34 Influence of seed priming on crop growth rate of barley under (a) optimum and (b) late sowing time (2014-15)
184
4.35 Influence of seed priming on crop growth rate of barley under (a) optimum and (b) late sowing time (2015-16)
185
4.36 Influence of seed priming on grain filling rate of barley under (a) optimum and (b) late sowing time (2014-15)
187
4.37 Influence of seed priming on grain filling rate of barley under (a) optimum and (b) late sowing time (2015-16)
188
xxvii
LIST OF APPENDICES
Appendix No. Title Page No.
1 Fixed cost (Experiment 6) 253
2 Variable cost (Experiment 6) 254
xxviii
LIST OF ABBREVIATIONS
Abbreviation Complete% percent°C degree Celsiusµg micro gramµM micro molarABA abscisic acidANOVA analysis of varianceB boronBCR benefit cost ratioCa calciumCaM calmodulinCAT catalaseCd cadmiumCDPK calcium dependent protein kinasesCGR crop growth rateCi intercellular CO2 concentrationcm centimeterCRD completely randomized designCu copperCUE carboxylation use efficiencyDAA days after anthesisDAP diamonium phosphateDAS days after sowingDAT days after treatmentDW dry weightEC electrical conductivityETR electron transport rateFm maximal fluorescenceFo minimal fluorescenceFv variable fluorescenceFv/Fm maximum quantum efficiency of
PSIIFW fresh weightGR glutathione reductasegs stomatal conductanceGST glutathione -S-transferaseh hourha hectareHAMK heat-shock activated mitogen
activated protein kinaseIAA indole-acetic acidK potassiumkg kilogramL literLAD leaf area durationLAI leaf area indexHVA Hordeum vulgaris abundant protein
xxix
Ls stomatal limitationLSD least significance differencem meterM molarMAPK mitogen activated protein kinaseMDA malondialdehydeMg Magnesiummg milligrammL mili litermM mili molarmm milli metermmol L-1 milli mole per literMn manganeseMPa mega PascalMRR marginal rate of returnMT metallothioneinsN nitrogenNa sodiumNAR net assimilation rateNIR near infrarednm nano meterO* singlet oxygenO2− superoxide anionOH− hydroxyl radicalP phosphorusPb leadPC phytochelatinsPEG polyethylene glycolPGPB plant growth promoting bactariaPN photosynthesisppm parts per millionPSII photosystem IIQY quantum yield of PSIIRCBD randomized complete block designROS reactive oxygen speciesRs. RupeesSAR sodium absorption ratioSOD superoxide dismutaseSOP sulphate of potasht tonTBA thiobarbituric acidTCA trichloroacetic acidTDM total dry matterTr transpirationTSS total soluble saltsUSA the United States of Americaw/v weight by volumeZn zinc
xxx
ABSTRACT
Abiotic stresses affect plant productivity by modulationg various physiological and biochemical processes. Studies were performed to evaluate the influence of seed priming on the performance of barley varieties under late sown and abiotic stress conditions. For this purpose, a series of experiments was conducted in field and green house of University of Agriculture, Faisalabad, and glass house of Texas A&M University, USA. In first pot experiment, seeds of two barley varieties (viz. Haider-93 and Frontier-87) primed with water (hydropriming), CaCl2 solution (osmopriming) and Enterobacter sp. strain FD17 culture (biopriming) were sown in pots. After seedling establishment, drought levels (viz. 80, 60 and 40% water holding capacity) were imposed. In second pot experiment, same varieties and seed priming treatments were followed except after seedling establishment salinity levels (viz. 50, 100 and 150 mM NaCl) were imposed. Third experiment was carried out in hydroponics. Seedlings were raised in sand filled polythene bags by using same varieties and seed priming treatments. After stand establishment seedlings were transplanted in hydroponics then, osmotic (-0.8 MPa using PEG) and ionic (-0.8 MPa using NaCl) stresses were imposed. In fourth experiment, same procedure was followed as in the third experiment except cadmium (Cd) toxicity stress levels (viz. 0, 8 and 12 mg L-1 water) were imposed. In fifth experiment, seeds of USA cultivar Solum were primed with water (hydropriming) and CaCl2 (osmopriming), and sown in pots. At reproductive stage two levels of heat stress viz. control (25/18°C day/night) and heat stress (35/25°C day/night) were applied. In all pot and hydroponics experiments dry seed was taken as control. The pot and hydroponics experiments were carried out using completely randomized design (CRD) with factorial arrangement having four replications, except fifth experiment in which six replications were used. In sixth experiment, same varieties and seed priming treatments, as in first pot experiment, were followed and sown in field at November 30 and December 30. The experiment was conducted by using randomized complete block design (RCBD) with split-split plot arrangement having four replications. In first and second experiments, drought and salinity decreased plant growth, yield and chlorophyll contents, and perturbed the water and nutrient relations; while, increased accumulation of osmolytes and lipid peroxidation in both barley varieties, as compared to control. Moreover, salinity increased the sodium (Na) accumulation while decreased potassium (K) accumulation. However, seed priming improved plant growth, yield, tissue water status, cell membrane stability, chlorophyll contents and accumulation of phenolics, total soluble proteins, free proline and glycine betaine contents while decreased the malondialdehyde (MDA) content in both varieties under stressed conditions, as compared to unprimed control. The gretest improvement in yield under drought was caused by biopriming; whereas, under moderate and severe salt stress by biopriming and osmopriming, respectively. Moreover, biopriming improved the grain zinc (Zn), manganese (Mn) and boron (B) contents. In third and fourth experiments, osmotic, salt as well as Cd stress decreased the seedling growth and dry biomass in both varieties while increased the osmolytes and lipid peroxidation, as compared to control. Moreover, NaCl salt stress and Cd stress increased Na and Cd contents in barley, respectively. However, seed priming enhanced seedling growth, fresh and dry biomass, chlorophyll contents, phenolics, total soluble proteins, free proline and glycine betaine contents while decreased MDA, Na and Cd contents under stressed conditions, as compared to unprimed control. Under osmotic and Cd stress biopriming was most effective, while, under salt stress osmopriming was superior in improving barley performance. In fifth experiment, terminal heat stress hampered the plant growth, yield, leaf gas exchange and chlorophyll photochemistry while increased the phenolics and lipid
1
peroxidation, as compared to control. However, seed priming improved the photosynthesis, stomatal conductance, carboxylation use efficiency (CUE), quantum yield of photosystem II (QY), electron transport rate (ETR), chlorophyll contents, phenolics and cell membrane stability while decreased MDA content under terminal heat stress, as compared to unprimed control, and osmopriming was superior in this regard. In sixth experiment, late sowing caused a reduction in emergence, growth, grain yield, dry matter accumulation, grain filling duration, chlorophyll contents, and grain crude protein and starch contents in both barley varieties, as compared to optimum sowing time. However, seed priming improved emergence, plant height, crop growth rate (CGR), total dry matter accumulation (TDM), leaf area index (LAI), grain filling rate, yield and related traits, and grain crude protein and starch contents under both optimum and late sowing, as compared to unprimed control. The greatest improvement was caused by osmopriming followed by biopriming. The economic analysis showed that late sowing decreased economic returns as well as benefit cost ratio (BCR) which was improved by seed priming treatments. Among all, biopriming caused maximum improvement in BCR and marginal rate of return (MRR). In all pot and field experiments, variety Haider-93 performed better than Fronteir-87. In conclusion, abiotic stresses and late sowing decreased the plant growth and yield by negatively affecting plant physiological processes. However, performance of barley varieties was effectively improved by seed priming treatments under stressed conditions by improving the water relations, nutrient relations, osmolytes accumulation, photosynthesis, chlorophyll contents and decreasing the lipid peroxidation under stressed conditions.
2
CHAPTER 1INTRODUCTION
Barley (Hordeum vulgare L.), is an important cereal crop, which is cultivated for
human consumption as well as animal feed (Alazmani, 2015). It grows well on both
normal as well as marginal lands (Kafawin et al., 2005) and is tolerant to drought and
salinity due to expression of proteins such as Hordeum vulgaris abundant protein (HVA)
(Nguyen and Sticklen, 2013). However, the yield of barley is very low owing to poor
agro-management practices such as improper sowing time coupled with abiotic stresses
for instance high and low temperature, salinity, drought and heavy metal toxicity stress.
Optimum sowing time is important for achieving better crop yield and quality.
Early sowing affects yield potential by allowing a longer time for biomass accumulation.
However, too early or late sowing significantly reduces crop yield. Though early sowing
reduces the risk of heat stress during grain filling, it increases the frost risk during
flowering. While late sowing reduces crop yield and malting quality due to poor stand
establishment. Similarly, late sowing caused the cultivars to mature earlier which
indicated that maturity was forced because of high temperature (Samarah and Al-Issa,
2006), resulting in fewer tillers and number of grains per plant (Alazmani, 2015);
Furthermore, increase in temperature causes shortening of heading period under late sown
conditions (Razzaque and Rafiquzzaman, 2006). Alam et al. (2007) reported that late
sowing reduced the yield and yield components of barley. Late planted barley produced
less productive tillers, grain weight and grain yield than those of timely planted crop
(Samarah and Al-Issa, 2006). Therefore, by targeting the optimal sowing date, seasonal
risks can be minimized to harvest better crop yield.
Under field conditions, plants may face various abiotic stresses. Abiotic stresses
are the major limiting factors due to the potential influence of climate change on
temperature extremes and rainfall patterns, salinization of agricultural lands by irrigation
that reduces the agricultural productivity (Araus et al., 2002; Vinocur and Altman, 2005;
Tabassum et al., 2017). However, drought, salt, heat and heavy metal stresses are of
prime importance.
Drought is a most vital abiotic factor that negatively influences the crop growth
and production globally. It causes 15% of potential yield losses (Edmeades and James,
2008), and more than 50% plant growth problems to arable lands will occur by 2050
3
annually (Vinocur and Altman, 2005). Reduction in crop yield by drought may happen
due to less absorption of the photosynthetically active radiation (PAR) by plant canopy,
reduced radiation utilization efficiency and decreased harvest index of crop plants (Earl
and Davis, 2003). Reduced germination and stand establishment are the foremost
responses of crop plants to water deficit conditions (Kaya et al., 2006). Soil water deficit
at flowering stage usually causes barrenness due to limited translocation of assimilates to
developing kernels below the threshold level that is needed to attain optimum growth of
grains (Yadav et al., 2004). Drought stress causes an osmotic stress that results in loss of
plant turgor, disorganized membrane, more denatured proteins and production of high
amounts of reactive oxygen species (ROS) viz. hydroxyl radical (OH-), superoxide anion
(O2-) and hydrogen peroxide (H2O2) causing oxidative stress. As a consequence, it
disrupts the cellular structures and impairs key physiological process such as inhibition of
photosynthesis, metabolic dysfunctions and damage to cellular structures contribute to
growth perturbances, reduced fertility, and premature senescence that ultimately reduce
the crop yield (Mahajan and Tuteja, 2005; Fahad et al., 2017).
Salt stress is a worldwide problem covering more than 0.8 million ha of arable
land by either sodicity (434 million ha) or salt stress (397 million h) (FAO, 2005; Munns,
2005). It causes 20% reduction in yield potential (Ashraf and Harris, 2005). It is caused
by a combination of the osmotic and ionic stress due to high concentration of Na+ in the
plant rhizosphere (Hasegawa et al., 2000). Various physiological functions such as
biological nitrogen fixation, photosynthesis, respiration and starch metabolism are
adversely effected by salt stress that ultimately losses the crop productivity (Farooq et al.,
2015, 2017). Salt stress limits plant sink, reduces activity of acid invertase in the
developing grains that causes poor grain setting which ultimately leads to reduced grain
yield (Abdullah et al., 2001; Basra et el., 2005; Kaya et al., 2013) and number of grains,
that are responsible for decrease in grain yield (Schubert et al., 2009). Though, salt stress
induced declines in assimilate flux, are furthermore responsible for decreased grain
setting and grain filling, that eventually lowers the crop yield (Lohaus et al., 2000).
Heavy metal contamination is one of the serious environmental issues in the
present time which is increasing with unavoidable pace (Liu et al., 2010). Heavy metals
cause deleterious impacts on plant metabolism (Grimm et al., 2008), which move to
consumer’s body by soil-plant-food interaction that cause some severe deformities in
humans and animals (Chaney et al., 2004). Among these Cd is a broadly spread lethal
toxin for plants, animals and humans, that come into the environment mostly from 4
numerous industrial discharges and man-made activities, containing chemical fertilizers,
pesticides and herbicides application, or irrigation with polluted groundwater and is then
translocated to the food chain (Liu et al., 2010). Most important impacts of Cd toxicity in
plants are growth inhibition, cell membrane disruption, and alteration in enzyme activity
that ultimately reduces the crop yield attributes (Anjum et al., 2015). Cadmium toxicity
reduces the yield and dry weight which might be due to inhibited net photosynthesis
owing to reduced stomatal gas exchange and photosynthetic pigments, decline in
chlorophyll contents related to reduced chlorophyll biosynthesis and disrupted
translocation and accumulation of photosynthetic assimilates that destroys the
ultrastructure of chlorophyll under Cd stress (Anjum et al., 2017a).
Heat stress adversely effects the plant growth, development, physio-chemical
processes and yield (Hasanuzzaman et al., 2012, 2013). Its response varies with time,
duration, and severity of the heat stress (Barnabás et al., 2008). High temperature stress
causes severe heat injury or irreversible damage that leads to the increased production of
ROS which causes oxidative stress (Wahid et al., 2007). It causes changes in
photosynthesis and respiration thereby resulting in a decreased life cycle and crop yield
(Barnabás et al., 2008). Heat stress primarily alters the structure of chloroplast protein
complex and decreases enzyme activity (Ahmad et al., 2010). Heat stress at reproductive
stage lowers the development of morphological units that contribute to harvest index (HI)
(Barnabás et al., 2008). It reduces the number of productive tillers, spikelets and grains
per spike as well as grain weight in maize and wheat (Prasad et al., 2008a, b; Farooq et
al., 2011). According to an estimate every 1°C increase in daily minimum temperature
decreases the rice grain yield up to 10% (Peng et al., 2004). Pollens and anthers were
more sensitive to high temperature and becomes sterile at temperatures ≥30°C (Matsui et
al., 2000), that leads to lower pollen grains development and reduced in vivo pollen
germination (Prasad et al., 2006a; Jagadish et al., 2010).
To cope with abiotic stresses, plants adopt different physiological and biochemical
processes; such as under different abiotic stresses and salt stress the stress resistance is
achieved by selective inclusion or exclusion of ions, ionic compartmentalization,
hormonal regulation, induction of antioxidants, modifications in membrane structure,
production of compatible solutes (Parida and Das, 2005; Farooq et al., 2009a; Fahad et
al., 2017). Likewise, under low water potential the osmotic adjustment is a feature in
plants for the maintenance of tissue water contents (Flowers et al., 2010). Tolerant
genotypes of wheat accumulated greater amount of sucrose when exposed to salt and 5
drought stresses as compared to the sensitive genotypes (Kerepesi and Galiba, 2000). In
plants, resistance against abiotic stresses can be improved by transgenic approaches and
plant breeding. However, it is complex, difficult and time requiring process. Moreover,
genetically modified plants remain un-accepted for some areas of the world (Wahid et al.,
2007).
In this scenario, seed priming is an attractive option as it is a cost effective,
simple, low risk and short gun approach to overcome the salt and drought problems
(Farooq et al., 2009b). It is a controlled hydration process of the seed performed near a
level where the germination associated metabolic events start without actual germination
(Farooq et al., 2006a). It can be done with water (hydropriming), solutions containing
salts, hormones, osmolytes as well as microbial inoculants. Seed priming improves
germination as well as seedling growth under normal and salt stress areas (Basra et al.,
2005). Pre-sowing seed treatments with inorganic or organic substances and/or with high
or low temperature improve plant growth and yield under abiotic stresses (Cantliffe,
2003). Seed priming with KCl improves wheat yield under salt and drought stress
conditions (Ghana and Schillinger, 2003). Seed priming with hormones, inorganic solute,
or antioxidant composites improves water utilization efficiency under drought conditions
(Ajouri et al., 2004), enhance salt stress tolerance (Basra et al., 2005), and enhances
activity of catalase (CAT) and superoxide dismutase (SOD) which are responsible for
protection of plants from oxidative stress (Basra et al., 2004).
Plant growth promoting bactaria (PGPBs) have the potential to improve the
growth and physiological functions in stressful conditions such as microbes induce
several natural processes to maintain plant growth under stressed environments (Yang et
al., 2008; Vardharajula et al., 2011). Plant growth promoting bactaria efficiently
colonizes the different crops, and are capable for improving the stand establishment,
growth, development and yield through stress mitigation and improves the root growth
that ultimately increase the nutrient availability to plants (Hardoim et al., 2008; Naveed
et al., 2014a). Microbes produce certain hormones, which are responsible to control the
root growth and efficiency. Plant root exudates produce tryptophan; PGPBs use it as
precursor to produce auxin in the root zone that alters the plant root architecture, increase
the total surface area of roots, which subsequently increase the water and nutrient uptake
in plants (Somers et al., 2004; Miliute et al., 2015). Moreover, some PGPB strains
promote plant growth under normal and stressed conditions through triggering certain
mechanisms for instance induced systemic resistance, lowering the production of stress 6
induced ethylene and exopolysaccharides (Sandhya et al., 2009; Saharan and Nehra,
2011; Upadhyay et al., 2011). Ethylene acts as phytohormone which affects the plant
growth at low levels (Glick et al., 2007), and its concentration usually rises under stressed
conditions (Zapata et al., 2007).
Certain PGPB contains ACC-deaminase, which degrades ACC (precursor of
ethylene) into ammonia and α-ketobutyrate in root vicinity (Glick et al., 2007). In this
way the inhibitory effects of ethylene on root growth of plants are supressed by PGPB
(Barnawal et al., 2012; Chen et al., 2013a). Under saline conditions, plants face the
nutritional imbalance and specific ion toxicity, and a high K+/Na+ ratio is extremely
important (Hamdia et al., 2004). Some PGPBs produce exopolysaccharides that binds the
Na+ and produced biofilm help in maintaining the high ratio of K+/Na+ in plants (Khodair
et al., 2008; Qurashi and Sabri, 2012). Furthermore, PGPB produce exopolysaccharides
that induce desiccation tolerance in microbes as well as plants and enable them to keep
their growth in pace under drought stress (Sandhya et al., 2009).
Proper sowing time is important for higher barley productivity as there are
problems associated with early and late sowing rearding stand establishment and grain
filling. Furthermore, under field conditions abiotic stresses severely affect barley growth
and productivity. Seed priming is a low cost, simple and shotgun approach that improves
crop stand establishment, and ameliorates the effects of harsh climatic conditions and
abiotic stresses. Moreover, seed priming with inorganic salts and PGPBs can be a viable
technique to improve barley stress tolerance and enhance barley productivity. It was
hypothesized that seed priming will improve the barley performance by improving stand
establishment, and modulating physiological and biochemical processes under late sown
and abiotic stress conditions. However, there is limited knowledge on underlying
processes. Therefore, this study was conducted with objectives to (i) improve the
productivity of late sown barley by seed priming, (ii) evaluate the potential of seed
priming treatments in improving the performance of barley under drought, salinity, heat
and cadmium stresses, (iii) monitor the physiological, biochemical and proteomic basis of
priming-induced resistance against abiotic stresses in barley. Moreover, the role of seed
priming with water, CaCl2 as well as PGPBs in resistance against abiotic stresses in
barley was also studied.
7
CHAPTER 2
REVIEW OF LITERATURE
2.1. Sowing Time
Optimum sowing time has a very important effect on crop growth and
productivity; as early sowing gives high grain yield in barley while; in case of late sowing
after the 1st week of December significantly decreases the barley yield. It shortens the
growing period and crops are exposed to late season high temperature stress during grain
filling period (Hossain et al., 2003; Yau, 2003). Proper sowing time ensures a good stand
establishment that is the main factor affecting crop productivity (Hossain et al., 2003).
Chen et al. (2003) suggested that winter wheat planted earlier, had the high economic
yield while; late planted crop significantly lowered the wheat yield. Better crop yield due
to sowing at optimum time is attributed to better emergence and stand establishment that
results in greater productive tillers and spikes per unit area (Yau et al., 2010).
2.1.1. Emergence and stand establishment
Sowing time has a significant effect on emergence and stand establishment which
is mainly associated with variation in temperature. It has been observed that late sowing
causes a reduction in emergence and stand establishment due to prevailing low
temperature at the time of sowing (Farooq et al., 2008a). Temperature <12°C causes
uneven and decreased emergence and stand establishment (Timmermans et al., 2007).
Reduction in emergence reults in less number of plants and tillers per unit area resulting
in significantly reduced crop productivity under late sown conditions (Farooq et al.,
2008a). Akhtar et al. (2012) reported that late sowing of wheat caused a reduction in
percent of final emergence which resulted in less fertile tillers and grain yield.
2.1.2. Growth and development
Optimum sowing time is essential for better stand establishment and growth of
crop plants. Late sowing produced less plant height as compared to early sowing as high
temperature during vegetative stage reduced the plant height, tiller formation, and growth
and development (Choudhury and Wardlaw, 1978). If barley is sown at optimum time it
results in higher number of productive plants and grains per spike, as compared to late
sowing (Knapp and Knapp, 1978). Late planted barley may have more chances of heat
shock that leads to less number of productive tillers, lower grain weight and number of
grains per ear (Tashiro and Wardlaw, 1999). Recently, Alazmani (2015) had suggested
8
that sowing of barley from last week of November to 5th of December showed maximum
plant height, grain yield and harvest index. It was noticed that in case of late sowing
increase in the ambient temperature at late vegetative growth stage reduced the plant
growth that ultimately lowered the crop yield. Farooq et al. (2008a) reported that late
sown wheat had lower CGR, TDM and LAI that fetched in reduced biological and grain
yield.
2.1.3. Effect of sowing time on crop yield
Timely sown barley gives higher yield and net returns. To obtain better yield, the
sowing time should be chosen to ensure favorable climatic conditions during the whole
growing period. Late sowing had significantly reduced plant height, number of fertile
tillers, spike length and panicle length (Ehdaie and Waines 1992; Alisial et al., 2010).
Early planted crop experience optimum temperature during reproductive period and attain
greater grain yield than late sown crop (Musick and Dusek, 1980). However, late planted
barley crop may be exposed to high temperature during reproductive phase that reduces
the productive tillers, grain weight and number per ear. Nevertheless, increase in
temperature during reproductive phase shortens the growing period and grain filling
duration (Tashiro and Wardlaw, 1999). Wajid et al. (2004) described that every day delay
in sowing decreases the grain yield of wheat by 39 kg/ha. Early planted crop gave higher
number of productive tillers, grain number and weight, and grain yield as well than late
planting (Alam, et al., 2006; Alisial et al., 2010). Alam et al. (2006) observed that sowing
date significantly affected the yield and related traits. Moreover, Singh et al. (1989)
noticed that late sown barley had less grain yield than early sown crop.
Early planted barley exhibits better stand establishment that consequently leads to
greater number of tillers and spikes per unit area, and grain yield by 61% because plants
have longer growth period as compared to the late sown barley (Wajid et al., 2004;
Ozturk et al., 2008). Juraimi et al. (2009) observed that when sowing of teff was delayed
by 7 and 15 days reduced plant height by 23 and 32%, spike length by 46 and 55%,
biological yield by 34 and 36%, and grain yield by 60 and 68%, respectively. Similar
results were reported by Razzaque and Rafiquzzaman (2006) that yield and related traits
i.e. spikes per m-2, grains per spike and grain weight of barley were negatively influenced
by delayed sowing as compared to timely sowing.
2.1.4. Effect of late sowing on grain quality
Late sowing negatively influences the grain quality in cereals. It was observed that
late sowing caused increase in seed dormancy in barley as compared to optimum sowing 9
time (Samarah and Al-Issa, 2006). Early planted barley had more grain protein contents
due to healthier plants with longer root systems that caused higher uptake of residual
nitrogen and had more time for grain filling as compared to late sowing (Ozturk et al.,
2008). Seleiman et al. (2011) found that late sowing reduced grain carbohydrates, as
compared to early sowing.
Late sowing exposes the plants to terminal heat stress that shortens the grain
development period as a result poor quality and shriveled grains are achieved (Ehdaie et
al., 2006; Kaur and Behl, 2010; Farooq et al., 2011). Similar results were observed in
another study that in case of late sowing occurrence of high temperature during
reproductive stage negatively affected the anthesis and grain filling duration (Tashiro and
Wardlaw, 1990), which led to poor seed vigor and grain quality as compared to early
sowing (Gooding et al., 2003; Ehdaie et al., 2006). In case of late sowing the temperature
above 30 °C during grain development stage not only altered the composition and
functions of grains but also modified the size and distribution of starch granules.
Moreover, it also increased the ratio of amylose to amylopectin but decreased the ratio of
glutenin to gliadin ratio that negatively affected the dough elasticity (Hurkman et al.,
2003).
2.2. Abiotic stresses
Changing climate can severely hamper crop productivity as crop plants are
exposed to abiotic stresses. Plant exposure to abiotic stresses induce a disruption in plant
metabolism, threaten the plant survival and the production of biomass implying at
physiological costs, thus leading to a reduction in growth can reach up to 50% in most
plant species hence, threatening the world food security (Vorasoot et al., 2003; Thakur et
al., 2010). It has been observed that abiotic stresses concequences in 50% yield reduction
in major field crops (Bray et al., 2000). Salinity, high temperature, drought and heavy
metals toxicity stress especially Cd occurring in combination or one after another which
progress into oxidative stress and cause severe cellular injury (Wang et al., 2003; Fahad
et al., 2015).
2.2.1. Drought stress
Drought is a serious hazard to world food security (Somerville and Briscoe, 2001).
Its severity depends upon occurrence and distribution of rainfall, scarcity of water
resources and evaporative water demands (Wahid and Rasul, 2005). Water is essential for
plants as growth occurs by division, elongation and differentiation of cells. However,
water deficit conditions adversely affect all these processes because cell growth is 10
drought-sensitive caused by loss of turgor pressure of the plant (Taiz and Zeiger, 2006).
Under drought stress, lowered soil moisture content may rise the soil temperature that
shows deleterious effects on growth of plants (Sekhon et al., 2010; Anjum et al., 2017b).
Drought stress affects several yield determining physiological processes viz. plant water
uptake is inhibited that leads to loss of turgor pressure of plant as a result reduced the rate
of mitosis, elongation as well as expansion of cell occurs (Nonami, 1998; Taiz and
Zeiger, 2006).
2.2.1.1. Crop growth and development
Early effects of drought stress are poor germination and stand establishment
(Kaya et al., 2006). Water deficit impairs germination and seedling growth in pea plants
(Okcu et al., 2005). Another study also described, that alfalfa plants exposed to
polyethylene glycol induced drought stress inhibited germination, shoot elongation and
seedling fresh and dry weights, except root length (Zeid and Shedeed, 2006). Plants
exposed to drought stress leads to significant reduction in leaf water status, rate of
photosynthesis and transpiration, leads to a substantial rise in plant leaf temperature and
early leaf fall (Wahid and Rasul, 2005). Drought stress adversely affects the crop growth
and development as it lowers the plant height and leaf area (Kaya et al., 2006; Hussain et
al., 2008). Deficit water stress decreases the water uptake; as a result plants close their
stomata to save moisture content that confines the CO2 uptake by leaf stomatal openings
and transpirational losses. It causes reduction in photosynthetic rate and assimilates
translocation to the plant that is necessary for grain filling. It results in increased
production of ROS and lipid peroxidation that disturbs the structure and function of
macromolecules (Rio et al., 2006; Kaya et al., 2006).
Drought significantly decreases the production of productive tillers and grains
number per ear that leads to reduction in grain yield of barley. Though water deficit
conditions affect the plants throughout its life cycle but reproductive stage is more
deleterious to economic yield of plant (Samarah, 2005; Kaya et al., 2006). At pollination
stage drought stress decreased the pollen viability and germination in maize crop, while at
flowering stage it reduced economic yield up to 40-55% in pigeon pea (Nam et al., 2001).
It is known that water deficit conditions reduce grain filling period and economic yield in
different crop plants (Samarah, 2005; Estrada-Campuzano et al., 2008).
2.2.1.2. Water and nutrient relations
Water is essential for plant mineral nutrition and drought stress affects the nutrient
uptake. Optimum soil water status coupled with fertilizer application increases the crop 11
growth and yield. Similar findings were reported by Abayomi and Adefila (2008) that
fertilizer application significantly increased the achene yield of sunflower at optimum soil
water conditions. Likewise, water deficiency disturbs the nutrient metabolism i.e. inhibits
the activity of nitrate reductase and glutamine synthetase (Rizhysky et al., 2004).
Moreover, drought stress causes 50% reduction in calcium uptake that disrupts the cell
membranes and other structures in maize.
2.2.1.3. Root-shoot signaling
Plants can survive in a wide range of environment through signal transmission that
regulates the plant behavior and growth rate. Plants sense environmental stresses and
signal is transmitted from root to shoot thus growth and functions of both shoot and root
are limited (Novák and Lipiec, 2012). Some plants develop shallow root system that
restricts water loss from their roots and survive under drought stress. Plants responses to
drought stress depend upon the rate of water uptake, leaf stomatal conductance, water
potential and turgor pressure that ultimately lowers the leaf elongation (Clark et al.,
2005). Short term exposure to drought increases root growth but long term exposure
reduces the root growth due to limited production of assimilates (Muller et al., 2011).
Furthermore, long term exposure to drought stress also reduces cation exchange capacity
of roots, nutrient uptake and relative uptake of the polyvalent cations especially
aluminum and heavy metals is increased which induces specific ion toxicity that further
decreases root growth and increases mortality rate (Huang and Eissenstat, 2000; Sekhon
et al., 2010; Lukowska and Józefaciuk, 2013).
2.2.1.4. Metabolic and biochemical processes
Water deficit conditions alter the metabolic and biochemical processes of plants. It
increases the ROS production such as super oxide anoin (O2-), singlet oxygen (O*), H2O2
and OH- (Anjum et al., 2017c). This results in oxidative stress that damages the
membranes and proteins and inhibits the enzymes activity (Zlatev and Lidon, 2012). In
response to oxidative stress plants activate the antioxidant enzymes that detoxify the
ROS. Moreover, plants produce certain metabolites that maintain the plants structures and
functions under drought stress (Farooq et al., 2009a; Zlatev and Lidon, 2012). However,
prolonged water deficit condition causes anatomical deformations, root shrinkage, and
weakens the roots-soil contact that restrict the water and nutrient supply to plants.
Drought stress reduces the biosynthesis of photosynthetic pigments, damages the
photosynthetic machinery and decreases the activities of important enzymes (Fu and
Huang, 2001; Monakhova and Chernyadèv, 2002). It might be attributed to disturbed 12
balance between the generation and detoxification of ROS through poor antioxidants
defense system (Reddy et al., 2004). It degrades the chlorophyll contents and disturbs the
ratio of chlorophyll to carotenoids contents that further induces the leaf senescence in
various crops (Yang et al., 2002a). Wheat seedlings exposed to drought stress for 7 days
caused 13-15% decrease in chlorophyll pigments and 30-40% decrease in soluble proteins
content (Chernyad’ev and Monakhova, 2003; Nikolaeva et al., 2010).
2.2.1.5. Plant biomass and yield
Water deficit stress disrupts a number of biochemical as well as physiological
processes in plants, which results in reduced growth and yield of many field crops . Effect
of drought stress varies with intensity, duration and time at which crop was exposed to
stress conditions (Plaut, 2003). Under mild drought stress plant biomass production is
more affected as compared to photosynthesis (Verelst et al., 2012). However, the rates of
photosynthesis and transpiration are considerably decreased under severe drought stress
than control (Zhang et al., 2010). Both drought and heat stress reduces the duration of
developmental growth phases and light interception couples with shortened life cycle that
might be responsible for yield reduction in cereals (Barnabás et al., 2008). It lowers the
accumulation of plant biomass, shortens the first internode length, causes premature cell
death, early senescence, fruit discoloration and damages in several plants (Vollenweider
and Gunthardt, 2005; Zlatev and Lidon, 2012). It was observed on the basis of drought
susceptibility index and water stress index that grain yield decreased significantly under
drought conditions in maize and barley (Rizza et al., 2004; Abayomi et al., 2012).
Water deficit conditions cause a significant reduction in economic yield of barley
by decreasing number of productive tillers, shriveled and fewer grains per spike, and
reduced grains test weight. It might be since drought stress decreases duration of the grain
filling stage that further reduces the activities of sucrose synthase and starch synthase as
well as extent of assimilates partitioning. It increases the time duration between silking to
anthesis stage, which leads to reduced grain yield in maize crop (Cattivelli et al., 2008).
In cotton, drought stress enhanced the flower shedding and bolls abortion that further
reduced the seed cotton and lint yield (Pettigrew, 2004).
2.2.2. Salt stress
Saline soils have excess level of soluble salts or exchangeable sodium in plant
rhizosphere. Owing to high crop water demand, limited rainfall, combined by poor water
and soil management the salinity has come to be a grave hazard to global food security
(Munns, 2002). 13
2.2.2.1. Growth and development
Salt stress negatively affects growth and development of crop plants. Deletrious
effects of salt stress vary on the basis of time, severity, duration, type of plant tissues,
stage of plant growth, and either the stress occurs slowly or suddenly (Munns et al.,
2000). Chaum and Kirdmanee (2009) had reported that progressive increase in salt stress
gradually decreased the seedlings fresh and dry weights, and plant leaf area. Salinity
stress alters plant physiological and cellular processes which results in reduced plant
growth and development (Munns, 2002; Munns and Tester, 2008; Munns, 2011). Wheat
crop exposed to salinity at germination and seedling establishment negatively influenced
the crop stand establishment as well as early seedling growth (Munns et al., 2006).
Another study also reported the same results that excess salt concentration in rhizosphere
decreased the final germination percentage and seedling growth in wheat (Afzal et al.,
2006). It might be attributed to salinity induced osmotic or drought stress, ionic stress,
nutrient imbalance and oxidative stress (Munns and Tester, 2008).
Under salt stress both Na+ and Cl- ions accumulated in guava plants that resulted
in reduced growth (Ferreira et al., 2001). Plants show different types of responses
depending upon stage of crop growth and germination is the most sensitive growth stage
(Ahmad and Jabeen, 2005), as seeds are mostly unable to germinate in saline soils.
Another study also showed that salinity stress reduced the flowering and fruit set which
resulted in reduced yield and quality of produce (Ashraf and Harris, 2004).
2.2.2.2. Photosynthesis
Salt stress adversely influences vital processes taking place within plants such as;
photosynthetic rate, protein synthesis and lipid metabolism. It causes a reduction in
stomatal conductance, photosynthesis and enhances the accumulation of salts that exerts
adverse effects on plant growth. Accumulation of salts to toxic levels causes injuries to
the leaves and thereby reduces photosynthetic area by causing the premature death of
older leaves in plants (Munns and Tester, 2008). Moreover, it reduces the photosynthetic
ability, leaf area and CO2 assimilation of many crop plants which results in reduced plant
biomass and yield (Akram et al., 2002). Tolerance of photosynthetic system to salts stress
depends on the efficiency with which plants exclude or compartmentalize toxic ions.
Furthermore, salinity causes a decrease in biosynthesis of the photosynthetic machinery.
It was noticed that salt stress caused a decrease in chlorophyll a and b contents in wheat,
as compared to control (Hanaa et al., 2008). It might be because of increased degradation
14
or decreased biosynthesis of chlorophyll by higher level of Na+ ion and lower level of
Mg2+ ion in plants at severe salinity stress (Rubio et al., 1995).
2.2.2.3. Physiological and biochemical processes
Salt stress lowers the osmotic potential through sodium and/or chloride toxicity,
altering protein synthesis (Farsiani and Ghobadi, 2009), that ultimately reduces the seed
germination (Khaje-Hosseini et al., 2003). It disrupts the mineral uptake, cell membranes,
subcellular and cellular organelles thus decreasing the growth and causing anomalous
development even results in plant death (Yasmeen et al., 2013; Farooq et al., 2015). Salt
stress causes inhibition of cell division and expansion, osmotic imbalance, disturbs
enzyme functioning that leads to higher accumulation of ROS (Mahajan and Tuteja,
2005). Moreover, salt stress disrupts the ion uptake, synthesis of proteins and nucleic
acid, photosynthesis, hormonal balance, activities of enzyme and osmotic adjustment that
ultimately lead to growth retardation (Dumbroff and Cooper, 1974). Salinity lowers the
soil osmotic potential that reduces the root water uptake and plants close their stomata to
save water loss thus reduce the CO2 uptake. Decreased CO2 in mesophyll cells reduce the
rate of photosynthesis and enhances the production of ROS (Ashraf and Harris, 2004).
However, in response to salt stress plants accumulate compatible solutes and osmolytes to
maintain their tissue water status. Salinity reduced the chlorophyll a, b and a+b in sweet
maize plants due to the fact that high concentration of salt stress injury disrupts the plant
structures and functions (Chaum and Kirdmanee, 2009).
Salinity stress negatively affects the de novo synthesis of D1 and other important
proteins (Murata et al., 2007). Furthermore, it suppresses the activity of Rubisco, inhibits
the CO2 fixation and protein synthesis that disturbs the balance between ROS generation
and detoxification. Furthermore, high concentration of Na+ ion in plant tissues reduces the
activity of ATP synthase that decreases the level of intracellular ATP that is crucial for
protein synthesis (Allakhverdiev et al., 2005). It has been observed that, it induces the
photo-damage to PSII in barley, rye and sorghum (Sharma and Hall, 1991; Hertwig et al.,
1992). Another study also reported the similar findings that excess concentration of salt
stress either stimulated the photo-damage to PSII or repressed the repair of PSII (Murata
et al., 2007).
2.2.2.4. Plant biomass and yield
Salt stress affects numerous physiological functions and processes like respiration,
photosynthesis, nitrogen fixation, starch synthesis, and source-sink limitations which are
the main reasons of poor grain setting that ultimately lowers the grain yield (Hiyane et al., 15
2010; Turki et al., 2012). Studies have indicated that salinity stress causes considerable
decline in grain yield (Schubert et al., 2009; Kaya et al., 2013). Under salt stress the salt
concentration in plant parts and tissues is increased to toxic level that diminishes the plant
growth and yield (Ashraf and Harris, 2004; Franzen, 2007).
It has been observed that salinity causes a reduction in number of productive
tillers m-2 and spikelets as well as grains per ear, and biological and grain yield (Ahmad et
al., 2003; Saffan, 2008). Similarly, salinity severely affects the yield and related
parameters of wheat. It was observed that number of spikelets per spike were decreased
much more by salt stress as compared to number of grains and grain weight at maturity
(Salah et al., 2005). Rice seedlings exposed to different levels of salt stress showed
decreased shoot and root dry weight, number of productive tillers, panicle length, number
of kernels per panicle, grain weight and grain yield. Nonetheless, it was observed that
grain sterility was increased with an increase in Na+ accumulation in rice shoots
(Mahmood et al., 2009a).
2.2.3. Osmotic stress
Salt stress causes its deleterious effects in two ways viz. osmotic stress (decline in
water potential) and ionic stress (ionic imbalance and specific ion toxicity) (Parida and
Das, 2005). First and foremost outcome of salt stress is osmotic stress. It occurs
immediately due to the high concentration of salts in the rhizosphere that reduces the
growth of new leaves and shoots (Munns and Tester, 2008). Salinity affects the plant
growth through osmotic preservation of water which decreases plant’s access to water by
increasing the concentration of salt in external environment of plants (Afzal et al., 2006).
Salt stress inhibits the seed germination by limiting the water uptake which concequently
leads to decreased radical emergence (Al-Karaki, 2000). Salt stress affects the
germination of seeds by establishing lower osmotic potential in external environment of
seed which prevents the water imbibition (Khaje-Hosseini et al., 2003). Salt stress
induces both hyper-osmotic as well as hyper-ionic stress that result in a considerable
decrease in crop yield (Mahajan and Tuteja, 2005). High levels of salt stress cause decline
in soil water potential which renders the plants unable to acquire water and nutrients from
soil thereby decreasing growth and development of plants. Salt stress induced osmotic
stress decreases the seedling shoot and root growth (Munns, 2002).
2.2.4. Ion toxicity
The second and slow effect of salt stress is the specific ionic toxicity on
protoplasm which increases salt concentration in plant cells (Munns and Tester, 2008; 16
Tabassum et al., 2017). Salinity-induced ion toxicity perturbs the plant water relations,
disturbs the activity of enzymes, enhances the specific ion toxicity and disrupts the
balance of ROS production and detoxification (Farooq et al., 2015, 2017; Tabassum et
al., 2017). Salt stress affects crop plants at each growth stage beginning from the
germination upto maturity by ionic and/or osmotic stress (Al-Karaki, 2000). Salinity
affects the crop growth and yield by perturbing osmotic and ionic equilibrium within cells
(Mahajan and Tuteja, 2005). Ionic stress occurs over time due to inability of plant to
restrict the influx and enhance the efflux of Na+/Cl− ion in plant tissues (Munns and
Tester, 2008). Salinity effects the germination of seeds both through osmotic stress and
Na+/Cl− ion toxicity to the seeds during imbibition (Khaje-Hosseini et al., 2003). Ionic
stress enhances the senescence of older leaves (Munns and Tester, 2008). Ionic stress
causes deficiency or toxicity of essential nutrients and tissue injuries (Munns and Tester,
2008). Osmotic stress inhibits more shoot growth than root growth (Hsiao and Xu, 2000).
2.2.5. Heavy metals stress
Heavy metals are a set of semi metals (metalloids) and metals which are related to
pollution combined to potential toxicity (Granero and Domingo, 2002; Govil et al., 2008).
Owing to their variation in concentrations, toxicity levels, speciation and specifications,
they pose a severe risk to crop productivity, thus directing a widespread series of plants
(Arshad et al., 2008). Among several heavy metals that affect plants, Cd is most toxic
pollutant after lead (Pb). Depending upon its toxicity in plants which influence the plant
growth and development, different plant species and cultivars behave differently under
varied concentration of Cd as some cultivars are sensitive to even very low concentrations
while others are tolerant to very high concentrations (Fahad et al., 2015). Its easy uptake
and translocation within plants make it more toxic to affect several morphological,
physiological, biochemical and structural events of the crop plants (Xu et al., 2014; Fahad
et al., 2015). Cadmium toxicity increases the cell membrane permeability and leakage of
electrolytes following ROS production at cellular and sub-cellular levels that creates
oxidative stress. It enhances the lipid peroxidation and damages to macromolecules with
concomitant cell death that ultimately leads to stunted plant growth (Mahmood et al.,
2009b).
2.2.5.1. Seedling growth
High Cd concentration in rhizosphere causes reduced rate of photosynthesis,
evaporation, transpiration, cell metabolism, water and nutrient uptake, inhibition of
enzymes activities, deficiency of nitrogen and phosphorus. All these leads to inhibited 17
growth and accelerated maturity, even death of plant (Cheng and Huang, 2006).
Furthermore, Cd stress causes the osmotic stress. Cadmium stress reduced the seedling
growth and development in maize, when compared with control (Malekzadeh et al.,
2007). Tiryakioglu et al. (2006) observed similar results in barley that Cd toxicity stress
caused reduction in root and shoot elongation especially elevated level of Cd was more
deleterious to root growth than shoot growth. It might be because roots come in contact
directly to Cd as compared to shoot. Kumari et al. (2011) reported that Cd stress reduced
fresh and dry weight of Vigna radiata L seedlings. Similar results were observed in
another study due to its negative effect on the photosynthesis rate (Metwally et al., 2003).
Gradual decrease in seedling growth of Leucaena leucocephala was observed with
progressive increase in Cd concentration (Muhammad et al., 2008).
2.2.5.2. Morphological and biochemical processes
Cadmium directly and indirectly affects plant metabolism as it causes the
oxidative stress. It has been observed that chloroplast is sensitive to Cd toxicity (Sandalio
et al., 2001). It disturbs the balance between ROS production and detoxification as a
result inhibits the functions of photosystem II (PSII) (Sigfridsson et al., 2004). Cadmium
stress reduces the total carbohydrates content and increases the total soluble sugar content
in seedling of V. radiata L. as compared to control. Moreover, it has been observed that
Cd toxicity stress decreases the soluble proteins content in V. radiata L. seedlings (Verma
et al., 2012). Cadmium stress causes chlorosis, leaf rolling, necrosis, and reduces the
activity of enzymes that inhibit the photosynthesis and transpiration (Gouia et al., 2000;
Benavides et al., 2005). Aditionally, it disrupts the plant water status through lowered
relative water content, increased stomatal resistance and reduced root and leaf expansion
(Perfus-Barbeoch et al., 2002).
Cadmium stress disturbs the nutrient balance, modifies the genes expression and
enhances the production of ROS (Herbette et al., 2006; Sandalio et al., 2009).
Furthermore, it causes severe damages to cell constituents viz. DNA, RNA, proteins and
lipids that leads to decreased growth (Schutzendubel and Polle, 2002; Grara et al., 2012).
In response, plants had developed a complex antioxidant defense system (enzymatic as
well as non-enzymatic) to detoxify and scavenge these ROS and protect cellular
membranes and macromolecule (Pinto et al., 2003). A short term exposure to Cd stress
increases the activity of antioxidant enzymes but prolonged exposure decreases activity of
these enzymes (Sandalio et al., 2001).
2.2.6. Heat stress18
Rise in the ambient temperature beyond a threshold for time span which induces
permanent damage to growth and development of plants is reffered to as heat stress. It is a
complex function of intensity (in degrees) and the rate of increase in temperature, and
duration (Wahid et al., 2007). The magnitude to which heat stress ensues in a specific
climate zone depends on the likelihood and period of the high temperature which occurrs
during day and/or night. The heat stress caused by high ambient temperature is becoming
the serious menace for crop production all over the world (Hall, 2001). Generally, 10-
15°C sudden increase in temperature above ambient is termed as heat stress. An estimate
has been made that with every 1°C rise in atmospheric temperature soil temeperature
could increase by 1.5°C (Ooi et al., 2012). Severe cell damages and/or even death could
be caused by short-term exposure to very high temperature within a short time (Schoffl et
al., 1999); while, it might take a long time until cellular damages under moderate high
temperature. The denaturation and/or aggregation of proteins with concomitant increase
in fluidity of cell membrane lipids are the direct harms caused by high temperature stress.
However, slower or indirect injuries due to heat stress consist of enzyme inactivation in
the mitochondria and chloroplast, protein degradation, inhibition of the protein
biosynthesis and decreased stability of cellular membranes (Howarth, 2005).
2.2.6.1. Growth and development
Heat stress adversely effects the growth and development of crop plants. Mild
heat stress speed up the growth rate but severe heat stress causes reduction in rate and
duration of growth in wheat plants. It causes seedling growth inhibition, leaf abscission,
leaf chlorosis and necrosis, which results in reduced biomass and economic yield
(Vollenweider and Gunthardt, 2005). High temperature from the germination to grain
formation shortens the plant life cycle (Wollenweber et al., 2003). Spring wheat sown at
high night temperature significantly decreased the duration of three important growth
stages (flowering, grain formation, and maturity) (Prasad et al., 2008a). Heat stress
decreased the shoot length, leaf number and dry weight in wheat. Furthermore, it reduced
the spike bearing tillers m-2, floral organs, grain formation and grains per spike (Yang et
al., 2002b; Prasad et al., 2008a).
2.2.6.2. Photosynthesis and transpiration
Optimum temperature is very important for photosynthesis and transpiration.
However, rise in temperature from 22 to 32°C lowers the rate of photosynthesis and
transpiration (Zhang et al., 2010). Furthermore, it has been observed that both heat and
drought stress reduces the stomatal conductance and photosynthetic activity (Crafts-19
Brander and Salvucci, 2002; Ashraf and Harris, 2013). Abrupt rise in leaf temperatures (>
38°C) is more deleterious for net photosynthesis rather than gradual increase in
temperature (Crafts-Brander and Salvucci, 2002). It might be attributed to a decrease in
internal CO2 concentration, activity of enzymes that were responsible for photosynthesis
and ATP synthesis (Zlatev and Lidon, 2012).
Among various physiological processes photosynthesis is the most sensitive one
to high temperature. As a short term exposure to high temperature disables the activity of
Rubisco and oxygen-evolving complex of PSII (Haldimann, and Feller, 2004; Suleyman
et al., 2007). Heat stress suppresses the efficiency of photosystem (PSII) through limiting
the transport of electrons, external proteins degradation/removal, and release of Mg2+ and
Ca2+ from their binding sites (Wahid et al., 2007; Barta et al., 2010). As a result, reaction
center of chlorophyll (PSII) produces singlet oxygen which concequently damages the D1
and D2 proteins in chloroplast (Yoshioka et al., 2006). Heat stress disrupts the balance
between damage and repair to PSII complex of photosynthesis. Moreover, it suppresses
the de novo synthesis of D1 and other essential proteins (Murata et al., 2007).
2.2.6.3. Molecular and biochemical processes
Heat stress denatures the proteins; increased fluidity of membrane bounded lipids,
inactivates the enzymes, reduces de novo protein synthesis and disrupts the membrane
integrity (Howarth, 2005; Kozlowska, 2007). If plants are exposed to moderate heat stress
they may face severe cellular injury, decrease in biosynthesis of chlorophyll, increase in
amylolytic activity, dissolution of the thylakoid grana and interruption of the assimilate
transport or even death at short term exposure to very high temperature (Kozlowska,
2007; Wahid et al., 2007). Furthermore, it reduces the ion fluxes and enhances production
of ROS and toxic compounds that may harm cells (Howarth, 2005).
2.2.6.4. Yield and yield related traits
Heat stress affects the plants from flowering to grain filling stage that leads to
often reduced crop yield due to limited growth of grains (Guilioni et al., 2003). Heat
stress prevailing during grain formation modifies seed nitrogen contents in grains of
legume crops (Sekhon et al., 2010). Furthermore, it reduces the grain protein content,
starch granules and oil contents in maize and wheat (Wilhelm et al., 1999). It also affects
the grain formation and baking quality of the flour in cereals (Balla et al., 2011).
Moreover, heat stress when combined with drought stress shows more deleterious effects
on grain yield and quality compared with alone heat stress (Balla et al., 2011).
20
Under heat stress abnormal ovary formation combines with poor pollen tube
development causing shriveled pollens and reduced grains per spike (Saini and Aspinall,
1982; Saini et al., 1983). Another study had shown that pollens are highly sensitive to
high temperature as it reduced the floret sterility, pollen germination and viability (Prasad
et al., 2006a). Similar results have been observed in rice (Prasad et al., 2006b), wheat
(Prasad et al., 2008a), peanut (Prasad et al., 2011a), barley (Sakata et al., 2000) and
sorghum (Prasad et al., 2011a) that heat stress diminished the formation, viability and
longevity of pollens that ultimately leads to pollen shedding and poor grain setting. Heat
stress induced leaf senescence decreases the activity of starch synthase, assimilates
translocation and partitioning to the developing grains that results in smaller and shriveled
grains (Prasad et al., 2006b, 2008b). Yang et al. (2002a) and Prasad et al. (2008a)
described that heat stress 10°C above ambient temperature (20/15°C) causes up to 50%
decline in final grain weight and 70% in grain yield of wheat plants.
2.3. Mechanisms of abiotic stresses tolerance
2.3.1. Drought stress
Plants respond to drought stress alterations in morphological, biochemical and
physiological attributes (Farooq et al., 2009a). Change in leaf and root architecture,
stomatal closure to avoid water loss, production and accumulation of compatible solutes,
osmotic adjustment, and production of abscisic acid (ABA), and induction of the
dehydrins are few mechanisms which have been evolved by plants to tolerate drought
stress by maintaining high leaf water potential and tissue water status (Turner et al.,
2001). The drought resistance is capability of crop plants to maintain better growth and
produce biomass with limited water supply or deficit water conditions (Passioura and
Angous, 2010).
Osmotic adjustment is an essential drought tolerance mechanism which assissts
the plants in surviving under dehydration conditions (Farooq et al., 2009a). It is
accomplished by accumulation of a variety of osmotically active ions or molecules such
as proline, glycine betaine, sugar alcohols, soluble sugars, sorbitol, trehlose, glutamate,
citruline, organic acids, K and Ca ions (Folkert et al., 2001; Serraj and Sinclair, 2002;
Farooq et al., 2008b; Farooq et al., 2009a). Under drought stress, plants accumulate these
solutes which lowers their osmotic potential and consequently water moves into cells
from the surroundings thereby maintaining the cell turgor and continue metabolic
activities in cells. With osmotic adjustment, activities of cytoplasm and cell organelles
continue normally which help the plants to maintain better growth, photosynthetic 21
activities and assimilate partitioning to developing grains (Ludlow and Muchow, 1990;
Subbarao et al., 2000).
Membrane stability is an important index for drought tolerance (Folkert et al.,
2001). In plants, the ROS are produced as a byproduct in response to numerous metabolic
activities (Rio et al., 2006). These ROS may serve as damaging, signaling or protective
elements depending on the equilibrium in synthesis and detoxification. The osmolytes
produced by plants rescue the cellular membranes from ROS (Folkert et al., 2001; Farooq
et al., 2009a). Moreover, antioxidants are produced by plants for protection from ROS in
response to abiotic stresses (Gill and Tuteja, 2010). Plants accumulate free leaf proline in
greater concentrations under drought which acts as osmoprotectant and/or compatible
solute, and induces drought tolerance in plants (Yamada et al., 2005). Molecular
mechanisms for drought tolerance include the production of ABA, and expression of
stress responsive genes and some transcription factors which are responsible for induction
of stress tolerance in plants (Farooq et al., 2009a).
Abiotic stresses prompt the expression of groups of two types of genes. First type
of group of genes are accountable for the protection of cells by enancing the osmolytes,
detoxifying damaging compounds, protecting and recycling proteins, and maintaining the
stability of cellular membranes (Shinozaki and Yamaguchi-Shinozaki, 2000); whereas,
econd type of group of genes involves expression of regulatory genes under stressed
conditions (Seki et al., 2003). Proline, an osmolyte, which is enhanced in response to
drought in the transgenic plants carries the gene coding for the osmolytes, thus making
the mechanism of protection against the oxidative-stress rather than osmotic-adjustment
(Vendruscolo et al., 2007). Wheat plants respond to drought by efficient assimilate
remobilization from the stem to grains by synchronized gene-expression which may
protect the premature cell death of wheat stem (Bazargani et al., 2011).
2.3.2. Salt stress
Water status, hormonal regulation and the availability of photosynthates are main
controlling elements in saline or drought conditions; while, in saline soils the hormonal
balance is more critical than water status (Munns, 2002). Salt resistance may be defined
as the genetic potential of a plant to withstand the damaging effects of salt stress in their
leaves and/or rhizosphere while avoiding the disturbance in their normal functioning
(Shannon and Grieve, 1999). Osmotic adjustment is an important echanism in plants
which are adapted to low water potential induced by salinity (Flowers et al., 2010).
Compatible solutes are osmoticum produced for safer accumulation but it requires energy 22
and hence the plants have to suffer the decreased growth rate (Munns and Tester, 2008).
Ionic balance is an important tool to maintain the normal plant metabolism under salt
stress. Plants control the expression of H+ pumps, and Na+ and K+ transporters to enhance
the uptake of ions which act as osmolytes and/or osmoprotectants such as K+, Mg+2 and
Ca+2 while restrict uptake of Na+ and Cl- ions by roots (Zhu et al., 1993).
Primarily, plants employ different mechanisms to tolerate the salinity stress such
as to avoid the entry of Na+ and Cl- ions in high concentrations in different plant parts but
if salts enter in plants then plants try to protect the plant tissues through ion exclusion
from roots or compartmentalization of these ions into cell vacuoles (Silva et al., 2010).
Another study also described the same adaptive mechanism for salt tolerance that plants
either exclude the salt from roots or store them in their vacuoles (Munns and Tester,
2008). Plants generate the proton motive force and exchange the Na+ with H+ ions
through plasma membrane H+-ATPase. Similarly, plants use the tonoplast H+-ATPase and
H+-pyrophosphatase proteins for vacuolar compartmentalization (Rodríguez et al., 2009;
Ye et al., 2009; Leidi et al., 2010; Pasapula et al., 2011). Salt tolerant plants develops the
high concentration of Na+/H+ antiporter (NHX1) to limit the sodium and chloride ion
inclusion (Pasapula et al. 2011). Plants overexpress the salt tolerance responsible
AtNHX1genes to sequestrate high concentration of Na+ and Cl- ions (Leidi et al., 2010;
Silva et al., 2010).
For long time exposure to salt stress plants produce or accumulate high
concentration of osmolytes like; proline, glycine betaine, polyols, sugars (fructose and
sucrose), polyamines and organic acids (malate, oxalate) (Valliyodan and Nguyen, 2006).
Production of ROS possess secondary stress in saline condition (Chaves et al., 2003) and
plants produce such substances which detoxify these detrimental species. Some enzymes
act as scavengers of these destructive oxygen species. Garratt et al. (2002) has mentioned
these enzymes such as CAT, SOD, glutathione reductase (GR) and glutathione-S-
transferase (GST). Plants manipulate these enzymes to synthesize osmolytes and
osmoprotectants which helps in osmotic adjustment and scavenging of ROS (Krishnan et
al., 2008; Chen and Murata, 2008). Another study also supports the same concept that
under salt stress plant accumulates high concentration of proline that not only helps in
osmotic adjustment but also maintain the cellular activities under salt stress conditions
(Verdoy et al., 2006).
2.3.3. Cadmium stress
23
Cadmium is potentially toxic for both plants and animals even at very low
concentrations can cause severe damages. Plants have developed several mechanisms to
resist/tolerate the Cd stress such as; lower uptake as well as accumulation of cadmium in
plant parts. Among the tolerance mechanisms plants use the metal chelation and
sequestration through particular ligands. For that purpose, plants accumulate both Cd and
metal-binding ligands such as; phytochelatins (PCs) and metallothioneins (MTs) in their
vacuoles (Hall, 2002; Cobbett and Goldsbrough, 2002). Plant accumulates phytochelatins
to bind the cadmium ions through PC-Cd or Cd-malate complexes in their vacuole
(Cobbett and Goldsbrough, 2002).
Hyperaccumulation is another adaptive and complex phenomenon to accumulate
high metals concentration in their shoots such as edible leaves and maintain a low metal
concentration in their roots (Kramer, 2010). Hyperaccumulation is the ability of some
metal tolerant plants to safely store high metal levels in their tissues without facing any
cellular damage. Metal hyperaccumulation is the molecular mechanisms for the
development of phytoremediation and biofortification technologies (Kramer, 2010; Shao
et al., 2010). It includes the transport of metal across the plasma membrane of root cells,
xylem loading and translocation, metal detoxification and sequestration at plant and
cellular levels (Lombi et al., 2002).
Cadmium toxity stress causes oxidative stress and plants synthesize and
accumulate high concentration of glycine betaine, proline, sugars, organic acids, polyols,
amino acids, and peptides and polypeptides (Rauser, 1999; Gill and Tuteja, 2010).
Another study also described the similar results that under Cd stress, plants use PCs to
detoxify the ROS (Maier et al., 2003). Furthermore, plants detoxify or scavenge the ROS
through enzymatic (SOD, CAT, ascorbate peroxidase and glutathione peroxidase) and
non-enzymatic antioxidants (α-tocopherol and ascorbate) (Pinto et al., 2003).
2.3.4. Heat stress
Under heat stress plant adopt several mechanisms to survive in such lethal
conditions. Heat tolerant plants acquire thermo-tolerance mechanism through pre-
exposure to sub-lethal temperature to cope with heat stress (Wahid et al., 2007). Plants
use heat-shock proteins (HSP32 and HSP101), ABA signaling, regulate gene expression
and systematic acquired pathway to protect plant cellular structures against heat stress
(Larkindale and Huang, 2005; Charng et al., 2006). Stress perception and signal
transduction is another adaptive mechanism for heat stress tolerance (Chinnusamy et al.,
2004). Plants use Ca2+ signaling pathway, plant stress related hormones (ABA, ethylene) 24
and redox system that activates the genes responsible for heat shock proteins and alters
the membrane fluidity and ratio of saturated to unsaturated fatty acids (Joyce et al., 2003;
Suzuki and Mittler, 2006).
Another study described that, under heat stress, the plants transduce signal to
mitogen activated protein kinase (MAPK) and as a heat shock response the cytosolic Ca2+
concentration increases sharply (Larkindale and Knight, 2002; Kaur and Gupta, 2005).
Plant uses the Ca2+ influx, heat-shock activated MAPK (HAMK), calmodulin (CaM)
related genes and Ca-dependent protein kinases (CDPK) to alleviate heat stress (Sangwan
and Dhindsa, 2002; Liu et al., 2003). It has shown that cytosolic Ca2+ concentration raises
that regulate the plant responses to increase the activity of antioxidants and maintain
turgor pressure in guard cells (Wahid et al., 2007).
Sung et al. (2003) reported that as a heat shock response the plants use heat shock
proteins, dehydrins, chaperone, antioxidants enzymes, osmolytes and osmoprotectants in
their cytoplasm to protect the structures and functions of essential proteins and
macromolecules. Heat shock proteins ensure the three dimensional structure of cell
membrane proteins to maintain the cellular structures and functions against heat stress
(Wahid et al., 2007). Another study has shown the same results that barley seeds pre-
treated with glycine betaine improved the cell membrane stability, rate of photosynthesis;
shoot dry mass and leaf water potential as compared to control (Wahid and Shabbir,
2005).
2.4. Management of abiotic stresses
Tolerance to abiotic stresses by plants follows a complex mechanism, and plants
use a series of adaptive mechanisms to withstand it. For example, under saline soil
conditions plants modulate a number of physiological processes viz. stomatal regulation,
osmotic adjustment, maintenance of tissue water status, hormonal balance, ion
homeostasis and activation of the antioxidant defense system (Hichem et al., 2009; Kaya
et al., 2010; Jafar et al., 2012). Similarly, in response to drought stress plants produce
certain antioxidants (enzymatic and non-enzymatic) for protection against ROS (Gill and
Tuteja, 2010). Furthermore, plants maintains more negative water potential than
surrounding soil and accumulates compatible solutes viz. proline, sugars, polyols, glycine
betaine, mannitol and sorbitol that assist in drought tolerance though act as ROS
scavengers and chemical chaperones (Taiz and Zeiger, 2006). Tolerant plants manage the
abiotic stress conditions by using the strategies such as osmotic adjustment, ion exclusion
through roots, ionic compartmentalization, maintenance of tissue water status, nutrient 25
balance, higher synthesis/accumulation of osmolytes/osmoprotectants and higher
detoxification or scavenging ability (Athar and Ashraf, 2009). Scientist also suggests that
abiotic stresses can be managed through good cultural practices. Among these the
possible strategies/cultural practices are selection of abiotic stress tolerant varieties,
timely sowing to avoid heat stress at reproductive stage and seed priming are more
important ones.
2.4.1. Selection of stress tolerant varieties
Drought stress effects the crop growth and development; depending upon the
intensity of stress and yield potential. As high yielding varieties are more preferred under
mild drought stress, whereas; high drought tolerant varieties would be more beneficial
under severe drought stress (Panthuwan et al., 2005; Rizza et al., 2004). Zhao et al.
(2014) compared two rice varieties based on plant height, leaf relative water content, leaf
and root K+ and Na+ concentration, root length, root weight, sugars and proline contents in
leaf and root tissues under normal and salt stress conditions. It was observed that salt
tolerant variety performed better for all these traits except leaf and root Na+ concentration
which was accumulated more in salt sensitive variety. In another study relative water
content, chlorophyll fluorescence, leaf gas exchange characters and RNA-Sequencing
were used to evaluate the drought tolerant and susceptible sorghum varieties (Fracasso et
al., 2016). Under normal and drought stressed conditions, two barley varieties were
differentiated for their resistance or susceptibility by using traits viz. plant height and
biomass, number of spike bearing tillers, spikelets and grains per spike, grain yield and
grain protein content.
It was observed that resistant genotype gave better results for all above mentioned
traits as compared to susceptible genotypes. Furthermore, drought tolerant genotype
accumulated more sugars, leaf proline, leaf glycine betaine and carbohydrate contents
under stressed conditions compared with drought susceptible genotypes (Chmielewska et
al., 2016). Amanullah et al. (2011) compared two barley and six wheat varieties under
water deficit and normal conditions. Based on yield and related traits, wheat varieties
were recommended for cultivation in dryland areas as compared to barley cultivars. In
soybean, there exists a genotypic difference to drought tolerant and susceptible varieties.
Varieties with more leaf proline accumulation and better root traits are preferable to
cultivate under drought conditions (Mwenye et al., 2016).
Kumawat et al. (2017) compared ten lentil varieties for their salt
tolerance/sensitivity based on dry matter yield and stress tolerance indices and stress 26
susceptibility index. Varieties with higher economic yield coupled with lowered values of
stress tolerance indices were preferred for salt stressed conditions then other varieties.
Similarly, under water deficit conditions drought tolerant variety of wheat gave higher
productive tillers and grain yield than susceptible ones (Matsunaka et al., 1992; Yasin et
al., 1993). In another study four wheat cultivars were compared against drought stress at
vegetative and reproductive stages and cultivar with higher leaf relative water content and
water potential was recommended than other ones (Siddique et al., 2000). Moreover,
Dhanda et al. (2004) screened the 30 wheat varieties against drought stress and varieties
with higher seed vigor index, germination percentage, shoot and root length were
preferred for cultivation under water deficit conditions.
2.4.2. Seed priming in abiotic stress tolerance
Abiotic stresses can be managed in plants through conventional breeding,
molecular engineering of specific genes and their introduction into crop plants. However,
these approaches need more time and resources coupled with the complex process to
stress tolerance and genetic characters into environment interaction, it is very difficult to
understand the key molecular mechanisms associated with stress tolerance. However,
seed priming is the most viable approach and has the potential just to overcome abiotic
stresses (Farooq et al., 2009a).
Seed priming is a low cost, easier, and low risk practice and an alternate method
used to overcome abiotic stresses. It has been observed that seed priming improves the
germination and seedling growth in normal (Khan, 1992) as well as salt stressed
conditions (Basra et al., 2005). Pre-sowing seed treatments with water (hydropriming),
salts (osmopriming) and microbes (biopriming) stimulate the germination processes and
gene expression for osmolytes and antioxidants to protect the plants from oxidative
damage under abiotic stress conditions (Cantliffe, 2003; Afzal et al., 2006). Pre-sowing
seed treatments enhance the seed germination and stand establishment in stressed
environments (Farooq et al., 2009b). Janmohammadi et al. (2008) stated that
hydropriming improved the final emergence percentage, germination index and growth of
maize seedlings under salinity stress. Primed seeds took less time for germination and
gave good stand establishment (Harris et al., 2002). Seed priming stimulates mobilization
of inorganic solutes/essential metabolites to germinating seeds (Taiz and Zeiger, 2002).
27
Enhanced germination rate and uniform germination which are the consequences
of seed priming have been employed to overcome drought stress in crop plants (Farooq et
al., 2007, 2009b). Seed priming allows pre-germination metabolic activities to happen
within seeds upto the level limited to that instantly precedes radicle emergence. Seed
priming improves growth and yield of crop plants under normal and stressed conditions
as well. Higher grain yield of wheat was observed by seed priming with KCl under saline
and water deficit conditions (Ghana and Schillinger, 2003). Seed priming with 4% KCl
solution and saturated CaHPO4 solution improved final germination, crop stand
establishment and crop yield under drought stress (Harris et al., 2002). Similarly, seed
priming with arginine solution improved growth, grain and biological yield, harvest
index, and grain soluble sugars, amino acids and protein contents in wheat (Amir and
Qados, 2009).
Seed priming has been found to improve the germination and water use efficiency
of wheat under drought stress (Ajouri et al., 2004). It helps in improving the drought
resistance by its beneficial effects such as faster and uniform emergence, early flowering
and improved grain yield (Kaur et al., 2005). Osmopriming of wheat seeds improved the
grain yield in field and glass house environments (Eivazi, 2012). When seeds were
primed with organic/inorganic salts, plant growth regulators and compatible solutes then
seedlings’ growth and development was improved (Afzal et al., 2006; Pill and Savage,
2008). It has also been observed that seed priming caused an increase in the CAT and
SOD activities (Basra et al., 2004). Therefore, seed priming with inorganic or organic
substances may be used to improve germination and stand establishment under abiotic
stresses.
2.4.2.1. Osmopriming with calcium salt and abiotic stress tolerance
Calcium is a main component of plant signaling transport pathway. It stabilizes
the structure of cell membranes and proteins that are embedded in membranes. It
regulates a number of plant processes such as cell growth (cell division, elongation and
differentiation), photomorphogenesis, cell polarity, cytoplasmic streaming, plant defense
system and thigmotropism under normal as well as stressed conditions (Nayyar, 2003).
Under stress conditions Ca2+ acts as secondary messenger that stimulates the expression
of genes that were responsible for osmolytes production (White and Broadley, 2003).
Furthermore, it improves the plant growth by regulating the mitotic activities, cell
membrane stability and integrity, and structural strength of cell walls (Hepler, 2005).
Exogenously applied calcium through seed priming helps the plants in ameliorating the 28
damaging effects of salinity by declining the Na+ ion influx and enhancing the K+ ion
efflux through non-selective cation channels (Shabala et al., 2006; Rathod and Anand,
2016).
Seed priming with CaCl2 increases the accumulation of osmolytes in wheat plants
exposed to salt stress from stand establishment to maturity (Tabassum et al., 2017). For
instance, seed priming with CaCl2 improved germination and seedling establishment of
rice in greenhouse study (Ruan et al., 2002a, b). Moreover, seed priming with CaCl2
improved the protein contents under salt stress conditions as calcium protects the cell
membrane (White and Broadley, 2003; Mahboob et al., 2015). Likewise, more 1000-
grain weight for rice was obtained through seed priming with CaCl2 followed by KCl
(Farooq et al., 2006b). Calcium enhances the production and accumulation of compatible
solutes (proline, glycine betain, sugars and polyols) and helps in osmotic adjustment
(Girija et al., 2002). Exogenous application of Ca2+ alleviates the deleterious effects of
salt stress on crop plants, as it stimulates uptake of K+ than Na+ ion (Hasegawa et al.,
2000). Seed priming with 1.5% solution of CaCl2 improved the leaf area, leaf relative
water content, leaf water potential, leaf osmotic potential, number of grains per spike,
grain weight and grain yield in wheat under salt stress (Tabassum et al., 2017).
2.4.2.2. Biopriming with PGPBs and abiotic stress tolerance
Plants face numerous abiotic stresses under field conditions. When plants fail to
avoid or tolerate primary stresses (drought, salinity, heat and heavy metals stress) then
secondary stress (oxidative stress) occurs that leads to production of ROS. Although
ROS have some benefits at low concentrations as they act as signaling compounds under
stress conditions but at high concentrations they interact with cell membranes and
macromolecules such as lipids, proteins and DNA (Munne-Bosch and Penuelas, 2003;
Reddy et al., 2006). Reactive oxygen species impair the normal functions of cells through
oxidative damage. Plants produce compatible solutes (proline, glycinebetaine,
polyamines), certain antioxidants (enzymatic and non-enzymatic) and activate various
defense systems to scavenge and detoxify these ROS (Gill and Tuteja, 2010).
Plant growth promoting bacteria acts as an alternative to chemicals. These
microorganisms ensure accessibility of necessary nutrients to crop plants, improves
nutrient utilization efficiency, seed germination, root development and abiotic stress
tolerance of crop plants (Dobbelaere et al., 2003; Khalid et al., 2009; Mitter et al., 2013).
Proposed ways by which PGPBs enhance growth and nutrition of plants under normal
and stressed conditions are phytohormones production, biological nitrogen fixation, plant-29
microbe symbiotic associations, inhibition the ethylene production, along with improving
the availability of macronutrients like Fe, P and other microelements, and growth
improvement by volatile composites (Hardoim et al., 2008; Mitter et al., 2013).
Plant related bacteria may release osmolytes such as proline, trehalose, glycine
betaine, mannitol and sorbitol in response to the stress combined with other PGPB traits
may act symbiotically with other plant-made osmolytes that enhance the plant growth
under less than optimal growth conditions (Paul and Nair, 2008). Seed priming with
endophytic bacterial strains develops a more efficient root architecture that improves the
relative water contents of plants under water stress conditions (Fisher et al., 2000; Lucy
et al., 2011; Dodd et al., 2010). Stress stimulated ethylene production was decreased
through inoculant strains containing 1-aminocyclopropane-1-carboxylate (ACC)
deaminase activity resulting in more proliferated roots systems, which help the water
uptake from deeper soil layers (Dodd et al., 2010; Vardharajula et al., 2011). Seed
priming with enterobacter spp. strain FD17 have the potential to efficiently colonize the
plant rhizosphere and considerably improves the biomass production, leaf area, number of
leaves per plant and economic yield up to 39, 20, 14 and 42%, respectively. Similarly, in
maize plants it improved the time to flowering and photochemical efficiency of PSII
(Vance et al., 2011; Naveed et al., 2014a,b).
Plant growth promoting bacteria improves the growth of main as well as lateral
roots which enhances the water uptake in plants raised from microbial seed priming.
Additionally, biopriming helps in mediating water transport and partitioning through
symplastic and apoplastic pathways fetched into improved plant growth under abiotic
stress conditions. Plant growth promoting bacteria modulates the plant metabolism such
as; production of indole-acetic acid (IAA), activity of ACC deaminase, production and
accumulation of antioxidant compounds, and nitrogen fixation (Glick, 2005; Dimkpa et
al., 2009; Bashan and de-Bashan, 2010). Moreover, it enhances the accumulation and
production of compatible solutes which helps in osmotic adjustment (Dimkpa et al.,
2009). Plants treated with Azospirillum and Bacillus helps in upregulating the genes
expression for heat shock proteins (HSP17.8) under heat stress conditions (Lee and
Vierling, 2000). Similarly, barley plants treated with Azospirillum gave lowered activity
of CAT and POD under salt stress. It might be attributed to improved growth and
photosynthetic activity that lowered the production of ROS in treated plants as compared
to control (Omar et al., 2009).
30
Seed priming with PGPB can be used to improve the crop performance under
optimum and stressed conditions (Mahmood et al., 2016). Plant growth promoting
bacteria successfully colonize the seeds and plants when employed through seed priming.
Saber et al. (2012) used various bacterial species for seed biopriming including Bacillus
lentus, Azospirillum spp., P. putida, B. subtilis and Pseudomonas fluorescens. Biopriming
with these bacterial spp. improved the growth and yield traits of wheat. Moreover, the
wheat plants produced from bioprimed plants exhibited decreased need for N and P than
plants from untreated seeds. In barley, biopriming with consortium of Azospirillum
lipoferum and Azotobacter chroococcum improved the dry matter production, yield and
harvest index (Mirshekari et al., 2012). Similarly, Sharifi (2012) reported an increase in
CGR, dry matter production, heads per plant, number of grains and grain weight, yield
and seed oil content in safflower.
2.5. Conclusion
Late sowing and abiotic stresses not only limits the crop productivity but also
cause a serious threat to world food security. Late sowing as well as abiotic stresses
decreases crop yield and quality through alteration in various morphological,
physiological and biochemical processes taking place in plant body. Seed priming with
water and inorganic salts such as CaCl2 can be a useful approach and has the potential to
improve barley performance under late sown and abiotic stress conditions. Moreover,
microbes may also play important role in promoting the growth through enhancing seed
germination, total root biomass and nutrient availability under normal and stressful
conditions. Therefore, it might be a useful approach to prime seed with inorganic salts
and microbes to mitigate the effects of abiotic stresses and enhance abiotic stress
tolerance in plants.
31
CHAPTER 3
MATERIALS AND METHODS
Study was conducted during 2014-17 to investigate the influence of seed priming
in improving the performance of barley varieties under late sown and abiotic stress
conditions. A series of experiments were performed in the green house and field
conditions.
3.1. Experiment 1: Potential role of seed priming in improving the resistance against
drought in barley
3.1.1. Experimental site and design
A pot experiment was carried out in the greenhouse of Faculty of Agriculture,
University of Agriculture, Faisalabad during 2014-15 and 2015-16 to investigate potential
of seed priming in improving the resistance against drought stress in barley. The
experiment was carried out by using completely randomized design (CRD) in factorial
arrangement with four replications.
3.1.2. Experimental material
Seed of two barley varieties, Hiaider-93 and Frontier-87, used in this study was
obtained from Ayub Agriculture Research Institute, Faisalabad, Pakistan.
3.1.3. Experimental treatments
Seed of both barley cultivars was subjected to four seed priming treatments viz.
control (dry seed), hydroprimed, osmoprimed with 1.5% solution of CaCl2 and bioprimed
with Enterobacter sp. strain FD17. Seed was soaked for 12 h in aerated 5% (w/v) solution
of microbes and CaCl2 for biopriming and osmopriming, respectively. Seed was soaked in
water for hydropriming; keeping seed and solution ratio of 1:5 (w/v). Aquarium pump
was used providing aeration. The seed was washed with distilled water for 2-3 times after
removing from the respective solution and dried back to its original weight by enforced
air at 27oC ± 2, then stored in refrigerator at 5oC after putting in polythene bags until used.
The crop was sown as per treatments. After stand establishment drought stress viz. 80%
(well-watered), 60% (mild drought) and 40% (severe drought) water-holding capacity
were applied.
3.1.4. Crop husbandry
Two barley cultivars viz. Haider-93 and Frontier-87 were sown manually in the
soil filled earthen pots (45 cm × 30 cm) on November 03, 2014 and November 07, 2015.
32
The soil properties are given in Table 3.1. Fertilizer dose was calculated per weight basis
of soil from recommended dose of NPK. Urea (containing 46% N), diamonium phosphate
(DAP) (containing 46% P2O5 and 18% N), sulphate of potash (SOP) (containing 50%
K2O) were used as sources of fertilizers. All NPK was applied at sowing. Fifteen seeds
per pot were sown, after stand establishment six plants per pot were maintained. Crop was
harvested on April 05, 2015 and April 10, 2016 at maturity, manually threshed and yield
traits were recorded.
3.1.5. Imposition of drought stress
Field capacity of soil used in this experiment was determined by taking three soil
samples (each of 100 g) while filling pots. Samples were placed in oven at 105°C± 5 for
24 h. Afterwards, samples were weighed to determine total moisture content. Amount of
distilled water used in making paste was measured to calculate saturation percentage of
soil samples. Field capacity of soil was calculated according to following formula:
The weight of soil containing pots and moisture content was known at sowing
time; therefore, weight of filled pots having moisture contents equilent to 60, 80 and
100% water holding capacity were calculated and maintained representing as drought
treatment.
3.1.6. Procedures for recording data
Procedures for recording data for different traits during the period of experiment
are given as follows;
3.1.6.1. Stand establishment
The seedlings were counted daily after emergence to determine stand
establishment traits by using the method given in Handbook of Association of Official
Seed Analysts (1990). The data on following stand establishment traits were recorded;
i) Final emergence (%)
The seedlings emerged were counted from each replication on daily basis till
constant value. The emergence percentage of final count was computed as a ratio of the
seedlings emerged to the total seeds sown and expressed in percentage.
ii) Time taken to 50% emergence (days)
33
Time taken for completion of 50% emergence was computed by using formula
given by Coolbear et al. (1984) and revised by Farooq et al. (2005);
Where,
N = Number of emerged seedlings
ni, nj = Accumulative number of the emerged seedlings at each adjacent count at
time ti and tj, while, ni < N/2 < nj
iii) Mean emergence time (days)
The mean emergence time was computed by using the formula given by Ellis and
Robert (1981);
Where,
n = Seedlings emerged on day D
D = Days from initiation of the emergence
iv) Emergence index
Emergence index was determined using the formula of Association of Official
Seed Analyst (1990);
3.1.6.2. Morphological and allometric traits
i) Plant height (cm)
The plant height was measured from three selected plants from all replications.
Plant height was measured using a meter rod from soil surface to tip and averaged.
ii) Leaf area (cm2)
Leaves of one selected plant from all replications were detached and the leaf area
was determined with digital leaf area meter (JVC TK-5310) and averaged.
3.1.6.3. Proteomics
i) Total soluble proteins (mg g-1 FW)
The total soluble proteins content was ascertained from flag leaves at booting
stage as follows;
Total soluble proteins extraction
34
Fresh leaves (0.5 g) were ground by adding extraction buffer having pH 7.2 (1
mL) to extract the total soluble proteins followed by addition of 1 µM cocktail protease
inhibitor. The phosphate buffer saline (10 mM Na2HPO4, 2 mM KH2PO4, 1.37 mM NaCl,
2.7 mM KCl) was used with pH 7.2 adjusted by HCl and volume made upto 1 L. It was
followed by autoclaving (Sambrook and Russell, 2001). Centrifugation of ground leaf
material was carried out at 12000 x g upto 5 min. Then supernatant was poured in the
separate tubes.
Determination of total soluble proteins (mg g-1 FW)
The method of Bradford (1976) was followed to ascertain the total soluble
proteins. Standard curve was prepared by using bovine serum albumin at different
concentrations (10, 20, 30, 40 and 50 µg mL-1) by addition of dye (400 µL) and distilled
water. Spectrophotometer was used to read absorbance of samples and blank at 595 nm.
Total soluble proteins content was ascertained using standard curve.
3.1.6.4. Biochemical traits
i) Chlorophyll contents (mg g -1 FW)
Chlorophyll contents were determined by taking fresh flag leaves (0.5 g) sample
at booting stage. Samples were soaked overnight in of 80% acetone (5 ml). Absornaces
were taken with spectrophotometer. Concentrations of chlorophyll were determined by
following the formulae of Arnon (1949);
Chlorophyll ‘a’ (mg g-1 FW)
Chlorophyll ‘b’ (mg g-1 FW)
ii) Free leaf proline (µmol g-1 FW)
Fresh flag leaves samples were obtained at booting stage and free leaf proline
content was determined according to Bate et al. (1973). Homogenation of samples was
performed in 3% sulfosalcyclic acid (10 mL) followed by filteration. Filterate (1 mL) was
poured in ninhydrin solution (1 mL) (prepared by adding 1.25 g ninhydrin in 20 mL of
6M orthophosphoric acid and acetic acid) and glacial acetic acid (1 mL). Mixture was
incubated upto 1 h at 100°C and cooled in the ice bath. Afterwards, toluene (5 mL) was
added to mixture, vortexed upto 5 min and then removed from the aqueous phase.
35
Absorbance was recorded at 520 nm and toluene was used as blank. Concentration of
proline was calculated as follows;
iii) Leaf glycine betaine (µmol g-1 FW)
Fresh flag leaves samples were taken at booting stage and free leaf glycine betaine
was assayed following Grieve and Grattan (1983). Leaves samples (1 g) were ground in
distilled water (10 mL) and filtered. Afterwards, filtrate (1 mL) was added in 2M HCL (1
mL) and incubated upto 1 h at 4°C. Potassium tri iodide (0.1 mL) was added to the
mixture and incubated upto 1 h at 4°C. In cooled mixture, 1,2-di-dichloroethane (10 mL)
and chilled water (2 mL) were adde and vortexed upto 5 min and absorbance of organic
layer was read at 365 nm. Concentration of the glycine betaine was calculated against
standard curve.
iv) Malondialdehyde (µmol g-1 FW)
Flag leaves samples were taken at booting stage for measuring MDA content
according to Cakmak and Horst (1991). Homogention of leaves samples (1 g) was done
in 0.1% trichloroacetic acid (TCA) solution (3 mL). Centrifugation of the homogenate
was performed upto 15 min at 20000 × g. In supernatant (0.5 mL), 0.5% thiobarbituric
acid (3 mL) made in 20% TCA was poured. Mixiture was heated upto 30 min at 95°C in
water bath and then cooled. The samples were centrifuged upto 10 min at 10,000 × g.
Absorbance of supernatant was observed at 532 and 600 nm. Malondialdehyde content
was determined as follows;
Where,
A = Absorption coefficient valued 155 mmol-1 cm-1
v) Total soluble phenolics (µg g-1 FW)
Extraction method
For determining the total soluble phenolics, the flag leaves samples (0.5 g) were
taken at booting stage, soaked in 80% acetone (5 mL) overnight and filtered. The filtrate
was made upto 10 ml by adding acetone.
Bioassay
Total soluble phenolics content was assayed by using the Folin-Ciocalteu method
of Ainsworth and Gillespie (2007). A 20 µL of sample, calibration solution and blank
36
were taken, and water (1.58 mL) and Folin-Ciocalteu-reagent (100 µL) were added,
mixed and waited upto 30 sec. Then, Na2CO3 solution (300 µL) was poured and kept upto
2 hours at 25oC. Absorbance of the mixture was recorded at 760 nm. Total soluble
phenolics content was determined using the standard curve prepared by gallic acid (25-
250 ppm).
vi) Cell membrane stability (%)
Fresh flag leaves samples were taken at booting stage to determine the cell
membrane stability. Leaves samples were weighed (0.2 g) and equal sized five segments
made, washed and soaked in distilled water (20 mL) upto 12 h. Electrical conductivity of
the solution (EC1) was determined and solution heated in water bath upto 30 min and
cooled at room temperature. Conductivity of the solution was determined again (EC2).
Cell membrane stability was calculated following Blum and Ebercon (1981).
3.1.6.5. Water relation traits
Flag leaves samples were taken at booting stage to determine the plant water
relation attributes.
i) Leaf relative water content (%)
Leaf relative water content was determined following Barrs and Weatherly
(1962). Fresh weight (Wf) of leaves was determined. The samples were soaked in
distilled water upto 4 h period to record saturated weight (Ws). After recording Ws, the
leaves were oven dried at 70oC to detrmine the dry weight (Wd). Leaf relative water
content was calculated as follows;
ii) Leaf water potential (-MPa)
Water potential apparatus was usded to determine leaf water potential according
to Scholander et al. (1964). Compressed gas was applied on leaf sealed in pressure bomb
untill xylem sap appeared at cut surface of leaf. The reading was recorded as leaf water
potential. Sampling was done between 6:00 a.m. to 8:00 a.m. to avoid evaporation.
iii) Leaf osmotic potential (-MPa)
37
Same leaf, utilized for the determination of water potential, was frozen in freezer
at -20°C for one week, thawed and cell sap was extract by pressing leaf with rod. Osmotic
potential wa determined with a vapor pressure osmometer.
iv) Leaf pressure potential (MPa)
Leaf pressure potential was computed as difference between water potential and
osmotic potential.
3.1.6.6. Grain analysis
i) Zinc content (µg g-1 DW)
Concentration of zinc in barley grains was determined according to the method of
Estefan et al. (2013). The digestion was carried out by using the following method:
Digestion
Ground grains (1 g) and di-acid mixture (10 mL) (nitric acid and perchloric acid in
2:1 ratio) were added in digestion tubes. The digestion tubes were heated at 150°C upto 1
h and then at 235°C on block digester untill fumes disappeared and solution became
colorless. Tubes were cooled, few drops of distilled water were added. Volume of
solution was made upto 100 mL with distilled water and filtered. A blank was also
included in batch for digestion.
Zn+2 concentration determination
Standard curve was prepared by running series of standards of Zn (0.2, 0.4, 0.8,
1.0 and 1.2 ppm). The filterate was used to determine zinc concentration by using atomic
absorption spectrophotometer. The Zn concentration was computed as follows;
Where,
V = volume of digest (mL)
W = weight of plant sample (g)
ii) Manganese content (µg g-1 DW)
Method of Estefan et al. (2013) was used to determine the concentration of Mn in
grain samples. Digestion of grains samples was done similarly as for Zn determination.
Standard curves was prepared by running series of standards of Mn (0.2, 0.4, 0.8, 1.0 and
1.2 ppm). TheMn concentration in filterate was determine by using atomic absorption
spectrophotometer. The Mn concentration was determined as follows.
38
Where, V = volume of digest (mL)
W = weight of plant sample (g)
iii) Boron content (µg g-1 DW)
Grain B contents were determined by dry ashing (Chapman and Pratt 1961). Dry
ashing of ground grains was done at 550°C for 6 h in furnace. Then extraction form ashed
samples was done with0.36 N H2SO4 (10 mL), filtered and volume was made upto 50 mL
with distilled water. Buffer solution (4 mL) (1.5% EDTA, 12.5% Acetic acid, 25%
ammonium acetate) and solution (4 mL) containg containing 1% ascorbic acid and 0.45%
azomethine-H was added to filterte (2 mL). Color was developed for 30 min. Standard
curve of B (0.5-3.0 ppm) was prepared, absorbance was read at 420 nm with
spectrophotometer and B concentration was determined as follows (Bingham 1982; Ho et
al., 1986; Malekani and Cresser 1998);
Where,
V = volume of digest (mL)
W = weight of plant sample (g)
3.1.6.7. Yield and related traits
Parameters on the yield and related traits were recorded by using following
procedures;
i) Number of tillers per pot
At maturity, number of tillers was counted from selected three plants from each
pot.
ii) Number of productive tillers per pot
At maturity, the number of tillers having spike was counted form selected three
plants from each pot.
iii) Spike length (cm)
From each pot, the spikes were collected from selected three plants and spike
length was measured by using a measuring scale and averaged.
iv) Number of spikelet’s per spike
From each pot, the spikes were collected from selected three plants and the
number of spikelet’s on all spikes was counted and averaged.
39
v) Number of grains per spike
At maturity, spikes were collected from selected three plants from each pot.
Grains per spike were counted after threshing spikes manually and then average was
calculated.
vi) 100-grain weight (g)
From each replication grains were collected after threshing the spikes of selected
three plants and 100-grains were counted manually. The weight of 100 grains was
recorded in grams using an electronic balance.
vii) Grain yield (g pot-1)
The spikes of selected three plants from each pot were threshed manually. Grain
weight from each replication was noted by an electric balance in grams.
viii) Biological yield (g pot-1)
The selected three plants were harvested from each pot and total biomass was
noted from all replications using an electric balance in grams.
ix) Harvest index (%)
Harvest index was computed as follows;
3.2. Experiment 2: Potential role of seed priming in improving the salt resistance in
barley
3.2.1. Experimental site and design
A pot experiment was conducted in greenhouse of Faculty of Agriculture,
University of Agriculture, Faisalabad during 2014-15 and 2015-16 to investigate the
potential of seed priming in improving the resistance against salt stress in barley. The
experiment was carried out by using completely randomized design (CRD) in factorial
arrangement with four replications.
3.2.2. Experimental material
Experimental material was same as mentioned in section 3.1.2.
3.2.3. Experimental details
Seed priming treatments and barley cultivars were remained same as in 1st
experiment. After uniformity of stand establishment salinity viz. 50 mM NaCl (control),
100 mM NaCl (mild salt stress) and 150 mM NaCl (severe salt stress) was applied. 40
3.2.4. Crop husbandry
In both years, crop was sown manually in soil filled earthen pots (45 × 30 cm) on
November 06, 2014 and November 11, 2015. Soil properties are given in Table 3.1.
Fertilizer dose was calculated per weight basis of soil from recommended dose of NPK.
Urea (46% N), DAP (46% P2O5 and 18% N), SOP (50% K2O) were used as fertilizer
sources. Whole quantity of NPK was applied as basal dose. Fifteen seeds were sown in
each pot and after stand establishment six plants per pot were maintained. Crop was
harvested on April 08, 2015 and April 13, 2016 at maturity and was threshed manually to
record yield traits.
3.2.5. Imposition of salinity stress
The original EC of the soil was 1.01 dS m-1. The 5 dS m-1 was used as control for
comparison because of high salt tolearance ability of barley.
Procedure of ECe measurement
To record ECe, 250 g of dry soil sample was taken from the soil that was used for
pots. Soil paste was made by adding distilled water in it and placed for 24 hours. After 24
hours, the water from paste was extracted with the help of extractor. The ECe of water
was measured with ECe meter.
Saturation percentage (%)
To record saturation percentage, 250 g of soil sample was collected in petri dish
and distilled water was added to make pasty mass. After pasty mass, 10 g of soil saturated
paste was taken in china dish and put in oven for 24 hours to get its constant weight. The
saturation percentage was calculated using following formula;
Salinity development
After weighing the soil in one pot, the salinity level was developed artificially by
adding the NaCl salt in the soil. The salt was added according to the weight of the soil.
The soil weight and salt quantity was measured. The NaCl was added in pots, thoroughly
mixed in pots and salinity levels were developed at 50, 100 and 150 mM. To develop
salinity levels, following procedure was adopted. The original ECe of the soil was used
for this study. Whole procedure is written below in mathematical form.
Saturation percentage of soil = 27%
5 dS m-1 = 50 mM41
Original ECe = 1.67 dS m-1
Required ECe = 5 dS m-1
Difference = 3.33 dS m-1
TSS = EC × 10 = 3.33 × 10 = 33.3
ECe = TSS × Eq. wt. × Saturation percentage/100
= 33.3×58.5 × 27.00/100 = 525.97 mg salt/kg of soil
= 5259.7 mg salt/10 kg of soil
= 5.260 g salt/10 kg of soil
= 13.379 g of NaCl / per pot
To develop 5 dS m-1, 13.379 g of NaCl was applied in each pot and soil was well
mixed to develop salinity. Same procedure was used to develop 10 dS m-1 and 15 dS m-1
salinity levels in respective pots.
3.2.6. Procedures for recording data
Procedures for recording the data on various traits during course of
experimentation are given as follows;
3.2.6.1. Stand establishment
Same as described in section 3.1.6.1.
3.2.6.2. Morphological and allometric traits
Same as described in section 3.1.6.2.
3.2.6.3. Mineral analysis
Flag leaves samples were taken at booting stage for determining the Na and K
ions.
Digestion
Digestion of ground dry leaves samples was carried out as described for Zn
determination.
Sodium concentration in plants
Sodium content in digested material was determined by using the flame
photometer according to Estefan et al. (2013). Standardization of instrument was done
with Na standard solutions (2, 4, 6, 8, 10, 15 mg L -1). Sodium concentration was
determined using the standard curve.
Potassium estimation
42
Potassium content was assayed with flame photometer according to Estefan et al.
(2013). Concentration of element was determined by using standard curve prepared by K
standard solutions (2, 4, 6, 8, 10, 15 mg L-1);
3.2.6.4. Proteomics
Same as described in section 3.1.6.3.
3.2.6.5. Biochemical traits
Fresh flag leaves samples were taken from each replication at booting stage and
biochemical attributes were recorded following procedure as described in section 3.1.6.4.
3.2.6.6. Water relation traits
Flag leaves samples were taken at booting stage and data regarding leaf water
relation traits were recorded as described in section 3.1.6.5.
3.2.6.7. Grain analysis
Grain B, Mn and Zn contents were determined according to section 3.1.6.6.
3.2.6.8. Yield and related traits
Yield and related traits were recorded by using the procedures given in section
3.1.6.7.
3.3. Experiment 3: Potential role of seed priming in improving the resistance against
osmotic and salt stresses in barley
3.3.1. Experimental site and design
To ascertain potential of seed priming in improving resistance against osmotic and
salt stresses in barley, a hydroponics experiment was carried out in green house of the
Faculty of Agriculture, University of Agriculture, Faisalabad, during 2016. The
experiment was conducted by using completely randomized design (CRD) in factorial
arrangement with four replications.
3.3.2. Experimental material
Experimental material was same as mentioned in section 3.1.2.
3.3.3. Crop husbandry and experimental details
Seed priming treatments and barley cultivars were remained same as in 1st
experiment. The untreated and primed seeds of barley varieties were sown in sand filled
polythene bags on November 10, 2015. Afterwards, fifteen days older seedlings were
transplanted in hydroponic solutions and grown in plastic tubs (length × width × height =
45 × 45 × 25 cm3) containing 1/2 strength Hoagland’s nutrient solution. Then, three stress
levels viz. control (no stress), osmotic stress (-0.8 MPa) by using PEG-8000 and ionic 43
stress (-0.8 MPa) by using NaCl were applied. The nutrient solution used for hydroponics
was a modified Hoagland's solution recipe (Hoagland and Snyder, 1993) and contained 5
mM NH4NO3, 0.5 mM KH2PO4, 3.5 mM K2SO4, 0.5 mM MgSO4.7H2O, 1.5 mM
Ca(NO3)2.4H2O, 25 μM H3BO3, 50 μM Fe-EDTA, 2 μM MnSO4.4H2O, 0.5 μM
H2MoO4·2H2O, 2 μM ZnSO4.7H2O, 0.5 μM CuSO4.5H2O dissolved in water. The nutrient
solution was refreshed after every five days and was aerated by aquarium pumps. An
individual plant was considered as a single replicate and plants were harvested thirty days
after transplanting.
3.3.4. Imposition of osmotic and ionic stress in hydroponics
Ionic stress was maintained through NaCl according to the method of Sosa et al.
(2005). Osmotic stress in hydroponics was maintained by using polyethylene glycol with
8000 molecular weight (PEG-8000) according to the following formula of Michel (1983):
Where, C=PEG concentration
T=Temperature
OP= Osmotic potential
After mixing the required quantity of NaCl and PEG-8000 in water the osmotic
potential of solutions were checked in a vapour pressure osmometer 1kg calibrated in mili
osmol (Osmette, Japan), and was added in the hydroponics solution of the respective
treatment.
3.3.5. Procedures for recording data
Following observations were recorded during the course of investigation;
3.3.5.1. Seedling vigor
i) Shoot length of seedling (cm)
At the end of experiment, the shoot length of all seedlings was measured using
measuring scale and expressed in cm. Then average shoot length was calculated.
ii) Root length of seedling (cm)
At the end of experiment, the root length of all seedlings was measured using
measuring scale and expressed in cm. Then average root length was calculated.
iii) Shoot fresh weight (mg)
Shoot fresh weight of all seedlings was weighed with electric weighing balance
after detaching from roots, averaged and expressed in mg.
iv) Root fresh weight (mg)
44
Detached roots of all seedlings were weighed with electric weighing balance,
averaged and expressed in mg.
v) Shoot dry weight (mg)
Shoots of all seedlings were dried in oven at 70 o C, averaged and expressed in
mg.
vi) Root dry weight (mg)
Detached roots of all seedlings were dried in oven at 70 o C, averaged and
expressed in mg.
3.3.5.2. Proteomics
A harvest leaf samples were taken and total soluble proteins were determined by
the same procedure as described in section 3.1.6.3.
3.3.5.3. Biochemical traits
Fresh leaf samples were taken from each replication at harvest and biochemical
attributes were recorded following procedure as described in section 3.1.6.4.
3.3.5.4. Mineral analysis
Fresh leaf samples were taken from each replication at harvest, and Na+
concentration was determined according to the section 3.2.6.3.
3.4. Experiment 4: Potential role of seed priming in improving the resistance against
cadmium stress in barley
3.4.1. Experimental site and design
To investigate the potential of seed priming in improving resistance against Cd
stress in barley, a hydroponics experiment was carried out in greenhouse of Faculty of
Agriculture, University of Agriculture Faisalabad, during 2016. The experiment was
conducted by using the completely randomized design (CRD) in factorial arrangement
with four replications.
3.4.2. Experimental material
Experimental material was same as mentioned in section 3.1.2.
3.4.3. Crop husbandry and experimental details
Seed priming treatments and barley cultivars were remained same as in 1st
experiment. The untreated and primed seeds of barley varieties were sown in sand filled
polythene bags on November 15, 2015. Afterwards, fifteen days older seedlings were
transplanted in hydroponic solutions and grown in plastic tubs (length × width × height =
45 × 45 × 25 cm3) containing half strength Hoagland’s nutrient solution. Then, three Cd
stress levels viz. control (no stress), moderate stress (8 mg Cd L-1) and severe stress (12 45
mg Cd L-1) were applied. The nutrient solution used for hydroponics was a modified
Hoagland's solution recipe (Hoagland and Snyder, 1993) and contained 5 mM NH4NO3,
0.5 mM KH2PO4, 0.5 mM MgSO4.7H2O, 3.5 mM K2SO4, 1.5 mM Ca(NO3)2.4H2O, 25 μM
H3BO3, 50 μM Fe-EDTA, 2 μM MnSO4.4H2O, 2 μM ZnSO4.7H2O, 0.5 μM
H2MoO4·2H2O, 0.5 μM CuSO4.5H2O dissolved in water. The nutrient solution was
refreshed after every five days and was aerated by aquarium pumps. An individual plant
was considered as a single replicate and plants were harvested thirty days after
transplanting.
3.4.4. Procedures for recording data
Following observations were recorded during the period of experimentation;
3.4.4.1. Seedling vigor
Seed vigor was recorded following the procedure given in section 3.3.5.1.
3.4.4.2. Proteomics
At harvest leaf samples were taken and total soluble proteins were determined by
the same procedure as described in section 3.1.6.3.
3.4.4.3. Biochemical traits
Fresh leaf samples were taken from each replication at harvest and biochemical
attributes were recorded following procedure as described in section 3.1.6.4.
3.4.4.4. Mineral analysis
i) Tissue cadmium content (μg g−1 DW)
At harvest the leaf samples were collected and concentration of cadmium contents
was determined by following the procedure of Meuwly and Rauser (1992).
Digestion
Digestion of ground dry leaves samples was carried out as described for Zn
determination.
Tissue cadmium content estimation
Cadmium content was determined by atomic absorption spectrophotometer. The
Cd concentration was calculated as follows;
Where, V = volume of digest (mL)
W = weight of plant sample (g)
46
3.5. Experiment 5: Potential role of seed priming in improving the resistance against
terminal heat stress in barley
3.5.1. Experimental site and design
To evaluate potential of seed priming in improving resistance against terminal
heat stress in barley, a pot experiment was carried out in greenhouse of Texas A&M,
Agrilife Research Center, Beaumont, Texas, USA which is the principal research and
crop production site of Texas A&M University, USA. The experiment was conducted
during 2017. The experiment was laid out in completely randomized design (CRD) in
factorial arrangement with six replications. Soil physico-chemical properties are given in
Table 3.2.
3.5.2. Experimental material
Seed of USA barley cultivar Solum used in this study was obtained from School
of Plant Sciences, The University of Arizona, USA.
3.5.3. Experimental treatments
Seed priming treatments were same as in 1st experiment except biopriming which
was not included in this experiment. The seeds were sown as per treatments. Mean
day/night temperatures in the greenhouse were observed by using standalone
sensor/loggers (HOBOs, Onset Computer Corporation, Bourne, Massachusetts, USA) and
maintained at desired level. At reproductive stage two levels of heat stress viz. control
(25/18°C day/night) and heat stress (35/25°C day/night) were applied. The heats stress
was applied by using the continuously controlled infrared heaters (1100 W, Chromalox,
Ogden, UT, USA).
3.5.4. Crop husbandry
Seeds of barley cultivar Solum were manually sown in soil filled plastic pots (25
cm × 15 cm) on January 21, 2017. Fertilizer dose was calculated per weight basis of soil
from recommended dose of NPK. Urea (46% N), DAP (46% P2O5 and 18% N), SOP
(50% K2O) were used as fertilizer sources. Whole of the NPK was applied at sowing as
basal dose. Six seeds per pot were sown, after stand establishment four plants per pot
were maintained. Crop was harvested on June 03, 2017 at maturity and was threshed
manually to record yield traits.
3.5.5. Procedures for recording data
47
Procedures for recording data on various traits during period of experimentation
are as follows;
3.5.5.1. Stand establishment
Stand establishment was recorded following the procedures as described in section
3.1.6.1.
3.5.5.2. Morphological traits
Plant height and number of productive tillers per plant were recorded as
mentioned in section 3.1.6.2.
3.5.6.3. Leaf chlorophyll contents
Leaf chlrophyll contents were determined according to the section 3.1.6.4
3.5.5.4. Leaf gas exchange characteristics
Gas-exchange traits like net photosynthesis, stomatal conductance, intercellular
CO2 concentration and transpiration were recorded by using a LI-6400 portable
photosynthesis system (LI-COR Inc., Lincoln, Nebraska, USA), at 7 and 14 days after
heat stress treatment (DAT). During measurements, incident photon flux density was
1500 µmol (photon) m-2 s-1, the leaf temperature 25oC and ambient CO2 concentration 400
µmol mol-1. The measurements were made on penultimate leaf, under bright sunlight
between 10:00 am and 11:00 am. Stomatal limitation (Ls) was determined by using the
formula; (Ls = 1-Ci/Ca). Carboxylation use efficiency (CUE) was determined as ratio
between photosynthesis to intercellular CO2 concentration.
3.5.5.5. Leaf chlorophyll fluorescence attributes
Chlorophyll a fluorescence parameters, the maximum quantum efficiency of PSII
(Fv/Fm), quantum yield of PSII (QY) and electron transport rate (ETR) were evaluated by
quantifying the fluorescence with a pulse modulated fluorometer (OS5p, Opti-Sciences,
Hudson, NH, USA). Minimal fluorescence (Fo), maximal fluorescence (Fm) and the Fv/Fm
were quantified in dark adapted leaves for 30 min. For QY and ETR, the plants were
under a steady state of photosynthesis (the plants were exposed to ambient sunlight for
more than 5 h), which is a prerequisite for the measurement of QY and ETR. The PAR
clip (OS5p PAR Clip, Opti-Sciences, Hudson, NH, USA) provided PAR measurements
when QY and ETR was measured. The range of PAR was 600-700 μmol m -2 s-1 when QY
and ETR was measured.
3.5.5.6. Leaf estimated oxidative stress
Cell membrane stability and MDA content was determined by using the method as
described in section 3.1.6.4.48
3.5.5.7. Total phenolics content (mg g-1 FW)
Total phenolics content was determined by using the method as described in
section 3.1.6.4.
3.5.6.8. Yield and related traits
Data on yield and related traits were noted by using procedures as described in
section 3.1.6.7.
3.6. Experiment 6: Influence of seed priming on the productivity of late sown barley
3.6.1. Experimental site and design
The experiment was conducted in the Agronomic Research Area, University of
Agriculture, Faisalabad, Pakistan during 2014-15 and 2015-16. The experiment was laid
out in randomized complete block design (RCBD) with split-split plot arrangement
having four replications with net plot size of 6 m × 2.7 m. Soil properties are given in
table 3.1.
3.6.2. Experimental material
Same as described in section 3.1.2.
3.6.3. Seedbed preparation
A soaking irrigation was applied a week before barley sowing to keep the
experimental land soft and moist. Seed bed was prepared by cultivating field twice
followed by planking.
3.6.4. Experimental details and crop husbandry
Seed priming treatments and barley varieties were remained same as in 1st
experiment. The crop was sown at two sowing dates viz. November 30 and December 30
during both 2014 and 2015. Soil properties are given in Table 3.1. Fertilizer dose (NPK
@ 50-35-25 kg ha-1) was applied using urea (46% N), DAP (46% P2O5 and 18% N), SOP
(50% K2O) as fertilizer sources. Whole of the NPK was applied as basal dose. Sowing
was done through hand drill and seed rate was 75 kg ha -1, Weeds were controlled
manually throughout the growing season in both years. Crop was harvested on April 01,
2015 and March 25, 2016 for November 31 sowing date, and April 22, 2015 and April 20,
2016 for December 31 sown crop at maturity and was threshed manually to record yield
traits.
3.6.5. Irrigation
49
Irrigation was applied at tillering, booting, anthesis and grain formation stages. In
all 4 irrigations were applied besides soaking irringation.
3.6.6. Procedures for recording data
Procedures for recording the data on various traits during the period of experiment
are given as follows;
3.6.6.1. Stand establishment
Stand establishment was recorded following the procedures as described in section
3.1.6.1.
3.6.6.2. Allometric, phenological and morphological traits
i) Plant height (cm)
The plant height was recorded by randomly selecting and tagging five plants from
each replication. Plant height was measured from soil surface upto tip by using a meter
rod and averaged.
ii) Leaf area index
The leaf area index was computed according to Watson (1952);
iii) Total dry matter (g m-2)
Total dry matter was determined by weighing the oven dried plants take from m -2.
The TDM production was expressed in g m-2.
iv) Crop growth rate (g m-2 d-1)
Crop growth rate was calculated according to Hunt (1978).
Where, W1 and W2 are TDMs at times t1 and t2, respectively
v) Grain filling rate (g spike-1 d-1)
For determination of garain filling rate, five spikes were selected randomly from
each plot with an interval of seven days. The samples were dried in an oven at 70 oC till
constant weigth, grains were manually threshed, weighed with an electric balance and the
grain filling rate was computed by using following formula;
Where, W1 and W2 are dried weights of selected spikes at times t1 and t2, respectively
50
vi) Grain filling duration (days)
Grain filling duration was recorded as time from anthesis to maturity.
3.6.6.3. Yield and related traits
The yield and related traits were recorded as follows;
i) Number of productive tillers m-2
Number of productive tillers was counted from the area of one m2 at final harvest.
ii) Spike length (cm)
The spike length of five selected spikes from each plot was measured from the
base of rachis to tip of spike excluding awns and averaged.
iii) Number of spikelet’s per spike
From each replication, five spikes were taken randomly and number of spikelet’s
in each spike was counted and averaged.
iv) Number of grains per spike
At maturity, five spikes were randomly selected from each replication. Number of
grains per spike was counted after threshing spikes manually and averaged.
v) 1000-grain weight (g)
The 1000-grain weigth was determined by counting and weighing the 1000 grains
on an electric balance from each replication and average was calculated.
vi) Grain yield (t ha-1)
Plants were threshed manually. Grain weight from each replication was recorded
by an electric balance in kg and later converted into t ha-1.
vii) Biological yield (t ha-1)
Plants were harvested and total biomass of was recorded from each replication
using an electric balance in kg and later converted into t ha-1.
viii) Harvest index (%)
Harvest index was calculated as follows;
3.6.6.4. Biochemical traits
i) Chlorophyll contents (mg g -1 FW)
Chlorophyll a and b contents were determined according to section 3.1.6.4.
3.6.6.5. Grain proximate analysis
i) Grain protein content (%)
For grain crude protein, grains were analyzed using near infrared (NIR)
51
technology (Omega Analyzer G™, Bruins Instruments, Germany). The analysis by this
method is non-destructive, and don’t require reagents or sample preparation (Moroi et al.,
2011). For protein, the barley grain samples (500 g per sample) were collected from each
replication. The weighed samples were inserted into an NIR Omega G Analyzer and
reflectance values obtained from samples were noted.
ii) Grain starch content (%)
Starch was analyzed by using the same method for grain protein content.
3.7. Economic Analysis
Economic analysis was carried out by following procedure of CIMMYT (1988).
The fixed cost of production of barley was computed for the factors which were kept
fixed viz. seed bed preparation, sowing, fertilization, irrigation, weed management etc.
The variable cost incurring on different treatments of seed priming was calculated
separately. The gross income for each treatment was computed based on grain yield
barley on per hectare basis according to prevailing market value. For calculation of net
field benefits total variable cost was subtracted from total benefits of each treatment. The
costs for inputs and output, gross income and benefits were converted into Rs. ha-1. The
BCR was computed according to CIMMYT (1988);
For calculation of net field benefits the variable cost was subtracted from gross
income. Marginal rate of return was computed according to CIMMYT (1988);
3.8. Meteorological data
Meteorological data during study periods are presented in table 3.3.
3.9. Statistical analysis
Data collected were analyzed statistically by employing the Fisher’s analysis of
variance (ANOVA) technique (Steel et al., 1997) with Statistix 8.1 (Analytical software,
Statistix; Tallahassee, FL, USA, 1985-2003) and the least significance difference (LSD)
test was used to compre the treatments’ means at 5% probability level.
52
Table 3.1: Properties of experimental soil (Experiments 1, 2 and 6)
Year 2014-15 2015-16
Characteristics Unit Value Value
Texture Sandy loam
pH - 8.0 7.9
EC dS m-1 1.07 1.11
Exchangeable Na mmolc L-1 9.7 9.4
Total soluble salts (TSS) mmolc L-1 18.2 18.0
Sodium absorption ratio
(SAR)(mmolc L-1)1/2 6.05
6.05
Chloride ion mmolc L-1 9.34 10.0
HCO3 mmolc L-1 6.48 6.69
Ca + Mg mmolc L-1 7.36 7.70
Available nitrogen % 0.06 0.057
Available phosphorus ppm 6.90 6.57
Available potassium ppm 176 180
Organic matter % 0.97 0.93
53
Table 3.2: Properties of experimental soil (Experiment 5)
Characteristics Unit Value
Texture clay loam -
pH - 6.8
EC dS m-1 1.00
Sodium (Na) ppm 171
Sodium Absorption Ratio (SAR) ppm 2.03
CaCO3 % 5
Calcium (Ca) ppm 3083
Magnesium (Mg) ppm 354
Available nitrogen ppm 4.2
Available phosphorus ppm 19.0
Available potassium ppm 121.0
Organic matter % 2.70
54
Table 3.3: Weather data during the growing seasons of barley at experimental site
Month Total rainfall
(mm)
Relative humidity
(%)Temperature (°C)
Sunshine (h)Monthly
maximum
Monthly
minimum
Daily mean
2014-15 2015-16 2014-15 2015-16 2014-15 2015-16 2014-15 2015-16 2014-15 2015-16 2014-15 2015-16
Nov. 10 9 62 62 26 27 12 12 19 20 8 7
Dec. 0 0 75 63 18 22 6 7 12 15 5 7
Jan. 12 13 75 74 17 18 7 8 12 13 5 1
Feb. 21 8 66 58 22 23 11 9 16 16 6 9
Mar. 68 67 64 60 24 27 14 16 19 21 5 7
Apr. 33 6 33 34 21 34 27 20 27 27 9 8
Source: Agro-meteorology Cell, UAF
55
CHAPTER 4
RESULTS AND DISCUSSION
4.1. Influence of seed priming in improving the resistance against drought in barley
4.1.1. Stand establishment
4.1.1.1. Final emergence percentage
Seed priming significantly affected final emergence percentage; the barley
varieties did not differ significantly for final emergence percentage, during both growing
seasons. The interactive effect of varieties and seed priming was non-significant, during
both years (Table 4.1). Seed priming improved final emergence percentage and maximum
improvement was caused by osmopriming followed by biopriming, as compared to
unprimed control (Table 4.2).
4.1.1.2. Time taken to 50% emergence
Time taken to 50% emergence was significantly affected by seed priming; while,
barley varieties did not differ significantly for time taken to 50% emergence, during both
growing seasons. The interaction between varieties and seed priming was non-significant
for time taken to 50% emergence, during both years (Table 4.1). Time taken to 50%
emergence was decreased as compared to unprimed control, during both years. Minimum
time taken to 50% emergence was elapsed by osmopriming followed by biopriming
(Table 4.3).
4.1.1.3. Mean emergence time
Seed priming significantly affected mean emergence time, during both years. The
barley varieties did not differ significantly for mean emergence time, during both growing
seasons. The interaction between varieties and seed priming was non-significant for mean
emergence time, during both seasons (Table 4.4). The mean emergence time was reduced
by seed priming treatments and least mean emergence time was recorded by osmopriming
(Table 4.5).
4.1.1.4. Emergence index
Seed priming significantly affected emergence index, during both growing
seasons. The barley varieties did not differ significantly for emergence index. Similarly,
interaction between varieties and seed priming was non-significant for emergence index,
during both years (Table 4.4). The emergence index was improved by seed priming
56
treatments, as compared to unprimed control. Maximum improvement was caused by
osmopriming
Table 4.1: Analysis of variance for the influence of seed priming on final emergence percentage and time taken to 50% emergence of barley SOV df Mean sum of square
Final emergence percentage Time taken to 50% emergence
2014-15 2015-16 2014-15 2015-16Varieties (V) 1 46.315ns 29.637ns 0.022ns 0.010ns
Priming (T) 3 140.062** 325.904** 0.458* 0.636*
V×T 3 16.656ns 9.879ns 0.121ns 0.018ns
Error 16 25.919 35.184 0.101 0.146Total 23
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.2: Influence of seed priming on final emergence (%) of barleyTreatments 2014-15 2015-16
H-93 F-87 Mean H-93 F-87 MeanControl 86.67 82.22 84.45 B 82.22 77.78 80.00 BHP 95.56 88.89 92.22 A 88.89 88.89 88.89 AOP 95.55 95.55 95.55 A 97.78 93.33 95.56 ABP 93.33 93.33 93.33 A 95.56 95.55 95.56 AMean 92.78 90.00 91.11 88.89
Seed priming LSD≤0.05 = 6.2310 (2014-15) and 7.2599 (2015-16)
Table 4.3: Influence of seed priming on time taken to 50% emergence (days) of barleyTreatments 2014-15 2015-16
H-93 F-87 Mean H-93 F-87 MeanControl 4.25 4.22 4.24 A 4.97 4.95 4.96 AHP 3.75 3.98 3.87 AB 4.38 4.29 4.34 BOP 3.63 3.64 3.64 B 4.31 4.15 4.23 BBP 3.89 3.44 3.67 B 4.37 4.47 4.42 BMean 3.88 3.82 4.51 4.47
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Seed priming LSD≤0.05 = 0.3889 (2014-15) and 0.4674 (2015-16)
Table 4.4: Analysis of variance for the influence of seed priming on mean emergence time and emergence index of barley SOV df Mean sum of square
Mean emergence time Emergence index2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 0.003ns 0.040ns 0.111ns 0.020ns
Priming (T) 3 0.274** 0.197* 0.591** 0.690**
V×T 3 0.019ns 0.007ns 0.052ns 0.023ns
Error 16 0.049 0.051 0.080 0.058Total 23
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
57
Table 4.5: Influence of seed priming on mean emergence time (days) of barleyTreatments 2014-15 2015-16
H-93 F-87 Mean H-93 F-87 MeanControl 4.69 4.70 4.70 A 5.17 5.11 5.14 AHP 4.45 4.58 4.52 AB 4.88 4.85 4.87 ABOP 4.14 4.23 4.19 C 4.74 4.69 4.72 BBP 4.46 4.33 4.40 BC 5.10 4.92 5.01 AMean 4.44 4.46 4.97 4.89
Seed priming LSD≤0.05 = 0.2720 (2014-15) and 0.2769 (2015-16)
Table 4.6: Influence of seed priming on emergence index of barleyTreatments 2014-15 2015-16
H-93 F-87 Mean H-93 F-87 MeanControl 3.01 2.78 2.90 B 2.66 2.50 2.58 CHP 3.49 3.15 3.32 A 3.00 3.04 3.02 BOP 3.67 3.62 3.65 A 3.45 3.29 3.37 ABP 3.38 3.46 3.42 A 3.17 3.23 3.20 ABMean 3.39 3.25 3.07 3.02
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Seed priming LSD≤0.05 = 0.3456 (2014-15) and 0.2940 (2015-16)
58
followed by biopriming (Table 4.6).
4.1.2. Discussion
Seed priming improved the emergence of barley by enhancing the emergence
percentage and decreasing the time for emergence. This may be due to improved
carbohydrates metabolism in germinating seeds by seed priming due to which activity of
hydrolytic enzymes is enhanced and food reserve becomes available for embryo (Farooq
et al. 2009b). It has been observed that seed priming invokes de novo synthesis of α-
amylase enzyme (Lee and Kim, 2000). Moreover, seed priming enhances activities of the
α-amylase, β-amylase, root system dehydrogenase and catalase enzymes under normal
and stressed conditions which leads to improved germination (He et al., 2002). In present
study, osmopriming was most effective in improving emergence which may be due to
Ca2+ used in osmopriming that is involved in regulating the cell wall structure, and cell
membrane integrity and permeability (Hepler, 2005). The improved cell membrane
stability by osmopriming results in decreased leakage and well maintained cell membrane
resulting in better and early germination (Posmyk et al., 2001). Ruan et al. (2002a, b)
reported improved energy of germination and seedling vigour index with concomitant
decrease in mean germination time by osmopriming with CaCl2 in rice. In present study,
improved emergence by biopriming may be due to endophytic bacteria which improves
water absorption in germinating seeds, and produces extracellular enzymes such as
amylase and protease that promote the degradation of proteins, sucrose and lipids leading
to enhanced and earlier germination (Zhu et al., 2017).
4.1.3. Agronomic attributes
4.1.3.1. Plant height
Drought stress and seed priming treatments significantly affected plant height;
barley varieties also differed significantly for plant height, during both growing seasons.
The interaction between varieties and drought stress was significant, during both years
while the interaction between varieties and seed priming was non-significant during
2014-15 but significant during 2015-16. The interaction between drought stress and seed
priming, and three way interaction among varieties, drought stress and seed priming were
significant, during both years (Table 4.7). Plant height was decreased with increase in
severity of drought stress. Taller plants were produced by Frontier-87 than Haider-93.
Seed priming enhanced the plant height of both barley varieties at all levels of drought
stress, as compared to unprimed control. Under moderate drought, during 2014-15
osmopriming of Frontier-87 and during 2015-16 biopriming of Frontier-87 caused 59
maximum increase in plant height. However, under severe drought the greatest increase in
plant height was recorded by biopriming of Frontier-87 during 2014-15 and osmopriming
of Frontier-87 during 2015-16 (Tables 4.8, 4.9).
4.1.3.2. Leaf area
Leaf area was significantly affected by drought stress and seed priming, during
both years. Selected barley varieties also differed significantly for leaf area, during both
growing seasons. The interaction between varieties and seed priming was non-significant,
during both years. The interactions between varieties and drought stress, and drought
stress and seed priming, and three way interaction among varieties, drought stress and
seed priming was significant, during both growing seasons (Table 4.7). There was a
decrease in leaf area with increase in severity of drought stress. Higher leaf area was
exhibited by Frontier-87 than Haider-93. Seed priming ameliorated the deleterious effects
of drought stress by improving the leaf area of both barley varieties at each level of
drought stress, as compared to unprimed control. Under moderate drought, maximum
increase in leaf area was caused by biopriming of Haider-93 during 2014-15 and
osmopriming of Frontier-87 during 2015-16. Under severe drought, the greatest increase
in leaf area was caused by biopriming of Frontier-87 (Tables 4.10, 4.11).
4.1.3.3. Total number of tillers per pot
There was a significant effect of drought stress and seed priming on total number
of tillers per pot, during both years; the tested varieties did not differ significantly for total
number of tillers per pot during 2014-15 while differed significantly growing 2015-16.
The interactions between varieties and drought stress, varieties and seed priming, drought
stress and seed priming were non-significant during 2014-15 while significant during
2015-16. However, the three way interaction among varieties, drought stress and seed
priming was significant, during both years (Table 4.12). The total number of tillers per
pot was decreased with increase in severity of drought stress. Haider-93 produced higher
number of tillers per pot than Frontier-87. Seed priming treatments improved the total
number of tillers per pot of both tested varieties at each level of drought stress, as
compared to unprimed control. Under moderate drought, maximum number of tillers per
pot was produced by biopriming of Haider-93 during 2014-15 and osmopriming of
Haider-93 during 2015-16. However, under severe drought, highest number of tillers was
produced by biopriming of Frontier-87 and Haider-93 during 2014-15 and 2015-16,
respectively (Tables 4.13, 4.14).
60
4.1.3.4. Number of productive tillers per pot
The number of productive tillers per pot was significantly affected by drought
stress and seed priming; the varieties also significantly differed, during both growing
seasons. Likewise, the interactions between varieties and drought stress, varieties and
seed priming, and drought stress and seed priming were non-significant during 2014-15
and significant during 2015-16. The three way interaction among varieties, drought and
seed priming was significant, during both years (Table 4.12). Number of productive tillers
was decreased with increase in drought severity. Haider-93 produced higher number of
productive tillers than Frontier-87. Moreover, seed priming improved the production of
number of productive tillers of both varieties at each level of drought, as compared to
unprimed control. Under moderate drought, maximum number of productive tillers was
produced by biopriming of Haider-93 during 2014-15 and osmopriming of Haider-93
during 2015-16. However, under severe drought, highest number of productive tillers was
produced by biopriming of Frontier-87 and Haider-93 during 2014-15 and 2015-16,
respectively (Tables 4.15, 4.16).
4.1.3.5. Spike length
Drought stress and seed priming significantly affected the spike length; tested
varieties also differed for spike length, during both years. The interaction between
varieties and drought stress was significant during 2014-15 while non-significant during
2015-16. The interaction between varieties and seed priming was non-significant during
2014-15 and significant during 2015-16. Interaction between drought stress and seed
priming as well as three way interaction among varieties, drought stress and seed priming
were significant, during both years (Table 4.17). There was a decrease in spike length
with increase in severity of drought stress. Longer spikes were produced by Haider-93
than Frontier-87. However, spike length of both tested varieties was enhanced by seed
priming treatments under all levels of drought stress, as compared to unprimed control.
Highest spike length was produced by osmopriming and biopriming of Haider-93 under
moderate and severe drought stress, respectively, during both years (Tables 4.18, 4.19).
4.1.3.6. Number of spikelets per spike
Drought stress and seed priming significantly affected the number of spikelets per
spike. The varieties also differed significantly for number of spikelets per spike, during
both years. The interaction between drought stress and seed priming was significant,
during both years. The interaction between varieties and drought stress was significant 61
during 2014-15 but non-significant 2015-16. However, the interaction between varieties
and seed priming, as well as three way interaction among varieties, drought and seed
priming were
62
Table 4.7: Analysis of variance for the influence of seed priming on plant growth of barley under drought stressSOV df Mean sum of square
Plant height Leaf area2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 435.63** 1227.66** 38845.3** 3782.3**
Drought (D) 2 1857.27** 931.17** 375779.1** 316092.0**
Priming (T) 3 348.14** 378.85** 13359.9** 27028.7**
V×D 2 100.52** 144.87** 26840.0** 1637.5**
V×T 3 32.45ns 62.03** 1093.1ns 989.7ns
D×T 6 49.25** 86.41** 1430.8** 6364.5**
V×D×T 6 51.01** 78.17** 4258.6** 2118.3**
Error 72 12.19 15.74 543.5 448.6Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, ns = Non-significant
Table 4.8: Influence of seed priming on plant height (cm) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 62.88 d-h 64.66 def 59.24 ghi 63.89 d-g 51.14 l 52.49 klHP 64.17 def 71.58 bc 58.88 hi 62.75 e-h 53.32 jkl 52.70 klOP 67.72 cd 86.43 a 65.26 de 71.16 bc 57.36 ijk 55.84 i-lBP 71.73 bc 73.70 b 60.29 f-i 65.32 de 57.82 ij 60.44 e-i
Varieties × Drought stress × Seed priming LSD≤0.05 = 4.9205
Table 4.9: Influence of seed priming on plant height (cm) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 61.31 fg 67.90 cd 58.10 f-i 67.67 cde 53.00 i 58.51 f-iHP 68.07 cd 68.76 cd 63.38 def 71.02 bc 55.39 hi 56.26 ghiOP 71.78 bc 72.47 bc 61.00 fg 74.86 b 63.65 def 71.26 bcBP 68.25 cd 87.74 a 60.05 fgh 75.14 b 62.08 ef 60.29 fgh
Varieties × Drought stress × Seed priming LSD≤0.05 = 5.5925
Table 4.10: Influence of seed priming on leaf area (cm2) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 507.14 cd 592.56 b 449.06 fgh 435.26 gh 298.86 m 318.93 lmHP 523.10 cd 597.05 b 419.81 hi 452.00 fgh 330.95 lm 345.94 klOP 516.12 cd 643.39 a 471.96 ef 462.05 efg 394.13 ij 368.92 jkBP 529.91 c 656.27 a 490.56 de 439.35 fgh 336.87 kl 439.53 fgh
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 32.8620
63
Table 4.11: Influence of seed priming on leaf area (cm2) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 506.34 ef 529.58 def 419.71 j 435.20 ij 332.09 m 321.97 mHP 548.50 cd 535.59 cde 459.66 hi 448.68 hij 327.63 m 348.02 lmOP 561.10 c 542.85 cd 501.79 fg 522.27 def 337.48 m 371.41 klBP 595.99 b 647.84 a 476.13 gh 447.53 hij 386.74 kl 452.87 hi
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 29.8548
Table 4.12: Analysis of variance for the influence of seed priming on number of total and productive tillers of barley under drought stress SOV df Mean sum of square
Total No. of tillers per pot No. of productive tillers per pot2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 2.042ns 6.253** 2.470** 4.092**
Drought (D) 2 104.073** 162.003** 110.165** 134.984**
Priming (T) 3 37.458** 33.246** 17.634** 18.292**
V×D 2 0.948ns 4.346** 0.276ns 2.016**
V×T 3 0.792ns 1.433** 0.068ns 0.716**
D×T 6 0.531ns 2.850** 0.162ns 1.380**
V×D×T 6 3.323** 3.444** 1.674** 2.189**
Error 72 0.667 0.319 0.255 0.138Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, ns = Non-significant
Table 4.13: Influence of seed priming on total number of tillers per pot of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 13.75 def 13.75 def 12.50 gh 11.75 hi 10.25 j 9.75 jHP 15.25 bc 14.00 de 12.75 fgh 13.00 efg 12.00 gh 10.75 ijOP 17.25 a 15.75 b 13.75 def 15.75 b 12.75 fgh 12.25 ghBP 15.75 b 16.00 b 15.50 b 14.25 cd 12.00 gh 13.00 efg
Varieties × Drought stress × Seed priming LSD≤0.05 = 1.1509
Table 4.14: Influence of seed priming on total number of tillers per pot of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 14.25 ef 13.75 efg 12.75 hi 11.50 jk 9.50 l 9.00 lHP 15.25 cd 15.25 cd 14.50 de 12.50 hi 11.00 k 12.75 hiOP 16.25 b 17.25 a 15.50 bc 13.63 fg 11.00 k 11.50 jkBP 18.00 a 15.75 bc 13.75 efg 13.75 efg 13.00 gh 12.00 ij
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 0.7956
64
Table 4.15: Influence of seed priming on number of productive tillers per pot of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 10.73 e 10.54 ef 8.92 hij 8.51 ij 6.98 k 6.84 kHP 11.82 bc 10.99 de 9.14 hi 9.37 gh 8.21 j 7.39 kOP 13.08 a 11.87 bc 9.97 fg 10.76 de 8.81 hij 8.48 ijBP 12.25 b 12.35 b 11.45 cd 9.87 fg 8.35 j 8.88 hij
Varieties × Drought stress × Seed priming LSD≤0.05 = 0.7121
Table 4.16: Influence of seed priming on number of productive tillers per pot of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 10.79 d 10.29 e 9.05 f 8.03 g 6.65 i 6.47 iHP 11.54 c 11.54 c 10.32 e 8.78 f 7.48 h 8.69 fOP 12.30 b 13.05 a 11.44 c 10.05 e 7.69 gh 7.88 ghBP 13.55 a 11.80 bc 9.82 e 10.04 e 9.05 f 8.11 g
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 0.5236
Table 4.17: Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under drought stress SOV df Mean sum of square
Spike length No. of spikelets per spike2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 7.432** 2.895** 21.028** 4.133*
Drought (D) 2 15.130** 17.597** 67.970** 62.527**
Priming (T) 3 2.540** 3.721** 14.858** 7.406**
V×D 2 1.201** 0.127ns 3.042* 0.182ns
V×T 3 0.154ns 0.345* 2.116ns 0.640ns
D×T 6 0.928** 0.456** 3.894** 1.710*
V×D×T 6 0.529** 0.431** 1.576ns 0.820ns
Error 72 0.143 0.092 0.970 0.596Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.18: Influence of seed priming on spike length (cm) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 7.36 c-g 7.41 c-f 7.10 efg 6.97 fg 6.21 i 5.15 jHP 7.86 bc 7.09 efg 7.13 d-g 6.34 hi 6.37 hi 6.15 iOP 8.60 a 8.24 ab 7.41 c-f 6.88 gh 7.25 d-g 5.87 iBP 7.86 bc 7.52 cde 6.98 fg 7.19 d-g 7.65 cd 6.30 i
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 0.5330
65
Table 4.19: Influence of seed priming on spike length (cm) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 7.47 def 6.90 g-j 6.55 jkl 6.47 kl 5.83 no 5.51 oHP 8.05 ab 7.45 def 6.62 i-l 6.57 jkl 5.99 mn 5.95 mnOP 8.37 a 7.56 cde 7.83 bcd 6.56 jkl 6.28 lm 6.29 lmBP 7.92 bc 7.97 abc 7.02 ghi 7.10 fgh 7.30 efg 6.73 h-k
Varieties × Drought stress × Seed priming LSD≤0.05 = 0.4271
Table 4.20a: Influence of seed priming on number of spikelets per spike of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 14.17 a 13.35 b 11.54 c 13.02 AF-87 13.84 ab 11.79 c 10.63 d 12.09 BMean 14.00 A 12.57 B 11.09 C
Varieties LSD≤0.05 = 0.4008, Drought stress LSD≤0.05 = 0.4909, Varieties × Drought stress LSD≤0.05 = 0.6942
Table 4.20b: Influence of seed priming on number of spikelets per spike of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 12.95 bcd 12.18 def 10.42 g 11.85 CHP 13.17 bc 12.65 cde 10.41 g 12.08 BOP 16.05 a 13.17 bc 11.61 f 13.61 ABP 13.84 b 12.29 c-f 11.92 ef 12.68 BMean 14.00 A 12.57 B 11.09 C
Drought stress LSD≤0.05 = 0.4909, Seed priming LSD≤0.05 = 0.5668, Drought stress × Seed priming LSD≤0.05 = 0.9818
Table 4.21a: Influence of seed priming on number of spikelets per spike of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 14.01 12.73 11.07 12.60 AF-87 13.43 12.34 10.79 12.19 BMean 13.72 A 12.54 B 10.93 C
Varieties LSD≤0.05 = 0.3140, Drought stress LSD≤0.05 = 0.3846
Table 4.21b: Influence of seed priming on number of spikelets per spike of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 12.90 bcd 12.18 de 10.30 f 11.79 BHP 13.43 bc 12.06 e 10.73 f 12.07 BOP 13.60 b 12.83 cd 11.73 e 12.72 ABP 14.93 a 13.07 bc 10.96 f 12.99 AMean 13.72 A 12.54 B 10.93 C
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Drought stress LSD≤0.05 = 0.3846, Seed priming LSD≤0.05 = 0.4441, Drought stress × Seed priming LSD≤0.05 = 0.7692
66
non-significant, during both years (Table 4.17). The drought stress decreased the number
of spikelets with minimum spikelets produced at severe drought, during both years.
Haider-93 produced higher number of spikelets as compared to Frontier-87. Seed priming
improved the number of spikelets per spike as compared to unprimed control and
maximum increase was caused by osmopriming during 2014-15 and biopriming during
2015-16 (Tables 4.20a-4.21b). Under moderate drought, maximum improvement in
number of spikelets was caused by osmopriming during 2014-15 and biopriming during
2015-16. However, under severe drought, biopriming during 2014-15 and osmopriming
during 2015-16 caused maximum increase in number of spikelets per spike (Tables 4.20b,
4.21b).
4.1.3.7. Number of grains per spike
Drought stress and seed priming significantly affected the grains per spike of
barley during; tested barley varieties also differed for grains per spike, during both years.
Likewise, the interaction between varieties and drought strss, varieties and seed priming,
drought stress and seed priming, and three way interaction among varieties, drought stress
and seed priming was significant for grains per spike, during both growing seasons (Table
4.22). Number of grains per spike was decreased with increase in severity of drought
stress. More number of grains per spike were recorded in variety Haider-93 than the
variety Frontier-87. Seed priming treatments ameliorated the effect of drought stress by
improving the number of grains per spike in both varieties, as compared to unprimed
control. Under moderate drought, biopriming of Haider-93 caused maximum increase in
number of grains per spike, during both growing seasons. However, under severe drought,
maximum increase in number of grains per spike was noted in osmopriming of variety
Haider-93, during both seasons (Tables 4.23, 4.24).
4.1.3.8. 100-grain weight
Drought stress and seed priming significantly affected the 100-grain weight of
barley during; tested barley varieties also differed for 100-grain weight, during both
growing seasons. The interactions between varieties and drought stress, and varieties and
seed priming was non-significant during 2014-15 and significant during 2015-16.
However, the interaction between drought stress and seed priming and three way
interaction among varieties, drought stress and seed priming was significant, during both
years (Table 4.22). Grain weight was decreased with increase in severity of drought
stress. Grain weight in variety Haider-93 was higher than the variety Frontier-87. Seed
priming treatments improved the 100-grain weight of both barley varieties at all levels of 67
drought stress, as compared to unprimed control. Under mild drought, biopriming of
Haider-93 had maximum increase in 100-grain weight, during both years. Under severe
drought, the greatest improvement in 100-grain weight was recorded by osmopriming and
biopriming of Haider-93 during 2014-15 and 2015-16, respectively. However, the effect
of osmopriming of Haider-93 was at par with biopriming of Haider-93 under severe
drouhgt during 2015-16 (Tables 4.25, 4.26).
4.1.3.9. Grain yield per pot
There was a significant effect of drought stress and seed priming on grain yield;
likewise, the tested varieties differed significantly for grain yield, during both years. The
interaction between varieties and drought stress was non-significant during 2014-15 while
significant during 2015-16. However, the interactions between varieties and seed priming,
drought stress and seed priming as well as three way interaction among varieties, drought
stress and seed priming was significant, during both growing seasons (Table 4.27). Grain
yield was decreased with increase in severity of drought stress. Haider-93 produced
higher grain yield than Frontier-87. Seed priming treatments improved the grain yield of
both tested varieties at each level of drought stress, as compared to unprimed control.
Under moderate drought, maximum increase in grain yield was occurred by biopriming of
Haider-93, during both years. Under severe drought, osmopriming and biopriming of
Haider-93 caused the greatest improvement in grain yield during 2014-15 and 2015-16,
respectively (Tables 4.28, 4.29).
4.1.3.10. Biological yield
A significant effect of drought stress and seed priming was noticed for biological
yield, during both years; however, the barley varieties differed significantly during 2014-
15 but did not differ significantly during 2015-16. The interactions between varieties and
drought stress, and drought stress and seed priming were significant, during both years.
Whereas, interaction between varieties and seed priming, and three way interaction
among varieties, drought stress and seed priming was non-significant during 2014-15 but
significant during 2015-16 (Table 4.27). Drought stress decreased the biological yield of
both varieties. Haider-93 produced higher biological yield than Frontier-87. Seed priming
improved the biological yield of both varieties, as compared to unprimed control. Under
mild as well as severe drought, greatest improvement in biological yield was noticed by
biopriming of Haider-93 (Tables 4.30a, 4.31).
4.1.3.11. Harvest index
68
Drought stress and seed priming significantly affected the harvest index of barley,
during both seasons; tested barley varieties also differed for harvest index. The interaction
between varieties and drought stress was significant, during both years. However, the
interactions between varieties and seed priming, drought stress and seed priming, and
three way interaction among varieties, drought stress and seed priming was significant
during 2014-15 but non-significant during 2015-16 (Table 4.27). Drought stress
decreased the harvest index of barley with increase in its severity. Haider-93 recorded
higher harvest index than Frontier-87. However, harvest index of both tested barley
varieties was improved by seed priming treatments under all levels of drought stress, as
compared to unprimed control. During 2014-15, the highest harvest index was recorded
by biopriming of Haider-93 and osmopriming of Frontier-87 under moderate and severe
drought, respectively. However, during 2015-16, drought stress caused a linear reduction
in harvest index with increasing stress severity. Variety Haider-93 produced higher
harvest index than Frintiers-87. Across drought stress and varieties, the osmopriming
caused maximum increase in harvest index (Tables 4.32-4.33b).
4.1.4. Discussion
Drought stress decreased growth and development of barley varieties. Drought
stress reduces plant growth by imposing its deleterious effects on mitotic activities and
cell elongation (Anjum et al., 2017b). Similar decrease in growth and development of
chick pea by drought at reproductive growth stage has been reported by Mafakheri et al.
(2010). However, in present study, seed priming treatments improved the growth of
barley plants under each level of drought stress. The improved plant growth by seed
priming under stressed conditions is attributed to early head start by greater early seedling
vigour (Afzal et al., 2006) and by improving the stress tolerance achieved through
improved water relations, osmolytes accumulation and antioxidants defense (Chen and
Arora, 2013; Tabassum et al., 2017). In present study, the improved plant growth by
osmopriming is attributed to improved cell wall structure, cell membrane integrity and
functioning, mitotic activity, and cell turgor and elongation by ca2+ which was used in
osmopriming (Hepler, 2005). Moreover, improved growth by biopriming might be due to
endophytic bacteria which improve the plant growth under normal and stressed conditions
by enhancing the uptake of water and nutrients, and enhanced production of auxin,
gibberellic acid and cytokinins while decreasing the levels of ethylene through production
of ACC deaminase (Santoyo et al., 2016).
69
The grain yield and harvest index of barley varieties was decreased by drought
stress with increase in its severity. However, the variety Haider-93 produced higher grain
yield and harvest index under severe drought which is attributed to higher number of
70
Table 4.22: Analysis of variance for the influence of seed priming on number of grains per spike and 100-grain weight of barley under drought stress SOV df Mean sum of square
No. of grains per spike 100-grain weight2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 66.600** 42.294** 0.190** 0.844**
Drought (D) 2 1479.248** 2018.698** 4.774** 6.549**
Priming (T) 3 100.164** 48.944** 0.947** 0.599**
V×D 2 12.967** 6.206** 0.025ns 0.051**
V×T 3 8.743** 4.698* 0.016ns 0.094**
D×T 6 8.419** 5.378** 0.075* 0.033*
V×D×T 6 6.459** 4.626** 0.077** 0.039**
Error 72 1.129 0.909 0.014 0.010Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.23: Influence of seed priming on number of grains per spike of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 33.92 de 32.28 fg 28.01 jk 26.73 kl 22.01 n 19.65 pHP 36.27 c 33.58 ef 28.61 ij 28.28 ij 24.07 m 20.37 opOP 35.10 cd 38.24 b 30.89 gh 30.81 gh 25.34 lm 22.42 nBP 40.22 a 39.57 ab 34.19 de 29.72 hi 24.79 m 21.78 no
Varieties × Drought stress × Seed priming LSD≤0.05 = 1.4976
Table 4.24: Influence of seed priming on number of grains per spike of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 33.63 c 32.37 c 27.84 f 26.45 g 19.85 jk 17.65 lHP 36.28 ab 37.51 a 28.68 ef 27.85 f 20.73 ij 18.80 klOP 37.38 a 37.26 a 29.56 de 30.48 d 22.52 h 19.50 jkBP 36.99 a 35.55 b 32.89 c 28.43 ef 21.34 hi 19.90 jk
Varieties × Drought stress × Seed priming LSD≤0.05 = 1.3443
Table 4.25: Influence of seed priming on 100-grain weight (g) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 3.22 e 3.30 de 2.90 hi 2.80 ij 2.55 kl 2.50 lHP 3.61 bc 3.18 efg 3.02 fgh 3.17 ef 2.84 ij 2.69 jkOP 3.84 a 3.83 a 3.24 e 3.22 e 3.01 gh 2.68 jkBP 3.63 b 3.58 bc 3.45 cd 3.30 de 2.88 hi 2.85 hij
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 0.1681
71
Table 4.26: Influence of seed priming on 100-grain weight (g) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 3.29 ef 3.17 fg 2.93 ij 2.73 k 2.45 lm 2.26 nHP 3.32 e 3.59 bc 3.06 ghi 2.87 jk 2.54 lm 2.40 mOP 3.79 a 3.47 cd 3.17 fg 3.02 hi 2.85 jk 2.56 lBP 3.61 b 3.37 de 3.36 de 3.09 gh 2.86 jk 2.45 lm
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 0.1388
Table 4.27: Analysis of variance for the influence of seed priming on grain yield, biological yield and harvest index of barley under drought stressSOV df Mean sum of square
Grain yield Biological yield Harvest index2014-15 2015-16 2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 8.598** 1.503** 28.703** 0.751ns 33.583** 22.234**
Drought (D) 2 280.125** 370.567** 1124.787** 2103.445** 1098.881** 891.370**
Priming (T) 3 20.548** 15.545** 91.122** 64.256** 60.466** 60.160**
V×D 2 0.291ns 1.257** 11.155** 10.276** 14.747** 13.666**
V×T 3 0.604* 1.234** 0.706ns 11.026** 3.944* 1.183ns
D×T 6 1.400** 2.114** 4.516** 10.260** 1.794ns 2.157ns
V×D×T 6 0.544** 0.624** 1.575ns 2.424* 4.251** 1.943ns
Error 72 0.100 0.063 1.006 0.996 0.880 1.906Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.28: Influence of seed priming on grain yield (g per pot) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 8.17 ef 8.08 ef 5.68 i 5.18 j 3.20 m 2.94 mHP 9.77 c 8.49 de 6.03 i 5.87 i 3.70 l 3.13 mOP 10.41 b 10.22 b 7.97 f 7.28 g 4.35 k 3.92 klBP 11.06 a 10.21 bc 8.62 d 6.82 h 4.11 kl 3.74 l
Varieties × Drought stress × Seed priming LSD≤0.05 = 0.4462
Table 4.29: Influence of seed priming on grain yield (g per pot) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 7.96 f 7.95 f 5.67 k 5.15 l 2.56 qr 2.25 rHP 9.09 e 10.81 b 6.61 i 6.11 j 2.86 opq 2.67 pqOP 11.17 a 10.81 b 7.29 g 6.97 gh 3.28 mn 3.05 noBP 10.19 c 9.58 d 7.79 f 6.74 hi 3.55 m 2.93 nop
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 0.3538
72
Table 4.30a: Influence of seed priming on biological yield (g per pot) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 28.02 a 24.23 b 17.39 d 23.21 AF-87 28.24 a 22.78 c 15.34 e 22.12 BMean 28.13 A 23.50 B 16.36 C
Varieties LSD≤0.05 = 0.4083, Drought stress LSD≤0.05 = 0.5001, Varieties × Drought stress LSD≤0.05 = 0.7073
Table 4.30b: Influence of seed priming on biological yield (g per pot) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 25.54 d 20.70 f 15.03 h 20.43 CHP 27.45 c 22.03 e 15.45 h 21.65 BOP 29.24 b 25.46 d 17.82 g 24.17 ABP 30.28 a 25.82 d 17.14 g 24.42 AMean 28.13 A 23.50 B 16.36 C
Drought stress LSD≤0.05 = 0.5001, Seed priming LSD≤0.05 = 0.5775, Drought stress × Seed priming LSD≤0.05 = 1.0002
Table 4.31: Influence of seed priming on biological yield (g per pot) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 23.58 de 24.16 d 20.23 f 19.57 f 10.84 i 9.29 jHP 26.00 c 30.18 a 22.53 e 23.39 de 11.68 hi 10.75 iOP 28.86 ab 29.74 a 22.60 e 23.38 de 12.29 gh 11.54 hiBP 27.88 b 25.97 c 25.65 c 24.15 d 13.22 g 11.12 hi
Varieties × Drought stress × Seed priming LSD≤0.05 = 1.4071
Table 4.32: Influence of seed priming on harvest index (%) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought
H-93 F-87 H-93 F-87 H-93 F-87Control 31.96 d 31.66 d 26.63 gh 25.79 h 20.15 l 20.70 klHP 35.56 ab 30.96 d 26.84 gh 27.16 fg 22.28 j 21.94 jkOP 36.02 a 34.58 bc 31.07 d 28.88 e 22.80 ij 23.67 iBP 36.71 a 33.56 c 31.38 d 28.20 ef 22.83 ij 22.93 ij
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 1.3224
73
Table 4.33a: Influence of seed priming on harvest index (%) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 36.07 a 30.00 b 25.43 d 30.50 AF-87 35.54 a 27.57 c 25.50 d 29.54 BMean 35.80 A 28.79 B 25.46 C
Varieties LSD≤0.05 = 0.5617, Drought stress LSD≤0.05 = 0.6880, Varieties × Drought stress LSD≤0.05 = 0.9730
Table 4.33b: Influence of seed priming on harvest index (%) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 33.48 27.23 23.81 28.17 DHP 35.42 27.73 24.80 29.32 COP 37.57 31.04 26.56 31.72 ABP 36.75 29.16 26.68 30.86 BMean 35.80 A 28.79 B 25.46 C
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Drought stress LSD≤0.05 = 0.6880, Seed priming LSD≤0.05 = 0.7944
74
productive tillers, spike length, number of spikelets, number of grain and grain weight
than Frontier-87. Drought stress affects the pollen viability due to decrease in pollen
moisture ultimately causing decrease in grain setting and spikelet fertility (Saragih et al.,
2013). Moreover, the drought stress decreases the photosynthesis and assimilate
translocation thus significantly decreasing the grain weight (Farooq et al., 2009a; Dong et
al., 2017). In present study, the seed priming improved grain yield and harvest index of
both varieties under drought stress. It was observed that seed priming enhanced the spike
length and number of spikelets which produced greater number of grains. Moreover, the
grain weight was improved by seed priming treatments which contributed to improved
grain yield and harvest index. The improved osmolytes accumulation, tissue water status
and better protection of cellular membranes from lipid peroxidation by seed priming
resulted in improved number of grains and grain weight under normal and stressed
conditions (Tabassum et al., 2017).
Improvement in grain yield of barley by osmopriming might be attributed to better
cell membrane stability by Ca2+ which led to improved pollen viability and number of
grains. Moreover, Ca2+ improves the photosynthesis, decreases ROS activity and lipid
peroxidation by enhanced osmolytes and antioxidants activity ultimately improving the
number of grains, grain weight and grain yield under stressed conditions (Dolatabadian et
al., 2013). Likewise, improved grain and biological yield, and harvest index by
biopriming is attributed to improved growth, osmolytes accumulation, and water and
nutrient relations by endophytic bacteria. Endophytic bacteria enhances production of
auxin while decreasing the ethylene accumulation which results in improved chlorophyll,
greater accumulation of osmolytes, and improved water and nutrient relations which is
translated into improved yield and harvest index (Santoyo et al., 2016). Similarly, Naveed
et al. (2014c) reported that endophytic bacterial Burkholderia phytofrmans strain PsJN
improved the photosynthesis, nutrients uptake, water relations, and yield and related traits
of wheat under drought stress.
4.1.5. Chlorophyll contents
4.1.5.1. Chlorophyll a content
The chlorophyll a content was significantly affected by drought stress and seed
priming; barley varieties significantly differed for the chlorophyll a, during both growing
seasons. The interaction between varieties and drought stress was significant, during both
years. However, the interactions between varieties and seed priming, and drought stress
and seed priming were significant during 2014-15 while non-significant during 2015-16. 75
The three way interaction among varieties, drought stress and seed priming was
significant, during both years (Table 4.34). There was a decrease in chlorophyll a with
increase in severity of drought stress. Haider-93 exhibited higher chlorophyll a than
Frontier-87 under well-watered and mild drought conditions while inverse was observed
under severe drought. However, seed priming ameliorated the deleterious effects of
drought stress by improving the chlorophyll a of both varieties at each level of drought
stress, as compared to unprimed control. During 2014-15 biopriming of Haider-93
resulted in greatest improvement in chlorophyll a content under both moderate and severe
drought. However, during 2015-16 maximum increase in chlorophyll a was observed by
osmopriming of Frontier-87 and Haider-93 under moderate and severe drought,
respectively (Figures 4.1a,b).
4.1.5.2. Chlorophyll b content
A significant effect of drought stress and seed priming was observed for
chlorophyll b content; the tested barley varieties also differed significantly for chlorophyll
b, during both growing seasons. The interaction between varieties and drought stress was
significant during 2014-15 but non-significant during 2015-16. Whereas, the interactions
between varieties and seed priming, and drought stress and seed priming as well as three
way interaction among varieties, drought and seed priming was significant, during both
years (Table 4.34). Chlorophyll b was decreased with increasing level of drought stress.
Haider-93 produced higher chlorophyll b content than Frontier-87. However, seed
priming ameliorated the deleterious effects of drought stress by improving the chlorophyll
b of both varieties at each level of drought stress, as compared to unprimed control.
Under moderate drought, highest chlorophyll b content was recorded by biopriming and
osmopriming of Haider-93 during 2014-15 and 2015-16, respectively. However, under
severe drought osmopriming and biopriming of Haider-93 caused the maximum increase
in chlorophyll b during 2014-15 and 2015-16, respectively (Figures 4.1c,d).
4.1.6. Osmolytes accumulation
4.1.6.1. Total soluble phenolics
The total soluble phenolics content was significantly affected by drought stress
and seed priming, during both years. The varieties did not differ significantly during
2014-15 while significantly differed during 2015-16. The interaction between varieties
and drought stress was non-significant during 2014-15 but significant during 2015-16.
However, the interactions between varieties and seed priming, drought stress and seed
priming as well as three way interaction among varieties, drought and seed priming was 76
significant, during both growing seasons (Table 4.35). Total soluble phenolics were
increased with an increase in the severity of drought stress. Haider-93 biosynthesized
more total soluble phenolics than Frontier-87 under control and mild drought while
opposite was observed under severe stress. However, total soluble phenolics contents of
both varieties were further increased by seed priming treatments under all levels of
drought stress, as compared to unprimed control. Under moderate drought, highest
phenolics content was produced by biopriming and osmopriming of Haider-93 during
2014-15 and 2015-16, respectively. However, under severe drought osmopriming and
biopriming of Haider-93 caused the maximum increase in phenolics content during 2014-
15 and 2015-16, respectively (Figures 4.2a,b).
4.1.6.2. Total soluble proteins
Drought stress and seed priming significantly affected the total soluble proteins;
however, the barley varieties did not differ significantly, during both growing seasons.
Similarly, the interaction between varieties and drought stress was non-significant, during
both years. However, the interactions between varieties and seed priming, drought stress
and seed priming, and three way interaction among varieties, drought stress and seed
priming was significant, during both years (Table 4.35). Total soluble proteins were
increased proportionally under drought stress relative to its severity. Haider-93 produced
greater total soluble proteins than Frontier-87. Furthermore, seed priming treatments
further increased the contents of total soluble proteins of both tested varieties under
drought stress, as compared to unprimed control. Under moderate stress, the highest total
soluble proteins content was recorded by osmopriming of Haider-93 and biopriming of
Frontier-87 during 2014-15 and biopriming of Haider-93 during 2015-16. Under severe
drought, hydropriming and osmopriming of Haider-93 exhibited highest total soluble
proteins during 2014-15 and 2015-16, respectively (Figures 4.2c,d).
4.1.6.3. Free proline content
There was a significant effect of drought stress and seed priming on free leaf
proline content, during both years; the barley varieties also differed significantly for free
proline content. The interactions between varieties and drought stress, varieties and seed
priming, drought stress and seed priming, and three way interaction among varieties,
drought stress and seed priming was significant, during both years (Table 4.36). Proline
content was increased with increase in severity of drought stress. Haider-93
biosynthesized more free proline than Frontier-87. Seed priming treatments further
increased the proline contents of both varieties under drought stress, as compared to 77
unprimed control. The greatest increase in free leaf proline content was recorded by
osmopriming of Haider-93 under both moderate
78
Table 4.34: Analysis of variance for the influence of seed priming on chlorophyll contents of barley under drought stress SOV df Mean sum of square
Chlorophyll a Chlorophyll b2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 0.0084** 0.0054** 0.0048** 0.0023*
Drought (D) 2 0.1409** 0.1152** 0.0210** 0.0484**
Priming (T) 3 0.0075** 0.0059** 0.0064** 0.0033**
V×D 2 0.0011* 0.0013* 0.0008** 0.0001ns
V×T 3 0.0024** 0.0002ns 0.0003* 0.0004**
D×T 6 0.0029** 0.0003ns 0.0009** 0.0002**
V×D×T 6 0.0011** 0.0010** 0.0008** 0.0005**
Error 72 0.0002 0.0002 0.0001 0.0001Total 95
Table 4.35: Analysis of variance for the influence of seed priming on total soluble proteins and total soluble phenolics contents of barley under drought stress SOV df Mean sum of square
Total soluble phenolics Total soluble proteins2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 238.7ns 1053.1** 0.0003ns 0.0023ns
Drought (D) 2 52503.9** 60190.5** 0.9519** 0.9148**
Priming (T) 3 23811.9** 11385.4** 0.0089** 0.0176**
V×D 2 119.9ns 680.6* 0.0002ns 0.0015ns
V×T 3 1421.8* 815.3** 0.0032** 0.0064*
D×T 6 3176.1** 4090.7** 0.0051** 0.0049**
V×D×T 6 2690.6** 2879.5** 0.0079** 0.0073**
Error 72 66.6 83.5 0.0005 0.0007Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
79
Chl
orop
hyll
a co
nten
t (m
g g-1
FW
)C
hlor
ophy
ll b
cont
ent (
mg
g-1 F
W)
80
Tot
al so
lubl
e ph
enol
ics (
µg g
-1 F
W)
Tot
al so
lubl
e pr
otei
ns (m
g g-1
FW)
81
and severe drought, during both years (Figures 4.3a,b).
4.1.6.4. Glycine betaine content
The drought stress and seed priming significantly affected the leaf glycine betaine
content during bth years; however, the tested barley varieties differed significantly during
2014-15 but did not differ significantly during 2015-16. The interaction between drought
stress and seed priming was non-significant during 2014-15 but significant during 2015-
16. Whereas, the interactions between varieties and drought stress, varieties and seed
priming, and three way interaction among varieties, drought stress and seed priming was
significant, during both years (Table 4.36). An increase in glycine betaine content was
noticed with increase in drought stress levels. Moreover, Haider-93 exhibited higher
glycine betaine content than Frontier-87. However, glycine betaine of both varieties was
further increased by seed priming treatments under all levels of drought stress, as
compared to unprimed control. During 2014-15, maximum increase in glycine betaine
was consequenced by biopriming of Haider-93 under both moderate and severe drought.
Whereas, during 2015-16, highest glycine betaine content was noticed by osmopriming of
Frontier-87 under both moderate and severe drought stress (Figures 4.3c,d).
4.1.7. Lipid peroxidation
4.1.7.1. Malondialdehyde content
Malondialdehyde content was significantly affected by drought stress and seed
priming, during both growing seasons; the tested barley varieties also significantly
differed for MDA content. The interaction between varieties and drought stress was
significant, during both years. However, the interactions between varieties and seed
priming, and drought stress and seed priming were significant during 2014-15 but non-
significant during 2015-16. The three way interaction among varieties, drought and seed
priming was significant, during both years (Table 4.37). Malondialdehyde accumulation
was increased with increase in severity of drought stress. Haider-93 accumulated less
MDA than Frontier-87. However, seed priming treatments caused a reduction in the
MDA accumulation in both tested varieties under all level of drought stress, as compared
to unprimed control. Minimum MDA content occurred by osmopriming and biopriming
of Frontriers-87 under moderate and severe drought, respectively, during 2014-15, while,
during 2015-16 biopriming and osmopriming of Haider-93 caused maximum decrease in
MDA under moderate and severe drought, respectively (Figures 4.4a,b).
82
4.1.7.2. Cell membrane stability
Cell membrane stability was significantly affected by drought stress and seed
priming; while barley varieties also differed significantly for cell membrane stability,
during both growing seasons. The interaction between varieties and seed priming was
non-significant during 2014-15 but significant during 2015-16. However, the interactions
between varieties and drought stress, drought stress and seed priming as well as three way
interaction among varieties, drought stress and seed priming was significant, during both
growing seasons (Table 4.37). Cell membrane stability was decreased with increase in
severity of drought stress. Haider-93 exhibited better cell membrane stability than
Frontier-87. However, seed priming ameliorated the deleterious effects of drought stress
by improving the cell membrane stability of both barley varieties at each level of drought
stress, as compared to unprimed control. Under moderate drought, greatest improvement
in cell membrane stability was noticed by biopriming of Haider-93, during both years.
Under severe drought, osmopriming of Haider-93 exhibited greatest improvement in cell
membrane stability, during both years. However, hydropriming of Frontier-87 produced
similar results for cell membrane stability during 2015-16 (Figures 4.4c,d).
4.1.8. Discussion
Drought stress impaired the chlorophyll synthesis and cell membrane stability
while increased the accumulation of osmolytes and MDA contents in both barley varieties
with increase in its severity. Drought stress hampers the growth and development of
plants by imposing deleterious effects on normal functioning of the photosynthetic
machinery, enzyme activities and oxidative burst by aggravated ROS activity (Xu and
Zhou, 2006). Nonetheless, plants turn on physiological and metabolic mechanisms which
assist in the maintenance of tissue water status and prevent injuries of oxidative stress
(Ahmadi et al., 2010). Under stressed conditions, plants tend to increase the biosynthesis
and accumulation of osmolytes that help in maintaining the tissue water status, and
protect cellular organelles and organic molecules from ROS activity by acting as physical
barriers (Kumar et al., 2012). Plants accumulate various osmolytes viz. free proline,
glycine betaine, soluble proteins and sugars, sugar alcohols, free amino acids, phenolics
etc. in large amounts under drought stress (Farooq et al., 2009a). In present study,
accumulation of osmolytes was increased in barley varieties which assisted in
maintaining the tissue water status.
In present study, better maintenance of chlorophyll and cell membrane stability by
greater accumulation of osmolytes and decreased lipid peroxidation in Haider-93 under 83
severe drought was associated with its greater stress tolerance ability. Kerepesi and
Galiba
84
Table 4.36: Analysis of variance for the influence of seed priming on free proline and glycine betaine contents of barley under drought stress SOV df Mean sum of square
Free proline content Glycine betaine content2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 0.0611** 0.0852** 0.0150** 0.0001ns
Drought (D) 2 0.2737** 0.1335** 0.3492** 0.3279**
Priming (T) 3 0.0364** 0.0187** 0.0531** 0.0224**
V×D 2 0.0127** 0.0060** 0.0027* 0.0072**
V×T 3 0.0026* 0.0032* 0.0149** 0.0083**
D×T 6 0.0037** 0.0043** 0.0016ns 0.0053*
V×D×T 6 0.0042** 0.0051** 0.0051** 0.0028*
Error 72 0.0008 0.0006 0.0008 0.0003Total 95
Table 4.37: Analysis of variance for the influence of seed priming on malondialdehyde and cell membrane stability of barley under drought stressSOV df Mean sum of square
Malondialdehyde Cell membrane stability2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 38.44** 403.39** 563.40** 482.99**
Drought (D) 2 2681.88** 4674.29** 6270.79** 4312.61**
Priming (T) 3 184.76** 72.42** 951.41** 359.60**
V×D 2 103.97** 87.01** 156.39** 249.68**
V×T 3 118.72** 4.38ns 5.84ns 35.62*
D×T 6 26.97* 12.46ns 57.16** 46.12**
V×D×T 6 43.23** 57.19** 72.42** 42.77**
Error 72 4.75 5.82 6.29 8.01Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
85
Free
pro
line
cont
ent (
µmol
g-1
FW
)G
lyci
ne b
etai
ne c
onte
nt (µ
mol
g-1
FW
)
86
Mal
ondi
alde
hyde
con
tent
(µm
ol g
-1 F
W)
Cel
l mem
bran
e st
abili
ty (%
)
87
(2000) reported that wheat seedlings exposed to drought stress showed more sucrose in
tolerant varieties as compared to sensitive ones. Similarly, Anjum et al. (2017c) reported
that tolerant varieties of maize accumulated more total soluble phenolics, proteins,
carbohydrates, free proline and glycine betaine, and exhibited decreased ROS activity and
lipid peroxidation than sensitive varieties.
Seed priming improved the leaf chlorophyll contents, cell membrane stability and
osmolytes accumulation while decreased the MDA accumulation in both barley varieties.
The higher chlorophyll contents in response to seed priming is attributed to better
protection of cellular membranes as indicated by well-maintained cell membrane stability
in response to seed priming (Song et al., 2017). The improved cell membrane stability in
turn is attributed to enhanced accumulation of osmolytes and decreased lipid peroxidation
(Tabassum et al., 2017). It is considered that seed priming induces stress itself because of
loss in desiccation tolerance followed by given desiccation and osmotic stress in case of
osmopriming that triggers the gene expression for osmolytes and heat shock proteins by
accumulation of transcription factors (Kibinza et al., 2011; Chen et al., 2012). The early
stress caused by seed priming induces cross tolerance in plants to subsequent stresses
through rapid expression of genes for osmolytes (Chen and Arora, 2013). Moreover, in
present study, greater accumulation of osmolytes by osmopriming might be due to the
role of Ca2+ as secondary messenger that enhanced the gene expression for osmolytes
(White and Broadley, 2003).
In current study, biopriming with endophytic bacteria ameliorated the damaging
effects of drought by substantially improving the accumulation of osmolytes and
decreasing the lipid peroxidation in both barley varieties under severe drought stress. This
might be due to endophytic bacteria which produces osmolytes in response to abiotic
stresses that act synergistically with plant produced osmolytes to induce stress tolerance
(Dimkpa et al., 2009). Moreover, endophytic plant growth promoting bacteria place the
metabolism of plants in primed state that enable greater and rapid accumulation of
transcription factors and metabolites for osmolytes and stress related gene expression
(Theocharis et al., 2012; Miotto-Vilanova et al., 2016). The enhanced accumulation of
osmolytes by endophytic bacteria results in decreased lipid peroxidation and improved
cell membrane stability (Theocharis et al., 2012).
88
4.1.9. Water relations
4.1.9.1. Leaf relative water content
Drought stress and seed priming significantly affected the leaf relative water
content; barley varieties also differed significantly, during both growing seasons.
Whereas, the interactions between varieties and seed priming as well as varieties and
drought stress were significant during 2014-15 but non-significant during 2015-16.
However, interaction between drought stress and seed priming, and three way interaction
among varieties, drought stress and seed priming was significant, during both years
(Table 4.38). Drought stress decreased leaf relative water content of barley with increase
in its severity. Haider-93 showed higher leaf relative water content than Frontier-87. Seed
priming treatments improved the leaf relative water content of both varieties under each
level of drought stress, as compared to unprimed control. Highest leaf relative water
content was observed by osmopriming and biopriming of Frontier-87 under moderate
drought during 2014-15 and 2015-16 respectively. However, under severe drought,
osmopriming of Haider-93 resulted in highest leaf relative water content, during both
growing seasons (Figures 4.5a,b).
4.1.9.2. Leaf water potential
Leaf water potential was significantly affected by drought and seed priming; the
varieties also differed significantly, during both years. The interaction between varieties
and seed priming was non-significant, during both growing seasons. However, the
interactions between varieties and drought stress, and drought stress and seed priming as
well as three way interaction among varieties, drought stress and seed priming was
significant, during both growing seasons (Table 4.38). Leaf water potential of barley was
decreased with increase in severity of drought stress. Haider-93 maintained higher leaf
water potential than Frontier-87. However, seed priming treatments improved the stress
tolerance by improving the leaf water potential of both varieties under each level of
drought stress, as compared to unprimed control. Under moderate drought, maximum
increase in leaf water potential was noticed by osmopriming of Haider-93, during both
years. Under severe drought, osmopriming and biopriming of Haider-93 led to maximum
improvement in leaf water potential during 2014-15 and 2015-16, respectively (Figures
4.5c,d).
4.1.9.3. Leaf osmotic potential
Drought stress and seed priming significantly affected leaf osmotic potential of
barley; the varieties also significantly differed, during both years. Moreover, the 89
interactions between varieties and drought stress, varieties and seed priming, drought
stress and seed priming as well as three way interaction among varieties, drought stress
and seed priming was significant, during both growing seasons (Table 4.39). Drought
stress decreased the leaf osmotic potential of barley with increase in its severity. Haider-
93 recorded higher leaf osmotic potential than Frontier-87. However, seed priming
treatments improved the stress tolerance by improving the leaf osmotic potential of both
tested varieties under each level of drought stress, as compared to unprimed control. The
greatest improvement in leaf osmotic potential was caused by biopriming and
osmopriming of Haider-93 under moderate and severe drought, respectively, during both
years (Figures 4.6a,b).
4.1.9.4. Leaf pressure potential
The leaf pressure potential was significantly affected by drought stress and seed
priming, during both growing seasons; the barley varieties also differed significantly. The
interactions between varieties and drought stress, and drought stress and seed priming
was non-significant during 2014-15 but significant during 2015-16; while, the interaction
between varieties and seed priming was non-significant, during both years. However, the
interaction among varieties, drought stress and seed priming was significant, during both
growing seasons (Table 4.39). Drought stress decreased leaf pressure potential
proportionally with increase in its severity. Haider-93 maintained higher leaf pressure
potential than Frontier-87. However, leaf pressure potential of both barley varieties was
improved by seed priming treatments under all levels of drought stress, as compared to
unprimed control. The maximum improvement in leaf pressure potential was caused by
biopriming and osmopriming of Haider-93 under moderate and severe drought,
respectively, during both years (Figures 4.6c,d).
4.1.10. Discussion
Drought stress disturbed the water relations of barley varieties and the effect of
drought was increased with increase in its severity. However, Haider-93 better maintained
the water relations under severe drought stress and this is attributed to greater
accumulation of osmolytes. Plants tend to increase the osmolytes accumulation in
response to drought stress to maintain tissue water status through osmotic adjustment
(Farooq et al., 2009a). In present study, seed priming improved the water relations in both
varieties. Improved water relations by seed priming are attributed to osmotic adjustment
through enhanced accumulation of osmolytes and improved root growth. Drought tolerant
plants increase the dry matter partitioning to roots under drought stress to increase the 90
root growth and improve the water uptake from soil (Kavar et al., 2007; Farooq et al.,
2009a). In this study, in osmoprimed plants, aside from osmolytes accumulation the Ca2+
also serves as osmoticum
91
Table 4.38: Analysis of variance for the influence of seed priming on leaf relative water content and leaf water potential of barley under drought stressSOV df Mean sum of square
Leaf relative water content Leaf water potential2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 30.30* 114.23** 11.579** 0.635*
Drought (D) 2 9908.02** 11805.58** 63.066** 89.181**
Priming (T) 3 484.14** 130.67** 1.650** 1.819**
V×D 2 37.82** 12.10ns 1.221** 3.045**
V×T 3 44.53** 17.62ns 0.147ns 0.179ns
D×T 6 51.95** 32.11** 0.304* 0.237*
V×D×T 6 31.22* 40.48** 0.910** 1.018**
Error 72 7.24 7.66 0.130 0.093Total 95
Table 4.39: Analysis of variance for the influence of seed priming on leaf osmotic potential and leaf pressure potential of barley under drought stressSOV df Mean sum of square
Leaf osmotic potential Leaf pressure potential2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 18.842** 14.338** 0.866* 8.912**
Drought (D) 2 158.830** 117.908** 23.528** 3.589**
Priming (T) 3 8.349** 5.652** 2.825** 1.088**
V×D 2 1.752** 1.089** 0.268ns 0.720**
V×T 3 0.497* 0.455* 0.258ns 0.069ns
D×T 6 0.786** 0.799** 0.217ns 0.237**
V×D×T 6 0.917** 0.753** 0.990** 0.645**
Error 72 0.142 0.034 0.182 0.063Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
92
Lea
f rel
ativ
e w
ater
con
tent
(%)
Lea
f wat
er p
oten
tial (
-MPa
)
93
Lea
f osm
otic
pot
entia
l (-M
Pa)
Lea
f pre
ssur
e po
tent
ial (
MPa
)
94
that might also have added its beneficial role in osmotic adjustment (White and Broadley,
2003). In current study, the bioprimed pants improved the water relation traits. The
endophytic bacteria in biopriming, improves the root growth of plants by enhanced
production of auxin while decreasing the ethylene production which results in water
uptake from deeper layers of soil (Santoyo et al., 2016). The inoculation of auxin
producing bacteria improves the root growth and helps to better maintain the water
relations under drought stress by enhanced uptake of water from soil (Vurukonda et al.,
2016). German et al. (2000) reported that inoculation with Azospirillum brasilense Cd
enhanced the specific root length and area, and root projection area as compared to
control in common bean (Phaseolus vulgaris L.) under drought conditions.
4.1.11. Grain nutrient contents
4.1.11.1. Grain zinc content
The grain Zn content was significantly affected by drought stress and seed
priming treatments; barley varieties also differed significantly, during both growing
seasons. The interaction between varieties and drought stress was significant during 2014-
15 but non-significant during 2015-16. Moreover, the interactions between varieties and
seed priming, drought stress and seed priming as well as three way interaction between
varieties, drought stress and seed priming was non-significant, during both years (Table
4.40). The drought stress caused reduction in grain Zn content and with greatest decrease
occurring at severe drought, as compared to control, during both years. Under mild as
well as severe drought the variety Haider-93 exhibited higher grain Zn content than
Frontier-87, during both growing seasons (Tables 4.41a, 4.42a). Across drought and
varieties the biopriming improved the grain Zn content, as compared to unprimed control,
during both years (Tables 4.41b, 4.42b).
4.1.11.2. Grain manganese content
Drought stress and seed priming significantly affected grain Mn content, during
both years. The varieties also significantly differed for grain Mn content. Grain Mn
content was significantly affected by interactive effect of varieties and drought stress,
during both years. However, the interactions between varieties and seed priming, drought
stress and seed priming, and three way interaction between varieties, drought stress and
seed priming was non-significant, during both growing seasons (Table 4.40). The drought
stress caused decrease in grain Mn content and least grain Mn content was recorded at
severe drought, as compared to control, during both years. Under mild as well as severe
drought higher grain Mn content was recorded by variety Haider-93 than Frontier-87 95
(Tables 4.43a, 4.44a). Across drought and varieties the biopriming improved the grain Mn
contents, as compared to unprimed control, during both years (Tables 4.43b, 4.44b).
4.1.11.3. Grain boron content
Grain B content was significantly affected by drought stress and seed priming
treatments; the tested varieties also differed significantly, during both growing seasons.
The interaction between varieties and drought stress was significant, during both growing
seasons. However, the interactions between varieties and seed priming, drought stress and
seed priming as well as three way interaction between varieties, drought stress and seed
priming was non-significant, during both years (Table 4.40). Grain B content was
decreased by drought stress as compared to control with maximum decrease occurring at
severe drought. Under mild drought, higher grain B content was recorded by variety
Haider-93, during both growing seasons. Under severe drought higher grain B content
was exhibited by Haider-93 during 2014-15 and by Frontier-87 during 2015-16 (Tables
4.45a, 4.46a). Across drought and varieties the biopriming improved the grain B contents,
as compared to unprimed control, during both growing seasons (Tables 4.45b, 4.46b).
4.1.12. Discussion
The grain nutrient contents were significantly decreased by drought stress in both
varieties. However, the Haider-93 exhibited more grain Zn, Mn and B contents under
drought stress which is attributed to better water relations and enhanced stress tolerance.
Decreased soil moisture causes a reduction in nutrient uptake due to decreased mobility
of nutrients which results in decreased tissue nutrient concentrations (Fahad et al., 2017).
Drought stress negatively affects the nutrient uptake and accumulation because of
decreased translocation by disturbed water relations and decreased assimilation of
nutrients due to decreased enzyme activity (Farooq et al., 2009a). However, in present
study the biopriming significantly improved the grain Zn, Mn and B contents of barley.
The plant growth promoting endophytic bacteria improves the nutrient uptake in plants by
solubilizing the nutrients in soil by production of organic acids, extra cellular enzymes
and siderophores, and by improving the root growth through increased production of
auxins, cytokinins and gibberellic acid while decreased synthesis of ethylene (Miliute et
al., 2015; Vurukonda et al., 2016). Moreover, increased translocation of nutrients is
essential for accumulation in grains. Thus improved water relations of barley in present
study seems the reason of improved grain Zn, Mn and B contents. Rana et al. (2012)
reported a significant increase in Zn, Mn, Cu and Fe uptake and accumulation in grains of
wheat by inoculation with Bacillus sp., Providencia sp. and Brevundimonas sp.96
Table 4.40: Analysis of variance for the influence of seed priming on grain mineral contents of barley under drought stressSOV df Mean sum of square
Seed zinc content Seed manganese content
Seed boron content
2014-15 2015-16 2014-15 2015-16 2014-15 2015-16Varieties (V) 1 161.02** 57.12** 921.38** 908.97** 0.285** 0.096**
Drought (D) 2 513.65** 761.17** 6252.31** 8299.25** 2.018** 2.440**
Priming (T) 3 66.98** 37.37** 611.42** 764.31** 0.238** 0.156**
V×D 2 24.57** 0.67ns 121.96* 186.66** 0.055** 0.113**
V×T 3 3.30ns 2.40ns 23.96ns 32.74ns 0.002ns 0.005ns
D×T 6 7.09ns 4.54ns 48.78ns 33.90ns 0.008ns 0.009ns
V×D×T 6 3.56ns 1.21ns 57.01ns 36.02ns 0.006ns 0.007ns
Error 72 3.61 3.83 29.78 23.35 0.006 0.005Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.41a: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 41.28 a 37.31 bc 33.97 d 37.52 AF-87 38.34 b 36.62 c 29.83 e 34.93 BMean 39.81 A 36.96 B 31.90 C
Varieties LSD≤0.05 = 0.7728, Drought stress LSD≤0.05 = 0.9465, Varieties × Drought stress LSD≤0.05 = 1.3386
Table 4.41b: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 39.31 35.65 30.76 35.24 CHP 39.88 37.86 32.77 36.84 BOP 36.97 35.64 31.03 34.55 CBP 43.08 38.70 33.05 38.28 AMean 39.81 A 36.96 B 31.90 C
Drought stress LSD≤0.05 = 0.9465, Seed priming LSD≤0.05 = 1.0930
Table 4.42a: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 42.63 a 38.22 c 32.65 e 37.83 AF-87 40.76 b 36.83 d 31.29 e 36.29 BMean 41.70 A 37.52 B 31.97 C
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties LSD≤0.05 = 0.7961, Drought stress LSD≤0.05 = 0.9751, Varieties × Drought stress LSD≤0.05 = 1.3790
97
Table 4.42b: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 40.57 36.30 30.96 35.94 BHP 41.72 37.85 30.99 36.86 BOP 40.63 36.52 32.69 36.61 BBP 43.86 39.41 33.26 38.84 AMean 41.70 A 37.52 B 31.97 C
Drought stress LSD≤0.05 = 0.9751, Seed priming LSD≤0.05 = 1.1259
Table 4.43a: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 122.44 a 117.86 b 95.27 d 111.85 AF-87 118.52 b 107.15 c 91.30 e 105.66 BMean 120.48 A 112.50 B 93.29 C
Varieties LSD≤0.05 = 2.2204, Drought stress LSD≤0.05 = 2.7195, Varieties × Drought stress LSD≤0.05 = 3.8459
Table 4.43b: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 117.69 108.94 90.11 105.58 CHP 119.43 113.31 96.26 109.67 BOP 113.98 109.13 89.73 104.28 CBP 130.81 118.64 97.05 115.50 AMean 120.48 A 112.50 B 93.29 C
Drought stress LSD≤0.05 = 2.7195, Seed priming LSD≤0.05 = 3.1402
Table 4.44a: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 123.41 a 115.19 b 94.98 c 111.19 AF-87 116.31 b 114.27 b 84.54 d 105.04 BMean 119.86 A 114.73 B 89.76 C
Varieties LSD≤0.05 = 1.9662, Drought stress LSD≤0.05 = 2.4081, Varieties × Drought stress LSD≤0.05 = 3.4056
Table 4.44b: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 116.63 110.65 86.68 104.65 CHP 121.30 117.03 91.32 109.88 BOP 111.66 110.30 86.07 102.68 CBP 129.84 120.94 94.95 115.25 AMean 119.86 A 114.73 B 89.76 C
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Drought stress LSD≤0.05 = 2.4081, Seed priming LSD≤0.05 = 2.7807
98
Table 4.45a: Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 1.86 a 1.81 b 1.37 d 1.68 AF-87 1.79 b 1.60 c 1.32 e 1.57 BMean 1.83 A 1.70 B 1.34 C
Varieties LSD≤0.05 = 0.0302, Drought stress LSD≤0.05 = 0.0370, Varieties × Drought stress LSD≤0.05 = 0.0523
Table 4.45b: Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 1.79 1.65 1.31 1.58 CHP 1.82 1.77 1.40 1.66 BOP 1.72 1.59 1.23 1.51 DBP 1.99 1.80 1.44 1.74 AMean 1.83 A 1.70 B 1.34 C
Drought stress LSD≤0.05 = 0.0370, Seed priming LSD≤0.05 = 0.0427
Table 4.46a: Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 1.87 a 1.75 b 1.30 d 1.64 AF-87 1.85 a 1.56 c 1.33 d 1.58 BMean 1.86 A 1.65 B 1.31 C
Varieties LSD≤0.05 = 0.0285, Drought stress LSD≤0.05 = 0.0349, Varieties × Drought stress LSD≤0.05 = 0.0494
Table 4.46b: Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 1.81 1.59 1.27 1.56 CHP 1.85 1.65 1.37 1.62 BOP 1.77 1.62 1.22 1.54 CBP 2.00 1.76 1.39 1.72 AMean 1.86 A 1.65 B 1.31 C
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Drought stress LSD≤0.05 = 0.0349, Seed priming LSD≤0.05 = 0.0403
99
4.2. Influence of seed priming in improving the salt resistance in barley4.2.1. Stand establishment
4.2.1.1. Final emergence percentage
Final emergence percentage was significantly affected by seed priming
treatments; however, tested barley varieties did not differ significantly for final
emergence percentage, during both growing seasons. Likewise, the interactive effect of
variety and seed priming was non-significant, during both years (Table 4.47). Final
emergence percentage was improved by seed priming as compared to unprimed control
with highest emergence percentage caused by osmopriming and it was followed by
biopriming, during both years (Table 4.48).
4.2.1.2. Time taken to 50% emergence
Seed priming significantly affected the time taken to 50% emergence, during both
growing seasons. However, barley varieties did not differ significantly for time taken to
50% emergence, during both years. The interactive effect of varieties and seed priming
was also non-significant for time taken to 50% emergence, during both years (Table
4.47). Seed priming decreased the time taken to 50% emergence as compared to
unprimed control and the order of decrease was osmopriming < biopriming <
hydropriming < control (Table 4.49).
4.2.1.3. Mean emergence time
Seed priming treatments significantly affected the mean emergence time; the
barley varieties did not differ significantly for mean emergence time, during both growing
seasons. The interactive effect of varieties and seed priming was also non-significant for
mean emergence time, during both growing seasons (Table 4.50). The mean emergence
time was reduced by seed priming treatments as compared to unprimed control. The order
of decrease in mean emergence time was osmopriming < biopriming < hydropriming <
control during 2014-15, while osmopriming < hydropriming < biopriming < control
during 2015-16 (Table 4.51).
4.2.1.4. Emergence index
Emergence index was significantly affected by seed priming treatments, during
both growing seasons. However, tested barley varieties did not differ significantly for
emergence index, during both years. Likewise, the interaction between variety and seed
priming was non-significant for emergence index, during both years (Table 4.50). The
emergence index was enhanced by seed priming as compared to unprimed control.
100
Maximum improvement was caused by osmopriming followed by biopriming, during
both
101
Table 4.47: Analysis of variance for the influence of seed priming on final emergence percentage and time taken to 50% emergence of barley SOV df Mean sum of square
Final emergence percentage Time taken to 50% emergence
2014-15 2015-16 2014-15 2015-16Varieties (V) 1 16.088ns 16.700ns 0.022ns 0.025ns
Priming (T) 3 85.493* 174.627** 1.227** 0.482*
V×T 3 21.046ns 6.784ns 0.028ns 0.170ns
Error 16 25.918 31.477 0.112 0.139Total 23
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.48: Influence of seed priming on final emergence (%) of barleyTreatments 2014-15 2015-16
H-93 F-87 Mean H-93 F-87 MeanControl 88.89 86.67 87.78 B 82.22 84.45 83.33 BHP 93.33 86.78 90.05 B 86.67 91.11 88.89 ABOP 95.55 97.78 96.67 A 95.55 95.55 95.55 ABP 91.11 91.11 91.11 AB 93.33 93.33 93.33 AMean 92.22 90.58 89.44 91.11
Seed priming LSD≤0.05 = 6.2309 (2014-15) and 6.8668 (2015-16)
Table 4.49: Influence of seed priming on time taken to 50% emergence (days) of barleyTreatments 2014-15 2015-16
H-93 F-87 Mean H-93 F-87 MeanControl 4.33 4.59 4.46 A 4.64 5.20 4.92 AHP 3.89 3.85 3.87 B 4.52 4.39 4.45 BOP 3.40 3.44 3.42 C 4.27 4.26 4.26 BBP 3.63 3.61 3.62 BC 4.50 4.33 4.42 BMean 3.81 3.87 4.48 4.55
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Seed priming LSD≤0.05 = 0.4096 (2014-15) and 0.4568 (2015-16)
Table 4.50: Analysis of variance for the influence of seed priming on mean emergence time and emergence index of barley SOV df Mean sum of square
Mean emergence time Emergence index2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 0.038ns 0.025ns 0.048ns 0.021ns
Priming (T) 3 0.559** 0.384* 0.624** 0.672**
V×T 3 0.013ns 0.081ns 0.046ns 0.016ns
Error 16 0.077 0.085 0.070 0.034Total 23
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
102
Table 4.51: Influence of seed priming on mean emergence time (days) of barleyTreatments 2014-15 2015-16
H-93 F-87 Mean H-93 F-87 MeanControl 4.72 4.87 4.80 A 5.10 5.34 5.22 AHP 4.36 4.47 4.42 B 4.67 4.90 4.79 BOP 4.02 4.13 4.08 B 4.60 4.63 4.62 BBP 4.29 4.23 4.26 B 5.00 4.75 4.88 ABMean 4.35 4.43 4.84 4.91
Seed priming LSD≤0.05 = 0.3400 (2014-15) and 0.3574 (2015-16)
Table 4.52: Influence of seed priming on emergence index of barleyTreatments 2014-15 2015-16
H-93 F-87 Mean H-93 F-87 MeanControl 3.03 2.90 2.97 C 2.69 2.65 2.67 CHP 3.44 3.13 3.29 BC 3.04 3.15 3.09 BOP 3.70 3.78 3.74 A 3.48 3.46 3.47 ABP 3.42 3.43 3.42 AB 3.13 3.31 3.22 BMean 3.40 3.31 3.08 3.14
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Seed priming LSD≤0.05 = 0.3243 (2014-15) and 0.2270 (2015-16)
103
years (Table 4.52).
4.2.2. Discussion
Emergence traits of barley varieties were improved by seed priming traits as
compared to unprimed control. Final emergence percentage and seed index was improved
while mean emergence time and time for 50% emergence was decreased by seed priming.
This may be due to time reduced for metabolism by controlled hydration of seed. Seed
priming allows the germination metabolism to occur without actual germination through
controlled hydration (Farooq et al., 2006a). Seed priming enhances activity of hydrolytic
enzymes and improves the carbohydrate metabolism in seeds which makes the food
reserves available for developing embryo (Farooq et al., 2009b). Moreover, improved
germination by seed priming is associated with exalted activity of α-amylase, β-amylase,
and dehydrogenase in root system and catalase in germinating seeds (He et al., 2002).
Moreover, seed priming enhances de novo synthesis of α-amylase (Lee and Kim, 2000).
In present study improved emergence by osmopriming might be due to the Ca2+ which is
structural part of cell wall structure, cell membrane integrity and permeability, and
regulates cell division and elongation (Hepler, 2005). The decreased cell membrane
leakage and improved cell membrane stability by Ca2+ leads to better germination with
increased germination time and seedling vigour index (Posmyk et al., 2001; Ruan et al.,
2002a, b). In current study better emergence by biopriming may be due to endophytic
bacteria which enhances seed germination by exalting water absorption, producing
cellular enzymes viz. amylase and protease and promotes the degradation of sucrose,
proteins and lipids resulting in better and earlier germination (Zhu et al., 2017).
4.2.3. Agronomic attributes
4.2.3.1. Plant height
Plant height was significantly affected by salinity and seed priming; barley
varieties also differed significantly for plant height, during both growing seasons. The
interaction between varieties and seed priming was significant during 2014-15 and non-
significant during 2015-16. The interactions between varieties and salinity, salinity and
seed priming as well as three way interaction among varieties, salinity and seed priming
was significant, during both years (Table 4.53). Salinity decreased the plant height and it
was proportional to its severity. Taller plants were produced by Frontier-87 than Haider-
93. Seed priming increased the plant height of tested barley varieties at each level of salt
stress, as compared to unprimed control. Under moderate salinity, biopriming of Frontier-
87 and osmopriming of Haider-93 produced the tallest plants during 2014-15 and 2015-104
16, respectively. However, under severe salinity, the tallest plants were produced by
osmopriming and biopriming of Haider-93 during 2014-15 and 2015-16, respectively
(Tables 4.54, 4.55).
4.2.3.2. Leaf area
Salinity and seed priming significantly affected the leaf area; barley varieties also
differed significantly for leaf area, during both growing seasons. The interaction between
varieties and seed priming was non-significant, during both years. However, the
interactions between varieties and salinity, salinity and seed priming, and three way
interaction among varieties, salinity and seed priming was significant, during both
growing seasons (Table 4.53). There was a progressive decrease in leaf area with increase
in severity of salt stress. Higher leaf area was produced by Frontier-87 than Haider-93.
Seed priming enhanced the leaf area of both varieties at all levels of salt stress, as
compared to unprimed control. Under moderate salinity, biopriming of Haider-93 and
osmopriming of Fronteirs-87 produced maximum leaf area during 2014-15 and 2015-16,
respectively. However, under severe salinity, the greatest increase in leaf area was caused
by biopriming of Frontier-87 during years (Tables 4.56, 4.57).
4.2.3.3. Total number of tillers per pot
There was a significant effect of salinity and seed priming on total number of
tillers; however, selected barley varieties did not differ significantly for total number of
tillers, during both years. The interactions between varieties and salinity, and varieties
and seed priming was non-significant during 2014-15 but significant during 2015-16.
However, the interaction between salinity and seed priming as well as three way
interaction among varieties, salinity and seed priming was significant, during both
growing seasons (Table 4.58). Total number of tillers was decreased with increase in
severity of salt stress. Haider-93 recorded higher number of tillers than Frontier-87. Seed
priming improved the total number of tillers of both barley varieties at all levels of
salinity, as compared to unprimed control. Under moderate salinity, maximum number of
tillers per pot were recorded by osmopriming of Frontier-87, during both years. Under
severe salinity, highest number of tillers was produced by osmopriming of Haider-93,
during both years (Tables 4.59, 4.60).
4.2.3.4. Number of productive tillers per pot
The number of productive tillers was significantly affected by salinity and seed
priming; however, the varieties did not differ significantly, during both years. The
interactions between varieties and salinity, and varieties and seed priming were non-105
significant during 2014-15 and significant during 2015-16. However, the interaction
between salinity and seed priming as well as three way interaction among varieties,
salinity
106
Table 4.53: Analysis of variance for the influence of seed priming on plant growth of barley under salinitySOV df Mean sum of square
Plant height Leaf area2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 573.01** 561.25** 38036.5** 3466.0**
Salinity (S) 2 2553.82** 3035.78** 361062.0** 303931.7**
Priming (T) 3 186.92** 69.28** 13956.3** 27489.2**
V×S 2 41.88** 153.00** 25629.0** 1570.3*
V×T 3 70.89** 9.19ns 1068.1ns 982.7ns
S×T 6 23.29** 91.61** 1372.3* 6107.7**
V×S×T 6 14.47** 60.11** 4097.1* 2109.4**
Error 72 4.61 6.05 523.5 432.2Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.54: Influence of seed priming on plant height (cm) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 65.13 fg 77.80 c 58.86 j-m 62.61 ghi 52.40 n 58.55 lmHP 73.05 d 78.80 bc 61.84 hij 67.28 ef 57.64 m 59.48 j-mOP 80.95 ab 80.84 ab 61.41 i-l 64.82 fgh 63.66 ghi 61.07 i-lBP 72.83 d 82.37 a 61.57 ijk 70.05 de 58.73 klm 63.05 ghi
Varieties × Salinity × Seed priming LSD≤0.05 = 3.0253
Table 4.55: Influence of seed priming on plant height (cm) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 71.17 e 76.54 bc 69.90 e 65.16 f 44.39 i 58.35 gHP 72.64 de 79.20 ab 65.02 f 64.79 f 51.14 h 64.52 fOP 75.24 cd 82.42 a 70.29 e 69.74 e 51.12 h 56.75 gBP 70.73 e 77.85 bc 65.16 f 70.13 e 62.46 f 61.83 f
Varieties × Salinity × Seed priming LSD≤0.05 = 3.4680
Table 4.56: Influence of seed priming on leaf area (cm2) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 496.99 cd 579.52 b 439.18 fgh 426.55 gh 291.69 m 311.91 lmHP 511.59 cd 585.11 b 412.26 hi 444.32 fgh 324.33 l 339.72 klOP 507.35 cd 633.10 a 463.93 ef 453.74 efg 387.43 ij 363.02 jkBP 520.90 c 644.46 a 481.73 de 432.33 fgh 331.14 kl 432.50 fgh
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 32.252
107
Table 4.57: Influence of seed priming on leaf area (cm2) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 495.20 efg 518.98 def 411.32 j 425.63 ij 324.78 m 314.24 mHP 537.53 cd 523.81 cde 451.84 hi 440.60 hij 321.74 m 341.06 lmOP 552.12 c 533.62 cd 492.76 fg 513.39 def 332.08 m 365.10 klBP 585.27 c 636.83 a 468.51 gh 439.47 hij 380.55 k 445.17 hi
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 29.303
Table 4.58: Analysis of variance for the influence of seed priming on number of total and productive tillers of barley under salinity SOV df Mean sum of square
Total No. of tillers per pot No. of productive tillers per pot
2014-15 2015-16 2014-15 2015-16Varieties (V) 1 0.336ns 0.055ns 0.274ns 0.046ns
Salinity (S) 2 46.517** 30.607** 54.629** 42.388**
Priming (T) 3 14.296** 7.111** 7.065** 3.085**
V×S 2 0.538ns 3.234** 0.244ns 1.563**
V×T 3 0.034ns 1.315* 0.045ns 0.741*
S×T 6 1.114* 1.455* 0.756** 0.909**
V×S×T 6 1.405** 1.659** 0.828** 0.880*
Error 72 0.246 0.237 0.127 0.120Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.59: Influence of seed priming on total number of tillers per pot of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 13.37 g-j 13.41 ghi 13.19 h-k 12.70 jkl 11.19 n 10.97 nHP 14.23 c-f 14.20 def 13.84 e-h 14.40 b-e 12.65 kl 11.93 mOP 13.90 efg 14.48 b-e 14.90 abc 15.49 a 13.59 fgh 12.22 lmBP 15.02 ab 14.84 a-d 15.47 a 14.61 bcd 12.05 lm 12.74 i-l
Varieties × Salinity × Seed priming LSD≤0.05 = 0.6997
Table 4.60: Influence of seed priming on total number of tillers per pot of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 13.77 efg 13.81 efg 13.33 fgh 13.34 fgh 12.31 i 11.41 jHP 14.86 bc 14.62 bcd 13.98 def 15.13 ab 13.16 gh 12.42 iOP 12.88 hi 14.94 bc 14.45 b-e 15.64 a 13.95 def 12.82 hiBP 15.07 ab 14.38 cde 15.00 abc 14.76 bc 12.66 hi 12.74 hi
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 0.6862
108
and seed priming was significant, during both growing seasons (Table 4.58). Number of
productive tillers was decreased with increase in severity of salt stress. Haider-93
produced higher number of productive tillers than Frontier-87. Moreover, seed priming
improved the number of productive tillers of both barley varieties at each level of salinity,
as compared to unprimed control. Under moderate salinity, maximum number of
productive tillers was produced by biopriming of Haider-93 during 2014-15 and
osmopriming of Frontier-87 during 2015-16. Under severe salinity, highest number of
productive tillers was produced by osmopriming of Haider-93, during both years (Tables
4.61, 4.62).
4.2.3.5. Spike length
Spike length was significantly affected by salinity and seed priming; while, the
tested varieties also differed for spike length, during both years. The interaction between
varieties and seed priming was significant during 2014-15 while non-significant during
2015-16. The spike length was not affected significantly by interaction between varieties
and salinity, during both years. Interaction between salinity and seed priming, and three
way interaction among varieties, salinity and seed priming were significant, during both
years (Table 4.63). There was a progressive decrease in spike length with increase in
severity of salinity. Longer spikes were produced by Haider-93 than Frontier-87.
However, spike length of both varieties was enhanced by seed priming treatments under
all levels of salt stress, as compared to unprimed control. Under moderate stress,
osmopriming and biopriming of Frontier-87 caused maximum increase spike length
during 2014-15 and 2015-16, respectively. Under severe salinity, biopriming of Haider-
93 produced the longest spikes, during both years (Tables 4.64, 4.65).
4.2.3.6. Number of spikelets per spike
The number of spikelets per spike was significantly affected by salinity and seed
priming, during both years. The varieties did not differ significantly during 2014-15 while
significantly differed during 2015-16. The interaction between varieties and salinity was
non-significant during 2014-15 but significant during 2015-16. The interactive effect of
varieties and seed priming, salinity and seed priming, as well as three way interaction
among varieties, salinity and seed priming was significant, during both growing seasons
(Table 4.63). Salinity decreased the number of spikelets per spike and it was proportional
to its severity. More number of spikelets per spike was produced by Haider-93 than
Frontier-87. The number of spikelets per spike of tested barley varieties were improved
by seed priming treatments under all levels of salt stress, as compared to unprimed 109
control. Under moderate salinity, osmopriming of Frontier-87 and Haider-93 caused
maximum increase in number of spikelets per spike during 2014-15 and 2015-16,
respectively. However, under severe salinity, biopriming of Haider-93 produced
maximum number of spikelets per spike, during both growing seasons (Tables 4.66,
4.67).
4.2.3.7. Number of grains per spike
Salinity and seed priming significantly affected the grains per spike of barley;
tested barley varieties also differed for grains per spike, during both growing seasons.
Interaction between variety and salinity was significant, during both years. However, the
interactions between variety and seed priming, and salinity and seed priming were
significant during 2014-15 but non-significant during 2015-16. The three way interaction
among variety, salinity and seed priming was significant for grains per spike, during both
years (Table 4.68). Salinity decreased the number of grains per spike and it was
proportional to its severity. Higher number of grains per spike was produced by Haider-
93 than Frontier-87. Seed priming enhanced the production of number of grains per spike
of both barley varieties at all levels of salinity, as compared to unprimed control. Under
moderate salinity, biopriming of Fronteirs-87 and Haider-93 produced maximum number
of grains per spike during 2014-15 and 2015-16, respectively. Under severe salinity,
biopriming of Haider-93 caused maximum increase in number of grains per spike during
both year. However, during 2015-16 osmopriming of Haider-93 produced similar number
of grains per spike (Tables 4.69, 4.70).
4.2.3.8. 100-grain weight
The 100-grain weight was significantly affected by salinity and seed priming
during years. The tested barley varieties also differed for 100-grain weight, during both
years. The interaction between varieties and salinity was non-significant during 2014-15
but significant during 2015-16. Interaction between varieties and seed priming was
significant during 2014-15 and non-significant during 2015-16. The interaction between
salinity and seed priming, and three way interaction among varieties, salinity and seed
priming were significant, during both years (Table 4.68). The 100-grain weight was
decreased with increase in severity of salt stress. Haider-93 produced higher 100-grain
weight than Frontier-87. Furthermore, seed priming improved the 100-grain weight of
both varieties at each level of salinity, as compared to unprimed control. Under mild
salinity, biopriming and osmopriming of Haider-93 had maximum increase in 100-grain
weight during 2014-15 and 2015-16, respectively. However, under severe salinity, the 110
greatest improvement in 100-grain weight was recorded by osmopriming of Haider-93,
during both years (Tables 4.71, 4.72).
Table 4.61: Influence of seed priming on number of productive tillers per pot of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 10.29 de 10.31 de 9.42 fg 9.07 gh 7.67 kl 7.52 lHP 10.78 cd 10.75 cd 9.88 ef 10.29 de 8.61 hij 8.12 jkOP 10.45 cd 10.89 bc 10.53 cd 10.95 bc 9.25 g 8.31 ijBP 11.47 a 11.33 ab 11.46 a 10.51 cd 8.25 ij 8.73 hi
Varieties × Salinity × Seed priming LSD≤0.05 = 0.5026
Table 4.62: Influence of seed priming on number of productive tillers per pot of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 10.59 cd 10.62 cd 9.52 fg 9.53 fg 8.43 i 7.81 jHP 11.26 ab 11.08 abc 9.98 ef 10.80 bc 8.95 h 8.45 iOP 9.69 fg 11.23 ab 10.22 de 11.06 abc 9.49 g 8.72 hiBP 11.51 a 10.98 bc 10.79 bc 10.62 cd 8.67 hi 8.73 hi
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 0.4888
Table 4.63: Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under salinity SOV df Mean sum of square
Spike length No. of spikelets per spike2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 2.548** 6.652** 0.158ns 5.202**
Salinity (S) 2 18.301** 18.712** 67.060** 87.847**
Priming (T) 3 2.506** 3.338* 15.185** 10.521**
V×S 2 0.035ns 0.145ns 0.236ns 1.742**
V×T 3 2.626** 0.244ns 3.970** 0.640*
S×T 6 1.110** 1.115** 0.987* 1.000**
V×S×T 6 0.365* 0.885** 1.301** 1.234**
Error 72 0.077 0.157 0.205 0.197Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.64: Influence of seed priming on spike length (cm) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 7.64 cde 7.14 fg 7.48 ef 6.39 ij 6.26 ij 6.03 jHP 7.93 bcd 7.94 bc 7.55 de 8.14 b 6.17 ij 6.31 ijOP 7.89 bcd 7.69 cde 7.74 cde 8.21 b 6.52 hi 6.80 ghBP 8.95 a 8.24 b 7.97 bc 6.49 hi 7.37 ef 6.17 ij
111
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 0.3922
112
Table 4.65: Influence of seed priming on spike length (cm) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 8.09 bc 7.63 c-f 7.73 b-f 6.41 hi 5.62 j 5.72 jHP 8.07 bcd 7.52 def 7.91 b-e 6.91 gh 7.30 fg 6.62 hOP 8.13 abc 8.13 abc 8.08 bcd 7.31 fg 6.87 gh 6.02 ijBP 8.25 ab 7.77 b-f 8.08 bcd 8.69 a 7.37 efg 6.47 hi
Varieties × Salinity × Seed priming LSD≤0.05 = 0.5579
Table 4.66: Influence of seed priming on number of spikelets per spike of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 13.37 c 13.03 cd 11.73 fg 11.33 gh 10.38 i 9.81 iHP 13.37 c 13.20 cd 12.60 de 13.27 c 11.08 h 11.08 hOP 13.54 bc 15.34 a 13.54 bc 13.54 bc 11.08 h 12.03 efBP 15.94 a 14.14 b 13.20 cd 13.37 c 12.37 ef 11.08 h
Varieties × Salinity × Seed priming LSD≤0.05 = 0.6375
Table 4.67: Influence of seed priming on number of spikelets per spike of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 13.50 cd 13.16 def 11.88 g 11.54 gh 9.70 jk 9.37 kHP 13.76 bcd 13.33 cde 12.60 f 11.64 gh 10.14 j 10.80 iOP 15.66 a 13.42 cd 13.82 bc 13.20 c-f 10.80 i 10.80 iBP 14.37 b 13.42 cd 12.75 ef 13.37 cde 11.73 g 11.05 hi
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 0.6250
Table 4.68: Analysis of variance for the influence of seed priming on number of grains per spike and 100-grain weight of barley under salinity SOV df Mean sum of square
No. of grains per spike 100-grain weight2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 26.660** 82.381** 1.044** 0.158**
Salinity (S) 2 691.712** 850.569** 5.445** 14.597**
Priming (T) 3 54.320** 57.804** 0.946** 0.779**
V×S 2 4.145* 11.312** 0.012ns 0.381**
V×T 3 3.558* 1.390ns 0.080** 0.026ns
S×T 6 2.835* 0.861ns 0.065** 0.084**
V×S×T 6 6.047** 6.179** 0.085** 0.079**
Error 72 1.040 1.213 0.008 0.015Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
113
Table 4.69: Influence of seed priming on number of grains per spike of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 34.49 c 32.88 d 30.33 fg 27.45 ij 24.63 lm 23.85 mHP 35.79 bc 32.88 d 30.77 ef 30.98 ef 27.21 ij 26.08 jkOP 37.70 a 35.89 bc 32.09 de 31.44 ef 25.36 kl 27.96 hiBP 38.10 a 36.92 ab 31.87 de 32.15 de 28.98 gh 26.19 jk
Varieties × Salinity × Seed priming LSD≤0.05 = 1.4373
Table 4.70: Influence of seed priming on number of grains per spike of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 32.84 d 30.97 ef 28.57 gh 27.02 h 21.53 l 21.42 lHP 33.63 cd 32.30 de 31.00 ef 25.78 ij 22.56 kl 23.26 kOP 35.52 b 34.58 bc 30.97 ef 28.55 gh 25.47 ij 22.94 klBP 37.35 a 33.00 d 32.18 de 29.84 fg 25.48 ij 25.22 j
Varieties × Salinity × Seed priming LSD≤0.05 = 1.5526
Table 4.71: Influence of seed priming on 100-grain weight (g) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 3.21 cd 3.06 ef 2.82 h 2.67 i 2.38 j 2.19 kHP 3.42 b 3.02 efg 2.97 fg 2.68 i 2.83 h 2.44 jOP 3.49 b 3.69 a 3.12 de 3.08 ef 2.90 gh 2.49 jBP 3.81 a 3.45 b 3.28 c 2.96 fg 2.67 i 2.65 i
Varieties × Salinity × Seed priming LSD≤0.05 = 0.1252
Table 4.72: Influence of seed priming on 100-grain weight (g) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 3.46 c 3.50 c 2.92 fg 3.01 ef 2.47 ijk 2.33 klHP 3.60 c 3.88 b 2.77 gh 3.18 d 2.45 jk 2.23 lOP 3.80 b 4.35 a 3.26 d 3.18 d 2.72 h 2.55 ijBP 3.92 b 4.19 a 3.15 de 3.16 de 2.63 hi 2.55 ij
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 0.1699
114
4.2.3.9. Grain yield per pot
A significant effect of salinity and seed priming on grain yield was noticed, during
both years; the barley varieties also differed significantly for grain yield, during both
growing seasons. The interaction between varieties and salinity was non-significant
during 2014-15 while significant during 2015-16. However, the interactions between
varieties and seed priming, salinity and seed priming, and three way interaction among
varieties, salinity and seed priming was significant, during both years (Table 4.73). The
grain yield was decreased with increase in severity of salt stress. Higher grain yield was
produced by Haider-93 than Frontier-87. Grain yield of both varieties was improved by
seed priming treatments under all levels of salinity, as compared to unprimed control.
Under moderate salinity, biopriming of Haider-93 exhibited greatest improvement in
grain yield, during both years. Under severe salinity, osmopriming of Haider-93 caused
maximum improvement in grain yield, during both years (Tables 4.74, 4.75).
4.2.3.10. Biological yield per pot
Biological yield was significantly affected by salinity and seed priming, during
both growing seasons; however, the barley varieties significantly differed during 2014-15
but did not differ significantly during 2015-16. The interactions between varieties and
salinity, and salinity and seed priming were significant during 2014-15 but non-
significant during 2015-16. The interaction between varieties and salinity, and three way
interaction among varieties, salinity and seed priming were significant, during both years
(Table 4.73). Salinity decreased the biological yield and it was proportional to its severity.
Under control and moderate salinity higher biological yield was exhibited by Frontier-87
while under severe salinity Haider-93 gave higher biological yield. Seed priming
enhanced the biological yield of both tested barley varieties at all levels of salt stress, as
compared to unprimed control. Under moderate salinity, the greatest increase in
biological yield was recorded by osmopriming of Frontier-87 and biopriming of Haider-
93 during 2014-15 and 2015-16, respectively. However, under severe salinity, biopriming
of Frontier-87 and osmopriming of Haider-93 exhibited highest biological yield, during
2014-15 and 2015-16, respectively (Tables 4.76, 4.77).
4.2.3.11. Harvest index
There was a significant effect of salinity and seed priming on harvest index; the
selected barley varieties also differed for harvest index, during both years. The interaction
between varieties and salinity was non-significant during 2014-15 and significant during
2015-16. The interactions between varieties and seed priming as well as salinity and seed 115
priming were significant during 2014-15 but non-significant during 2015-16. The three
way interaction among varieties, salinity and seed priming was significant, during both
growing seasons (Table 4.73). Harvest index was decreased with increase in severity of
salt stress. Haider-93 recorded higher harvest index than Frontier-87. Seed priming
improved the harvest index of both barley varieties at all levels of salinity, as compared to
unprimed control. Under moderate salinity, highest harvest index was noticed by
osmopriming of Haider-93, during both years; while, under severe salinity, osmopriming
and biopriming of Haider-93 greatest increase in harvest index of barley during 2014-15
and 2015-16, respectively (Tables 4.78, 4.79).
4.2.4. Discussion
Salinity caused a reduction in growth and development of both barley varieties;
nonetheless, seed priming improved the plant height and leaf area. Deccarese in growth
and development by salt stress is attributed to osmotic stress (Farooq et al., 2015), ion
toxicity and oxidative stress induced by salinity (Munns and Tester, 2008). In present
study, improved growth by seed priming might be due to early head start and improved
stress tolerance by enhanced osmolytes accumulation and activity of antioxidants under
stressed conditions (Chen and Arora, 2013). Moreover, osmopriming enhances gene
expression and transcription factors for osmolytes, antioxidants, carbohydrate
metabolism, nitrogen metabolism, cell development and response to oxidative stress
under stress conditions (Hussain et al., 2016). Moreover, Ca2+ used in osmopriming in
present study, is the structural component of cell wall, regulates cell membrane integrity
and cell division by acting as the secondary messenger in signaling pathway that regulates
calmodulin like proteins and modulates growth processes (White and Broadley, 2003;
Hepler, 2005; Sarwat et al., 2013). In biopriming, endophytic bacteria improved the plant
growth by enhancing water and nutrient uptake which may be due to better root growth
and enhanced synthesis of growth promoting hormones i.e. auxin, gibberellic acid and
cytokinins while decreasing the ethylene production by producing ACC deaminase
(Santoyo et al., 2016).
Yield and related traits of both barley varieties were decreased by salt stress while
Haider-93 performed better in this regard. However, seed priming improved the grain
yield and harvest index by improving the spike length, number of spikelets per spike, and
number of grains and grain weight of both varieties. Salinity adversely affects the pollen
viability which decreases the number of seeds per plant and plant yield (Gul and Ahmad,
2006). Moreover, decreased photosynthesis and assimilate partitioning by salinity 116
decreases grain weight and grain yield (Cruz et al., 2017). However, in this study,
improved spike length
117
Table 4.73: Analysis of variance for the influence of seed priming on grain yield, biological yield and harvest index of barley under salinitySOV df Mean sum of square
Grain yield Biological yield Harvest index2014-15 2015-16 2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 7.031** 1.197** 3.648* 1.149ns 185.148** 53.000**
Salinity (S) 2 148.015** 209.824** 599.284** 817.033** 449.178** 714.016**
Priming (T) 3 14.941** 7.976** 41.198** 16.538** 58.858** 48.122**
V×S 2 0.177ns 0.978** 12.792** 13.176** 4.102ns 14.911*
V×T 3 1.398** 0.793** 5.154** 2.766ns 14.445** 1.926ns
S×T 6 0.993** 0.883** 2.641** 2.695ns 5.080* 2.939ns
V×S×T 6 0.997** 0.611** 7.600** 6.585** 9.831** 12.383**
Error 72 0.118 0.088 0.721 1.228 1.906 1.465Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.74: Influence of seed priming on grain yield (g per pot) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 8.53 e 8.65 e 7.05 g 6.83 g 5.13 jk 4.28 lHP 9.62 c 8.68 e 8.05 f 7.18 g 5.88 hi 5.01 kOP 9.72 c 10.46 b 8.82 de 8.93 de 6.09 h 5.33 jkBP 11.73 a 9.75 c 9.28 cd 8.63 e 5.88 hi 5.55 ij
Varieties × Salinity × Seed priming LSD≤0.05 = 0.4839
Table 4.75: Influence of seed priming on grain yield (g per pot) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 8.34 e 8.00 ef 6.47 ij 6.19 j 4.09 m 3.63 nHP 8.85 d 9.33 c 6.75 hi 6.74 hi 4.27 lm 3.97 mnOP 9.28 c 10.62 a 7.36 g 6.88 hi 4.85 k 4.23 mBP 10.62 a 9.85 b 7.91 f 7.09 gh 4.67 kl 4.24 m
Varieties × Salinity × Seed priming LSD≤0.05 = 0.4175
Table 4.76: Influence of seed priming on biological yield (g per pot) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 24.62 gh 26.66 cd 23.28 i 23.60 hi 18.38 kl 16.56 mHP 25.03 efg 28.67 ab 24.78 fgh 26.64 cd 20.11 j 17.99 lOP 25.98 de 27.77 bc 25.95 def 28.39 b 20.12 j 19.16 jklBP 29.65 a 27.51 bc 27.81 bc 26.73 cd 19.50 jk 20.22 j
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 1.1972
118
Table 4.77: Influence of seed priming on biological yield (g per pot) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 23.77 def 24.95 bcd 21.43 gh 21.45 gh 15.61 jkl 14.28 lHP 24.84 bcd 25.47 b 20.49 h 24.80 bcd 16.96 ij 14.93 klOP 25.41 bc 27.62 a 21.40 g 22.48 efg 17.18 i 15.49 jklBP 27.43 a 27.24 a 23.90 cde 22.34 fg 16.26 ijk 16.25 ijk
Varieties × Salinity × Seed priming LSD≤0.05 = 1.5622
Table 4.78: Influence of seed priming on harvest index (%) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 34.68 cd 32.47 ef 30.27 gh 28.92 hi 27.91 ij 25.82 kHP 38.43 ab 30.29 gh 32.50 ef 26.97 jk 29.21 hi 27.88 ijOP 37.42 b 37.68 ab 33.98 cde 31.47 fg 30.24 gh 27.82 ijBP 39.59 a 35.44 c 33.47 de 32.35 ef 30.18 gh 27.43 ijk
Varieties × Salinity × Seed priming LSD≤0.05 = 1.9461
Table 4.79: Influence of seed priming on harvest index (%) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity
H-93 F-87 H-93 F-87 H-93 F-87Control 35.07 bc 32.17 ef 30.21 ghi 28.89 hij 26.22 kl 25.42 lHP 35.67 bc 36.63 b 32.98 de 27.22 jk 25.18 l 26.63 klOP 36.55 b 38.46 a 34.37 cd 30.59 fgh 28.34 j 27.34 jkBP 38.75 a 36.19 b 33.12 de 31.73 efg 28.76 ij 26.10 kl
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 1.7060
119
by seed priming resulted in improved number of spikelets and grains ultimately
improving the grain yield. Moreover, the grain weight was improved by seed priming
treatments which contributed to improved grain yield and harvest index. The improved
osmolytes accumulation, tissue water status and better protection of cellular membranes
from lipid peroxidation by seed priming is attributed to improved number of grains and
grain weight under salinity (Tabassum et al., 2017).
In present study, the yield improvement by osmopriming, is attributed to
improved osmolytes accumulation, tissue water status, cell membrane stability and
decreased lipid peroxidation. The Ca2+, used in osmopriming, is involved in cell
membrane stability which might have improved the pollen viability and number of grains.
Moreover, Ca2+ improves the photosynthesis, decreases ROS activity and lipid
peroxidation by enhancing osmolytes accumulation and activity of antioxidants ultimately
improving the number of grains, grain weight and grain yield under stressed conditions
(Dolatabadian et al., 2013). In present study, the biopriming improved the grain yield of
barley which was associated with improved plant growth that led to enhanced spike
length, number of spikelets and grains and grain weight. Moreover, the enhanced
osmolytes accumulation, better water relations and well maintained cell membrane
stability due to decreased lipid peroxidation was translated in improved grain yield and
harvest index. Endophytic bacteria, used in biopriming, enhances growth and
development by production of auxin while decreasing the ethylene accumulation that
results in improved chlorophyll, greater accumulation of osmolytes, and improved water
and nutrient relations which is translated into improved yield and harvest index (Miliute
et al., 2015; Santoyo et al., 2016; Montalbán et al., 2017). Similar, Naveed et al. (2014c)
reported that endophytic bacteria Burkholderia phytofrmans strain PsJN improved the
photosynthesis, nutrients uptake, water relations, and yield and related traits of wheat
under drought stress.
4.2.5. Chlorophyll contents
4.2.5.1. Chlorophyll a content
Salinity and seed priming induced a significant effect on chlorophyll a content;
tested barley varieties also significantly differed for chlorophyll a content, during both
growing seasons. The interactions between varieties and salinity, varieties and seed
priming, salinity and seed priming, and three way interaction among varieties, salinity
and seed priming was significant, during both years (Table 4.80). The chlorophyll a
content was decreased with increase in severity of salt stress. Higher chlorophyll a 120
content was exhibited by Frontier-87 during 2014-15 while during 2015-16 Haider-93
produced more chlorophyll a content. Seed priming ameliorated the deleterious effects of
salinity by improving the chlorophyll a content of tested barley varieties at each level of
salt stress, as compared to unprimed control. Under moderate salinity, the biosynthesis of
chlorophyll a was exaggerated by biopriming of Frntiers-87 and hydropriming of Haider-
93 during 2014-15 and 2015-16, respectively. However, under severe salinity, maximum
increase in chlorophyll a content was recorded by osmopriming of Haider-93 and
biopriming of Frontier-87 during 2014-15 and 2015-16 (Figures 4.7a,b).
4.2.5.2. Chlorophyll b content
Chlorophyll b content was significantly affected by salinity and seed priming,
during both years. Similarly, barley varieties also differed significantly for chlorophyll b,
during both growing seasons. The interaction between varieties and salinity was non-
significant during 2014-15 but significant during 2015-16. The interaction between
varieties and seed priming, salinity and seed priming as well as three way interaction
among varieties, salinity and seed priming was significant, during both years (Table
4.80). Salinity decreased the chlorophyll b and it was proportional to its severity. More
chlorophyll b content was produced by Haider-93 than Frontier-87. However, seed
priming ameliorated the deleterious effects of salinity by improving the chlorophyll b of
both varieties at all levels of salinity, as compared to unprimed control. Chlorophyll b
content was exalted by biopriming of Haider-93 under both moderate and severe salinity,
during both years (Figures 4.7c,d).
4.2.6. Osmolytes accumulation
4.2.6.1. Total soluble phenolics
Salinity and seed priming significantly affected total soluble phenolics contents,
during both growing seasons; the varieties also differed significantly for total soluble
phenolics contents. The interactions between varieties and salinity, varieties and seed
priming, salinity and seed priming, and three way interaction among varieties, salinity
and seed priming was significant, during both years (Table 4.81). The total soluble
phenolics content was increased with increase in severity of salt stress. Frontier-87
produced higher total soluble phenolics than Haider-93. Moreover, seed priming further
improved the production of total soluble phenolics of both barley varieties at each level of
salinity, as compared unprimed control. During 2014-15, greatest increase in total soluble
phenolics content was caused by osmopriming of Haider-93 under both moderate and
severe salinity. However, during 2015-16, highest total soluble phenolics content was 121
noticed by biopriming and osmopriming of Haider-93 under moderate and severe salt
stress,
122
Table 4.80: Analysis of variance for the influence of seed priming on chlorophyll contents of barley under salinity SOV df Mean sum of square
Chlorophyll a Chlorophyll b2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 0.0018** 0.0050** 0.0053** 0.0107**
Salinity (S) 2 0.2494** 0.3547** 0.0914** 0.1363**
Priming (T) 3 0.0238** 0.0048** 0.0064** 0.0053**
V×S 2 0.0019* 0.0006** 0.0001ns 0.0019**
V×T 3 0.0049** 0.0007** 0.0004** 0.0003*
S×T 6 0.0023** 0.0016** 0.0010** 0.0009**
V×S×T 6 0.0021** 0.0010** 0.0004** 0.0016**
Error 72 0.0001 0.0001 0.0001 0.0001Total 95
Table 4.81: Analysis of variance for the influence of seed priming on total soluble proteins and total soluble phenolics contents of barley under salinity SOV df Mean sum of square
Total soluble phenolics Total soluble proteins2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 2800.4** 1882.1* 0.0408** 0.0044**
Salinity (S) 2 131106.8** 251795.2** 0.5409** 0.8596**
Priming (T) 3 11235.6** 4813.8** 0.0109** 0.0033**
V×S 2 3707.5** 8575.6** 0.0094** 0.0028**
V×T 3 3306.7* 1936.9** 0.0018* 0.0008ns
S×T 6 2789.9** 1563.6** 0.0017** 0.0017**
V×S×T 6 356.5** 2240.5** 0.0040** 0.0024**
Error 72 104.9 207.7 0.0002 0.0004Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
123
Chl
orop
hyll
a co
nten
t (m
g g-1
FW
)C
hlor
ophy
ll b
cont
ent (
mg
g-1 F
W)
124
Tot
al so
lubl
e ph
enol
ics (
µg g
-1 F
W)
Tot
al so
lubl
e pr
otei
ns (m
g g-1
FW)
125
respectively (Figures 4.8a,b).
4.2.6.2. Total soluble proteins
Total soluble proteins were significantly affected by salinity and seed priming; the
barley varieties significantly differed, during both growing seasons. The interaction
between varieties and seed priming was significant during 2014-15 while non-significant
during 2015-16. However, the interactions between varieties and salinity, salinity and
seed priming as well as three way interaction among varieties, salinity and seed priming
was significant, during both years (Table 4.81). Total soluble proteins were increased
with increase in severity of salt stress. Higher total soluble proteins were produced by
Haider-93 than Frontier-87. Seed priming ameliorated the deleterious effects of salinity
by further enhancing the accumulation of total soluble proteins of both varieties at each
level of salt stress, as compared unprimed control. Under moderate stress, greatest
increase in total soluble proteins was caused by osmopriming of Haider-93 and
biopriming of Frontier-87 during 2014-15 and 2015-16, respectively. Under severe
salinity, biopriming and hydropriming of Haider-93 exhibited highest total soluble
proteins during 2014-15 and 2015-16, respectively (Figures 4.8c,d).
4.2.6.3. Free proline content
There was a significant effect of salinity and seed priming on free leaf proline
content; the tested barley varieties also differed significantly, during both years. The
interaction between varieties and seed priming, varieties and salinity, salinity and seed
priming, and three way interaction among varieties, salinity and seed priming was
significant, during both growing seasons (Table 4.82). Free proline content was increased
by salt stress relative to its severity. Higher free proline content was exhibited by Haider-
93 than Frontier-87. Seed priming enhanced the accumulation of free proline in both
barley varieties at all levels of salinity, as compared unprimed control. Under moderate
salinity, greatest increase in free leaf proline content was recorded by biopriming of
Frontier-87 and hydropriming of Haider-93 during 2014-15 and 2015-16, respectively.
However, under severe salinity, osmopriming and biopriming of Haider-93 caused
maximum increase in proline content during 20114-15 and 2015-16, respectively (Figures
4.9a,b).4.2.6.4. Glycine betaine content
Leaf glycine betaine content was significantly affected by salt stress and seed
priming; tested barley varieties also differed significantly, during both years. The
interactions between varieties and salinity, and varieties and seed priming were non-
significant during 2014-15 but significant during 2015-16. However, interaction between 126
salinity and seed priming, and three way interaction among varieties, salinity and seed
priming were significant, during both years (Table 4.82). The glycine betaine content was
increased with increase in severity of salt stress. Haider-93 accumulated more glycine
betaine than Frontier-87. Glycine betaine content was further increased by seed priming
in both varieties at all levels of salt stress, as compared to unprimed control. Under
moderate stress, highest glycine betaine content was noticed by osmopriming of Haider-
93, during both years. However, under severe salt stress, biopriming and osmopriming of
Haider-93 caused maximum increase in glycine betaine content during 2014-15 and
2015-16, respectively (Figures 4.9c,d).
4.2.7. Lipid peroxidation
4.2.7.1. Malondialdehyde content
There was a significant effect of salinity and seed priming on MDA content,
during both years; the tested barley varieties also differed significantly for MDA content.
The interaction between varieties and seed priming was significant during 2014-15 but
non-significant during 2015-16. However, interactions between varieties and salinity,
salinity and seed priming, and three way interaction among varieties, salinity and seed
priming was significant, during both seasons (Table 4.83). The MDA content was
increased with increase in severity of salt stress. Higher MDA content was accumulated
in Frontier-87 than Haider-93. Seed priming ameliorated the deleterious effects of salinity
by lowering down MDA accumulation in tested barley varieties at all levels of salinity, as
compared to unprimed control. Minimum MDA accumulation occurred in response to
osmopriming of Haider-93 under both moderate and severe salinity, during 2014-15.
However, during 2015-16 biopriming of Haider-93 caused maximum decrease in MDA
under both moderate and severe salinity (Figures 4.10a,b).
4.2.7.2. Cell membrane stability
A significant effect of salinity and seed priming was observed for cell membrane
stability; tested barley varieties also differed significantly for cell membrane stability,
during both growing seasons. The interaction between salinity and seed priming was non-
significant during 2014-15 but significant during 2015-16. However, interactions between
varieties and salinity, and varieties and seed priming, and three way interaction among
varieties, salinity and seed priming was significant, during both years (Table 4.83).
Salinity decreased the cell membrane stability and it was proportional to its severity.
Haider-93 recorded higher cell membrane stability than Frontier-87. Seed priming
improved the cell membrane stability of both varieties at all levels of salinity, as 127
compared to unprimed control. Under moderate salt stress, greatest improvement in cell
membrane stability was noticed by osmopriming and biopriming of Haider-93 during
2014-15 and 2015-16, respectively. Under severe salinity, osmopriming and
hydropriming of Haider-93 was superior in improving cell membrane stability during
2014-15 and 2015-16, respectively (Figures 4.10c,d).
4.2.8. Mineral analysis
4.2.8.1. Na content
The Na content was significantly affected by salinity and seed priming, while,
varieties also differed significantly for Na content, during both years. Moreover, the
interactions between varieties and salinity, varieties and seed priming, salinity and seed
priming as well as three way interaction among varieties, salinity and seed priming was
significant for Na content, during both years (Table 4.84). The Na content was increased
with increase in severity of salt stress. Haider-93 accumulated less Na than Frontier-87.
Moreover, seed priming decreased the accumulation of Na in both barley varieties at each
level of salt stress, as compared to unprimed control. Under moderate salts stress,
minimum Na accumulation occurred by biopriming of Frontier-87 and osmopriming of
Haider-93 during 2014-15 and 2015-16, respectively. However, under severe salinity,
minimum Na accumulation was recorded by osmopriming of Haider-93, during both
years (Figures 4.11a,b).
4.2.8.2. K content
Leaf K content was significantly affected by salinity and seed priming, during
both growing seasons; varieties also differed significantly for K content. The interaction
between varieties and seed priming was non-significant during 2014-15 but significant
during 2015-16. However, the interactions between varieties and salinity, salinity and
seed priming as well as three way interaction among varieties, salinity and seed priming
was significant, during both growing seasons (Table 4.84). The K content was
proportionally decreased by salt stress relative to its severity. Higher K content was
exhibited by Haider-93 than Frontier-87. Seed priming enhanced the K content in both
varieties at each level of salinity, as compared to unprimed control. Under moderate
salinity, the greatest increase in K content was recorded by hydropriming and
osmopriming of Haider-93 during 2014-15 and 2015-16. Whereas, under severe salts
stress, maximum K content was noticed by osmopriming and hydropriming of Haider-93
during 2014-15 and 2015-16, respectively (Figures 4.11c,d).
128
Table 4.82: Analysis of variance for the influence of seed priming on free proline and glycine betaine contents of barley under salinity SOV df Mean sum of square
Free proline content Glycine betaine content2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 0.1321** 0.0389** 0.0324** 0.0193**
Salinity (S) 2 1.7916** 1.3544** 0.4837** 0.6131**
Priming (T) 3 0.1871** 0.0254** 0.0266** 0.0338**
V×S 2 0.0344** 0.0094** 0.0011ns 0.0236**
V×T 3 0.0187** 0.0013* 0.0009ns 0.0025*
S×T 6 0.0518** 0.0069** 0.0180** 0.0077**
V×S×T 6 0.0199** 0.0035** 0.0059** 0.0035**
Error 72 0.0021 0.0005 0.0006 0.0006Total 95
Table 4.83: Analysis of variance for the influence of seed priming on malondialdehyde and cell membrane stability of barley under salinitySOV df Mean sum of square
Malondialdehyde Cell membrane stability2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 171.42** 340.34** 53.03** 54.76**
Salinity (S) 2 889.52** 1395.97** 5318.72** 4981.59**
Priming (T) 3 171.89** 84.63** 547.86** 249.60**
V×S 2 36.58** 32.94** 30.69** 131.14**
V×T 3 12.41** 1.96ns 21.77* 42.13**
S×T 6 37.72** 11.61** 7.17ns 22.89**
V×S×T 6 17.38** 11.37** 27.47** 26.17**
Error 72 2.37 1.78 5.87 2.08Total 95
Table 4.84: Analysis of variance for the influence of seed priming on leaf mineral contents of barley under salinitySOV df Mean sum of square
Na content K content 2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 99982** 111203** 45581** 8963**
Salinity (S) 2 15498035** 18125546** 148125** 297312**
Priming (T) 3 224227** 37860** 10695** 2892**
V×S 2 95082** 138417** 2617** 2888**
V×T 3 42443* 14439* 833ns 2966**
S×T 6 104532** 23474** 2396** 793*
V×S×T 6 29189** 10670** 1611** 1626**
Error 72 1476 509 314 194Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
129
Free
pro
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ent (
µmol
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W)
Gly
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bet
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con
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(µm
ol g
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130
Mal
ondi
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(µm
ol g
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W)
Cel
l mem
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ty (%
)
131
Na
cont
ent (
mg
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W)
K c
onte
nt (m
g g-1
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132
4.2.9. Discussion
Salt stress decreased the chlorophyll contents, cell membrane stability and K
content while increased osmolytes accumulation, Na and MDA contents in both barley
varieties with increase in its severity and more deleterious effects on Frontier-87. Salinity
decreases plant growth and dry matter accumulation by decreasing the net assimilation
rate (NAR), relative water content, leaf water potential, soluble sugars, K+, Ca2+ and
Mg2+ contents, chlorophyll and carotenoids contents, and number and size of stomata
while increasing the Na+, Cl− and lipid peroxidation (Karimi et al., 2005; Farooq et al.,
2015). However, plants respond to salt stress by increased osmolytes accumulation,
antioxidants activity and selective uptake of Na+ and K+ which results in improved water
relations and decreased lipid peroxidation by ROS (Munns and Tester, 2008).
In present study, seed priming improved the chlorophyll contents and cell
membrane stability by enhanced accumulation of phenolics, total soluble proteins, proline
and glycine betaine while decreased lipid peroxidation in both barley varieties. Improved
chlorophyll contents by seed priming is attributed to well-maintained cell membrane
stability due to better protection of cellular membranes from lipid peroxidation (Song et
al., 2017). Under stressed conditions, the osmopriming enhances stress tolerance by
triggering the gene expression for osmolytes, antioxidants and stress proteins (Chen et al.,
2012; Kubala et al., 2015; Souza et al., 2016) and improving the tissue water status,
chloroplast structure and functioning of chlorophyll (Kubala et al., 2015; Tabassum et al.,
2017; Dai et al., 2017), while lowering the lipid peroxidation damage to cellular
membranes (Zhang et al., 2015). Furthermore, in present study the Ca2+ used in
osmopriming, triggers the gene expression for osmolytes, and improves plant growth and
stress tolerance by regulating the calmodulin like proteins in signaling pathways (White
and Broadley, 2003; Sarwat et al., 2013).
Biopriming improved the plant growth and stress tolerance by improving the
chlorophyll contents, osmolytes accumulation and decreased lipid peroxidation in both
barley varieties under severe salt stress. Plant growth promoting bacteria improves the
stress tolerance through enhanced osmolytes accumulation, antioxidants defense, nutrient
uptake and carbohydrates metabolism (Dimkpa et al., 2009; Chakraborty et al. 2011)
which results in decreased lipid peroxidation and better cell membrane stability
(Theocharis et al., 2012). Endophytic bacteria in biopriming, place the metabolism of
plants in primed state that enable greater and rapid accumulation of transcription factors
133
and metabolites for osmolytes and stress related gene expression (Theocharis et al., 2012;
Miotto-Vilanova et al., 2016).
Seed priming enhanced K accumulation while decreased Na accumulation in both
barley varieties under severe salinity. Osmopriming triggers the gene expression for high
affinity potassium transporter protein 1 (HAK1) and the salt overly sensitive 1 (SOS 1)
antiporter which causes increase in K and decrease in Na uptake and accumulation under
stressed conditions (Souza et al., 2016). Moreover, extracellular Ca2+ causes a decrease in
efflux of K and influx of Na via non-selective cation channels due to decreased
membrane depolarization by NaCl in the presence of high Ca2+ concentration (Shabala et
al., 2006). In biopriming, endophytic bacteria enhances uptake of N, P and K thereby
increasing the K:Na ratio in plants under salinity (Dodd and Pérez-Alfocea, 2012). They
excrete exopolysaccharides which bind Na and decrease its uptake under salinity (Ashraf
et al., 2004). Moreover, it has been suggested that a greater proportion of root zone of
endophytic bacteria treated plants was covered with soil sheath that decrease the
apoplastic flow of Na+ into stele (Dodd and Pérez-Alfocea, 2012).
4.2.10. Water relations
4.2.10.1. Leaf relative water content
There was a significant effect of salinity and seed priming on leaf relative water
content; barley varieties also differed significantly, during both growing seasons.
Interaction between varieties and salinity was significant during 2014-15 but non-
significant during 2015-16. Whereas, the interactions between varieties and seed priming,
salinity and seed priming as well as three way interaction among varieties, salinity and
seed priming was significant, during both years (Table 4.85). Leaf relative water content
was proportionally decreased by salt stress relative to its severity. Haider-93 recorded
higher leaf relative water content than Frontier-87. Moreover, seed priming improved the
leaf relative water content in tested barley varieties at each level of salt stress, as
compared to unprimed control. Highest leaf relative water content was observed by
biopriming of Frontier-87 and Haider-93 under moderate salinity during 2014-15 and
2015-16 respectively. However, under severe salinity osmopriming of Haider-93 resulted
in highest leaf relative water content, during both growing seasons (Figures 4.12a,b).
4.2.10.2. Leaf water potential
Salt stress and seed priming significantly affected leaf water potential; the selected
varieties also differed significantly, during both growing seasons. However, the
134
interaction between varieties and seed priming was significant during 2014-15 but non-
significant during 2015-16. Whereas, the interactions between varieties and salinity,
salinity and seed priming, and three way interaction among varieties, salinity and seed
priming was significant, during both years (Table 4.85). Leaf water potential was
decreased with increase in severity of salt stress. Haider-93 maintained higher leaf water
potential than Frontier-87. Leaf water potential of both varieties was improved by seed
priming treatments under all levels of salinity, as compared to unprimed control. Under
moderate salinity, maximum increase in leaf water potential was noticed by hydropriming
and osmopriming of Haider-93 during 2014-15 and 2015-16. Under severe salinity,
osmopriming and biopriming of Haider-93 led to maximum improvement in leaf water
potential during 2014-15 and 2015-16, respectively (Figures 4.12c,d).
4.2.10.3. Leaf osmotic potential
Salinity and seed priming significantly affected the leaf osmotic potential of
barley, during both growing seasons; while, the varieties significantly differed during
2014-15 but did not differ significantly during 2015-16. The interactions between
varieties and salinity, varieties and seed priming, salinity and seed priming, and three way
interaction among varieties, salinity and seed priming was significant, during both years
(Table 4.86). Salinity decreased the leaf osmotic potential and it was proportional to its
severity. Higher osmotic potential was exhibited by Haider-93 than Frontier-87. The
osmotic potential of both barley varieties were improved by seed priming treatments
under each level of salinity, as compared to unprimed control. Under moderate stress, the
greatest improvement in leaf osmotic potential was caused by osmopriming of Haider-93,
during both years. Under severe salinity, maximum leaf osmotic potential was observed
by biopriming of Haider-93, during both years. However, osmopriming of Haider-93
produced similar results for leaf osmotic potential under sever salt stress during 2014-15
(Figures 4.13a,b).
4.2.10.4. Leaf pressure potential
The leaf pressure potential was significantly affected by salinity, during both
growing seasons. However, there was a non-significant effect of seed priming on water
potential, during both years. Whereas, the varieties did not differ significant during 2014-
15 but differed significantly during 2015-16. The interaction between varieties and
salinity was significant, during both growing seasons. However, the interaction between
varieties and seed priming was non-significant during 2014-15 but significant during
2015-16; while, interaction between salinity and seed priming was non-significant, during 135
both growing seasons. Three way interaction among varieties, salinity and seed priming
was significant during 2014-15 but non-significant during 2015-16 (Table 4.86). Leaf
pressure
136
Table 4.85: Analysis of variance for the influence of seed priming on leaf relative water content and leaf water potential of barley under salinitySOV df Mean sum of square
Leaf relative water content Leaf water potential2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 225.40** 163.88** 5.694** 3.550**
Salinity (S) 2 8651.30** 10060.88** 41.225** 47.351**
Priming (T) 3 202.10** 97.11** 0.568* 5.157**
V×S 2 79.54** 0.49ns 1.154** 1.667*
V×T 3 16.85** 11.33* 0.279** 0.157ns
S×T 6 44.69** 14.93** 0.146* 0.414**
V×S×T 6 11.34* 29.99** 0.299** 0.410**
Error 72 2.59 2.44 0.063 0.077Total 95
Table 4.86: Analysis of variance for the influence of seed priming on leaf osmotic potential and leaf pressure potential of barley under salinitySOV df Mean sum of square
Leaf osmotic potential Leaf pressure potential2014-15 2015-16 2014-15 2015-16
Varieties (V) 1 7.069** 0.024ns 0.074ns 3.000**
Salinity (S) 2 82.650** 73.200** 8.005** 3.641**
Priming (T) 3 0.847** 5.896** 0.152ns 0.041ns
V×S 2 3.496* 0.137* 1.390* 0.917**
V×T 3 0.219* 0.511** 0.071ns 0.339*
S×T 6 0.092** 0.308** 0.061ns 0.109ns
V×S×T 6 0.088** 0.208* 0.544** 0.071ns
Error 72 0.014 0.018 0.068 0.074Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
137
Lea
f rel
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ater
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Lea
f wat
er p
oten
tial (
-MPa
)
138
Lea
f osm
otic
pot
entia
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Pa)
Lea
f pre
ssur
e po
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ial (
MPa
)
139
potential was proportionally decreased by salt stress relative to its severity. Haider-93
maintained higher pressure potential than Frontier-87. Moreover, seed priming improved
the leaf pressure potential of tested barley varieties at each level of salt stress, as
compared to unprimed control. The maximum improvement in leaf pressure potential was
caused by osmopriming of Haider-93 and hydropriming of Frontier-87 under moderate.
Whereas, under severe salinity, hydropriming of Haider-93 and biopriming of Frontier-87
caused greatest increase in leaf pressure potential during 2014-15 and 2015-16,
respectively (Figures 4.13c,d).
4.2.11. Discussion
Water relations were perturbed by salinity with increase in its severity; however,
seed priming improved the leaf relative water content, water potential, osmotic potential
and pressure potential in both varieties. However, Haider-93 better maintained tissue
water status which is attributed to greater accumulation of osmolytes. Salinity disturbs the
water relations of by osmotic stress; however, to cope with this situation plants produce
and accumulate osmolytes in greater amount for osmotic adjustment (Munns and Tester,
2008). In present study, improved water relations by seed priming might be due to better
root growth that enhanced water uptake from deeper layers of soil and osmotic
adjustment through enhanced accumulation of osmolytes due to increased gene
expression resulting from accumulation of transcription factors during priming induced
stress in the form of desiccation and osmotic stress (Chen and Arora, 2013). Moreover, in
osmopriming Ca2+ also serves as osmoticum that might also have added its beneficial role
in osmotic adjustment (White and Broadley, 2003). In biopriming, the endophytic
bacteria produce auxin which results in enhanced root growth of plants making the plants
capable for water uptake from deeper layers of soil (Santoyo et al., 2016). It has been
observed that treatment with auxin producing bacteria enhances root growth and water
uptake which aids to maintain better tissue water status under stressed conditions
(German et al., 2000; Vurukonda et al., 2016). Moreover, endophytic bacteria enhances
production and accumulation of osmolytes that maintain better water relations through
osmotic adjustment as observed in present study (Dimkpa et al., 2009).
4.2.12. Grain nutrient contents
4.2.12.1. Grain zinc content
The grain Zn content was significantly affected by salinity and seed priming;
varieties also differed for grain Zn content significantly, during both growing seasons.
The interaction between varieties and salinity was significant, during both years. 140
However, the interactions between varieties and seed priming, salinity and seed priming
and three way interaction among varieties, salinity and seed priming was non-significant,
during both years (Table 4.87). A reduction in grain Zn content was caused by salt stress
with greatest decrease occurring at severe salinity, as compared to control. Under both
moderate as well as severe salinity the variety Haider-93 exhibited higher grain Zn
content than Frontier-87, during both growing seasons (Tables 4.88a, 4.89a). Across
salinity and varieties the biopriming improved the grain Zn contents, as compared to
unprimed control (Tables 4.88b, 4.89b).
4.2.12.2. Grain manganese content
Grain Mn content was significantly affected by salinity and seed priming. Selected
barley varieties also significantly differed for grain Mn content, during both years. The
interaction between varieties and salinity was significant, during both years. However, the
interactions between varieties and seed priming, salinity and seed priming and three way
interaction among varieties, salinity and seed priming was non-significant, during both
growing seasons (Table 4.87). Grain Mn content was decreased by salt stress and least
Mn content was recorded at severe salinity, as compared to control (Table 2). Under
moderate stress, variety Haider-93 exhibited higher Mn content, during both years.
However, under severe salinity higher grain Mn content was observed in variety Haider-
93 during 2014-15 and in Frontier-87 during 2015-16 (Tables 4.90a, 4.91a). Across
salinity and varieties the grain Mn content was improved by biopriming, during both
growing seasons, as compared to unprimed control (Tables 4.90b, 4.91b).
4.2.12.3. Grain boron content
Salt stress and seed priming significantly affected grain B contents; barley
varieties also differed significantly, during both years. The interaction between varieties
and salinity was significant, during both years. However, the interactions between
varieties and seed priming, salinity and seed priming and three way interaction between
varieties, salinity and seed priming were non-significant, during both seasons (Table
4.87). Salinity decreased the grain B content as compared to control with maximum
decrease occurring at severe salinity (Table 2). Under moderate salinity, higher grain B
contents were recorded by Frontier-87 during 2014-15 while during 2015-16 higher B
contents were noticed in Haider-93. However, under severe salt stress higher grain B
content was exhibited by Haider-93, during both years (Tables 4.92a, 4.93a). Across
salinity and varieties the biopriming improved the grain B contents, as compared to
unprimed control, during both years (Tables 4.92b, 4.93b).141
4.2.13. Discussion
Salt stress caused a reduction in grain mineral nutrients contents in both varieties
relative to its increasing severity; however, Haider-93 accumulated more Zn, Mn and B in
its grains. Better grain nutrient contents in Haider-93 is attributed to well-maintained
tissue water status and cell membrane stability. Salt stress causes osmotic stress which
results in decreased water uptake with concomitant decrease in nutrient uptake by plants
(Marcelis and Hooijdonk, 1999). In present study, seed priming treatments improved the
grain nutrient contents under salt stress. There was significant increase in grain mineral
nutrients contents by biopriming which might be due to solubilization of nutrients in soil
by producing extra cellular enzymes and siderophores, and through improved root growth
due to production of growth promoting phytohormones and decrease in ethylene synthesis
(Miliute et al., 2015; Vurukonda et al., 2016). In present study, biopriming improved
water relations in both varieties which might have caused enhanced translocation and
accumulation of nutrients in grains. Similar results were reported by Rana et al. (2012)
that inoculation of wheat with Bacillus sp., Providencia sp. and Brevundimonas sp.
increased Zn, Mn, Cu and Fe uptake and accumulation in wheat grains.
142
Table 4.87: Analysis of variance for the influence of seed priming on grain mineral contents of barley under salinitySOV df Mean sum of square
Seed zinc content Seed manganese content
Seed boron content
2014-15 2015-16 2014-15 2015-16 2014-15 2015-16Varieties (V) 1 72.77** 75.63** 1522.11** 441.27** 0.288** 0.232**
Salinity (S) 2 553.44** 807.85** 6622.35** 10426.41** 1.180** 1.448**
Priming (T) 3 49.58** 50.50** 608.86** 529.01** 0.113** 0.093**
V×S 2 14.86* 18.08** 152.67* 240.11** 0.114** 0.040*
V×T 3 1.67ns 1.39ns 28.71ns 20.27ns 0.006ns 0.002ns
S×T 6 6.92ns 6.73ns 101.14ns 26.54ns 0.012ns 0.017ns
V×S×T 6 4.00ns 2.02ns 20.07ns 24.76ns 0.004ns 0.001ns
Error 72 3.32 3.13 46.50 20.64 0.006 0.009Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 44.88a: Influence of seed priming on grain zinc content (µg g -1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanH-93 40.29 a 36.32 bc 31.00 d 35.87 AF-87 36.98 b 35.47 c 29.93 d 34.13 BMean 38.64 A 35.89 B 30.47 C
Varieties LSD≤0.05 = 0.7409, Salinity LSD≤0.05 = 0.9074, Varieties × Salinity LSD≤0.05 = 1.2833
Table 4.88b: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanControl 37.76 34.47 29.19 33.80 CHP 38.25 35.64 30.82 34.90 BOP 36.64 36.00 30.08 34.24 BCBP 41.91 37.46 31.77 37.05 AMean 38.64 A 35.89 B 30.47 C
Salinity LSD≤0.05 = 0.9074, Seed priming LSD≤0.05 = 1.0478
Table 4.89a: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanH-93 41.66 a 37.04 bc 30.73 d 36.48 AF-87 38.20 b 36.47 c 29.44 e 34.70 BMean 39.93 A 36.75 B 30.08 C
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties LSD≤0.05 = 0.7202, Salinity LSD≤0.05 = 0.8821, Varieties × Salinity LSD≤0.05 = 1.2474
143
Table 4.89b: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanControl 38.79 35.59 29.05 34.48 CHP 40.70 36.21 30.20 35.70 BOP 37.49 36.58 29.65 34.58 CBP 42.73 38.63 31.43 37.60 AMean 39.93 A 36.75 B 30.08 C
Salinity LSD≤0.05 = 0.8821, Seed priming LSD≤0.05 = 1.0185
Table 4.90a: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanH-93 127.45 a 123.18 ab 97.69 d 116.11 AF-87 119.35 b 110.92 c 94.16 d 108.14 BMean 123.40 A 117.05 B 95.92 C
Varieties LSD≤0.05 = 2.7748, Salinity LSD≤0.05 = 3.3984, Varieties × Salinity LSD≤0.05 = 4.8060
Table 4.90b: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanControl 121.81 111.36 91.22 108.13 CHP 121.60 120.47 96.71 112.93 BOP 115.88 113.93 95.70 108.50 CBP 134.31 122.44 100.05 118.94 AMean 123.40 A 117.05 B 95.92 C
Salinity LSD≤0.05 = 3.3984, Seed priming LSD≤0.05 = 3.9241
Table 4.91a: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanH-93 124.92 a 113.96 c 86.53 e 108.47 AF-87 120.82 b 104.11 d 87.62 e 104.18 BMean 122.87 A 109.04 B 87.08 C
Varieties LSD≤0.05 = 1.8488, Salinity LSD≤0.05 = 2.2643, Varieties × Salinity LSD≤0.05 = 3.2022
Table 4.91b: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanControl 119.25 104.34 83.64 102.41 CHP 121.06 107.90 87.22 105.39 BOP 119.05 108.16 85.96 104.39 BCBP 132.12 115.75 91.49 113.12 AMean 122.87 A 109.04 B 87.08 C
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Salinity LSD≤0.05 = 2.2643, Seed priming LSD≤0.05 = 2.6146
144
Table 4.92a: Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanH-93 1.95 a 1.70 c 1.61 d 1.75 AF-87 1.82 b 1.72 c 1.39 e 1.64 BMean 1.88 A 1.71 B 1.50 C
Varieties LSD≤0.05 = 0.0316, Salinity LSD≤0.05 = 0.0387, Varieties × Salinity LSD≤0.05 = 0.0547
Table 4.92b: Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanControl 1.85 1.64 1.43 1.64 CHP 1.86 1.73 1.49 1.69 BOP 1.81 1.68 1.51 1.67 BCBP 2.02 1.80 1.57 1.80 AMean 1.88 A 1.71 B 1.50 C
Salinity LSD≤0.05 = 0.0387, Seed priming LSD≤0.05 = 0.0447
Table 4.93a: Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanH-93 1.96 a 1.69 c 1.51 d 1.72 AF-87 1.80 b 1.67 c 1.40 e 1.62 BMean 1.88 A 1.68 B 1.45 C
Varieties LSD≤0.05 = 0.0378, Salinity LSD≤0.05 = 0.0463, Varieties × Salinity LSD≤0.05 = 0.0655
Table 4.93b: Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanControl 1.85 1.58 1.39 1.60 CHP 1.88 1.73 1.42 1.67 BOP 1.81 1.66 1.49 1.65 BCBP 1.99 1.75 1.53 1.75 AMean 1.88 A 1.68 B 1.45 C
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Salinity LSD≤0.05 = 0.0463, Seed priming LSD≤0.05 = 0.0534
145
4.3. Influence of seed priming in improving the resistance against osmotic and salt stresses in barley4.3.1. Seedling growth
Osmotic stress and seed priming significantly affected shoot and root length, and
fresh and dry weights of barley seedlings; the tested varieties of barley also differed
significantly for seedling growth traits except shoot length and root dry weight. The
interaction between varieties and osmotic stress was significant for shoot length, shoot
fresh weight, root fresh weight and shoot dry weight while, non-significant for root length
and root dry weight. Interaction between varieties and seed priming was significant for all
seedling growth traits except shoot fresh weight. However, the interaction between
osmotic stress and seed priming, and three way interaction among varieties, osmotic
stress and seed priming were significant for all studied seedling growth traits (Table
4.94).
Seedling growth was decreased by both osmotic stress (PEG-8000) and salt stress
(NaCl salt), as compared to control. Salt stress caused greater reduction in seedling
growth of both varieties as compared to osmotic stress. The varieties showed a
differential response to osmotic and salt stress regarding seedling growth traits. The
deleterious effects of osmotic stress on root growth were greater in Frontier-87 while for
shoot growth more reductions were observed in Haider-93. However, salt stress imposed
more negative effects on both root and shoot growth traits of Frontier-87 than Haider-93.
Seed priming improved the seedling growth of both varieties under stressed conditions, as
compared to unprimed control. Under osmotic stress, maximum increase in shoot length,
root length, shoot dry weight, and root fresh and dry weights was caused by biopriming of
Haider-93; while, shoot fresh weight was improved most by osmopriming of Frontier-87.
Under salt stress, maximum increase in shoot length, root length, shoot and root fresh and
dry weights was caused by osmopriming of Haider-93 (Figures 4.14a-c, 4.15a-c).
4.3.2. Chlorophyll contents
Chlorophyll a and b contents were significantly affected by osmotic stress and
seed priming; while, barley varieties also differed significantly for chlorophyll a and b
contents. The interaction between varieties and osmotic stress was significant for
chlorophyll a and b contents. However, interactive effects of varieties and seed priming,
and osmotic stress and seed priming were significant for chlorophyll a content while non-
significant for chlorophyll b content. The three way interaction among varieties, osmotic
stress and seed priming was significant for both chlorophyll a and b contents (Table
146
4.95). Osmotic and salt stress decreased the chlorophyll a and b contents in both varieties,
as compared to control. However, both osmotic and salt stresses were equally deleterious
for Haider-93 but salt stress was more deleterious for Frontier-87 than osmotic stress
regarding chlorophyll a and b contents. Seed priming improved the chlorophyll contents
in both varieties under osmotic as well as salt stress, as compared to unprimed control.
Under osmotic stress, maximum increase in chlorophyll a and b contents was caused by
biopriming of Haider-93. Under salts stress, chlorophyll a and b contents were increased
most by biopriming and osmopriming of Haider-93, respectively (Figures 4.16a,b).
4.3.3. Osmolytes accumulation
Osmotic stress and seed priming significantly affected total soluble phenolics,
total soluble proteins, proline and glycine contents; tested barley varieties also differed
significantly for all studied osmolytes. The interaction between varieties and seed priming
was non-significant for all studied osmolytes. The interactions between varieties and
osmotic stress, osmotic stress and seed priming, and three way interaction among
varieties, osmotic stress and seed priming was significant for all studied osmolytes
(Tables 4.95, 4.96).
Osmotic and slat stresses increased the production and accumulation of osmolytes
in both barley varieties, as compared to control. However, accumulation of total soluble
phenolics, total soluble proteins, proline and glycine contents was greater under osmotic
stress in both varieties than salt stress. Moreover, the varieties differed in osmolytes
accumulation under osmotic and salt stress. Osmolytes accumulation in both varieties was
similar under osmotic stress, however, under salt stress Haider-93 accumulated more
osmolytes than Frontier-87. Seed priming further increased the accumulation of
osmolytes under stressed conditions, as compared to unprimed control. Under osmotic
stress, total soluble phenolics, total soluble proteins and glycine betaine contents were
enhanced most by biopriming of Haider-93, while, proline content was exalted by
osmopriming of Haider-93. Under salt stress, biopriming of Frontier-87 and Haider-93
caused maximum increase in accumulation of total soluble phenolics and proline,
respectively. However, maximum increase in total soluble proteins and glycine betaine
contents was caused by osmopriming of Haider-93 (Figures 4.16c, 4.17a-c).
4.3.4. Lipid peroxidation and sodium accumulation
Osmotic stress and seed priming significantly affected MDA and Na contents.
Varieties also differed significantly for MDA and Na accumulation. The interactions
between varieties and osmotic stress, and osmotic stress and seed priming were non-147
significant for MDA while significant for Na content. However, interaction between
varieties and seed priming was significant for MDA but non-significant for Na content.
The three way interaction among varieties, osmotic stress and seed priming was
significant for both MDA and Na contents (Table 4.97). Osmotic and salt stress
substantially increased the accumulation of MDA, while Na content was increased by
NaCl salt stress in both varieties, as compared to control. The MDA accumulation was
greater under salt stress than osmotic stress. Moreover, greater MDA and Na was
accumulated in Frontier-87 than Haider-93 under stressed conditions. Seed priming
caused a reduction in MDA and Na accumulation in both varieties under osmotic as well
as salt stress, as compared to unprimed control. Under osmotic stress, biopriming of
Haider-93 decreased the MDA content most. However, under salt stress, osmopriming of
Haider-93 caused maximum decrease in MDA and Na accumulation (Figures 4.18a,b).
4.3.5. Discussion
Osmotic and salt stress caused a reduction in seedling growth and biomass
production of both barley varieties. However, seed priming improved the growth and
stress tolerance of barley varieties under both PEG-8000 induced osmotic stress and NaCl
salt stress. Nonetheless, growth improvement was more pronounced under salt stress and
it was associated with better chlorophyll contents, greater accumulation of osmolytes and
decreased MDA accumulation. The improved plant growth and stress tolerance by
osmopriming might be due to up-regulation of gene expression for osmolytes (Kubala et
al., 2015), antioxidants (Souza et al., 2016), dehydrin like proteins (Chen et al., 2012),
aquaporins (Chen et al., 2013b), and improved water relations (Tabassum et al., 2017),
chloroplast ultrastructure (Dai et al., 2017) and chlorophyll photochemistry (Kubala et
al., 2015), while decreased ROS activity and lipid peroxidation (Zhang et al., 2015).
Moreover, Ca2+ used in osmopriming, acts as a secondary messenger, enhances gene
expression for osmolytes, regulates calmodulin like proteins in signaling pathways that
trigger various growth mechanisms and protect plants from stresses (White and Broadley,
2003; Sarwat et al., 2013).
In present study, biopriming improved the plant growth, chlorophyll contents and
accumulation of phenolics, total soluble proteins, proline and glycine betaine under
stressed conditions. The endophytic bacteria in bioprimed plants may have improved
plant growth and development under stressed conditions by enhancing the production of
plant growth promoting hormones viz. auxins, cytokinins and gibberellic acid while
decreasing ethylene production by producing ACC deaminase enzyme which improved 148
the chlorophyll contents and induced stay green character in plants (Mahmood et al.,
2016). Improved stress tolerance by endophytic bacteria in bioprimed plants is associated
with enhanced osmolytes accumulation, antioxidants activity, nutrient uptake and
carbohydrates metabolism (Dimkpa et al., 2009; Chakraborty et al., 2011). Moreover,
endophytic bacteria improves the osmolytes and stress related metabolites by placing the
plants in primed condition that rapidly trigger the expression for osmolytes and stress
related genes expression on exposure to stress (Miliute et al., 2015; Miotto-Vilanova et
al., 2016). In present study, enhanced accumulation and activity of osmolytes by
endophytic bacteria in bioprimed plants decreased the lipid peroxidation by ROS and
improved plant growth and development which is in accordance with Montalbán et al.
(2017).
In present study, seed priming enhanced the accumulation of phenolics, total
soluble proteins, proline and glycine betaine under both PEG-8000 and NaCl induced
osmotic stress that conferred a decrease in lipid peroxidation, and improved chlorophyll
and plant growth of barley. The phenolics accumulation is increased in plants under
stressed conditions and it is associated with improved stress tolerance (Anjum et al.,
2017c). Phenolics protect the plants from ROS (Shetty et al., 2001) and stabilizes cellular
membranes due to the presence of aromatic ring having one or more hydroxyl groups in
their structure (Bhattacharya et al., 2010; Taiz et al., 2015). The soluble proteins protect
the cellular membranes, organelles and organic molecules from oxidative damage by
ROS and enhance hydration of cell structures (Arafa et al., 2009; Wahid and Close,
2007). Moreover, the stress proteins are involved in transport and protection of cell
proteins and repair of damaged proteins (Wahid et al., 2007). The accumulation of proline
and glycine betaine in plants is exalted under stressed conditions to enhance the plant
growth and stress tolerance ability by scavenging and quenching the ROS with
concomitant decrease in MDA accumulation, well maintained cell membrane stability
(Anjum et al., 2017c), and improved tissue water status trough osmotic adjustment (Song
et al., 2017; Tabassum et al., 2017).
The Na accumulation in leaves of both barley varieties was exaggerated under
NaCl salt stress; however, seed priming caused a significant reduction in Na
accumulation, as compared to unprimed control. Although PEG-8000 and NaCl induced
stresses decreased growth of barley but there was no pronounced difference in growth
reduction either by PEG-8000 or NaCl salt stress. However, decreased Na accumulation
and more pronounced growth improvement by seed priming under salt stress indicates 149
that aside form osmotic stress the ionic stress was also responsible for growth reduction in
plants exposed to salt stress. Osmopriming causes a reduction in Na uptake and
accumulation in plants by up-regulating the genes for high affinity potassium transporter
protein 1 (HAK1) and the salt overly sensitive 1 (SOS 1) antiporter (Souza et al., 2016).
Moreover, extracellular Ca2+, used in osmopriming in this study, decreases influx of Na
and efflux of K via non-selective cation channels due to less membrane depolarization by
NaCl in the presence of high Ca2+ concentration (Shabala et al., 2006). In present study
decreased Na content by biopriming is attributed to the endophytic bacteria which reduces
Na uptake by excreting the exopolysaccharides that bind Na and prevent its uptake under
salt stress (Ashraf et al., 2004). Moreover, they enhance the uptake of N, P and K thus
increase the K:Na ratio in salt stressed plants (Dodd and Pérez-Alfocea, 2012).
150
Table 4.94: Analysis of variance for the influence of seed priming on seedling growth of barley under osmotic and salt stressSOV df Mean sum of square
Shoot length
Root length
Shoot fresh
weight
Root fresh
weight
Shoot dry
weight
Root dry
weightVarieties (V) 1 0.20ns 199.96** 61075** 7311* 635** 253ns
Osmotic stress (O) 2 1135.71** 2167.50** 4399939** 1342194** 57825* 11889**
Seed priming (T) 3 121.79** 197.10** 732617** 298075** 25183** 3081**
V×O 2 9.59** 2.74ns 30856** 42206** 890** 21ns
V×T 3 6.69** 12.17** 11988ns 22464** 851* 307*
O×T 6 23.82** 22.35** 92932** 31821** 5743** 1110**
V×O×T 6 40.07** 10.35** 28759** 10099** 1679** 612**
Error 72 1.61 1.73 4953 1123 69 88Total 95
Table 4.95: Analysis of variance for the influence of seed priming on chlorophyll and total soluble phenolics contents in barley under osmotic and salt stressSOV df Mean sum of square
Chlorophyll a content
Chlorophyll b content
Total soluble phenolics
Varieties (V) 1 0.0088** 0.0006* 2546.3**
Osmotic stress (O) 2 0.1352** 0.0297** 21157.5**
Seed priming (T) 3 0.0114** 0.0046** 10446.2**
V×O 2 0.0009* 0.0008** 208.9*
V×T 3 0.0017** 0.0001ns 40.0ns
O×T 6 0.0014** 0.0001ns 1311.2**
V×O×T 6 0.0014** 0.0005** 532.8**
Error 72 0.0003 0.0001 62.6Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
151
Shoo
t len
gth
(cm
)R
oot l
engt
h (c
m)
Shoo
t fre
sh w
eigh
t (m
g)
152
Roo
t fre
sh w
eigh
t (m
g)Sh
oot d
ry w
eigh
t (m
g)R
oot d
ry w
eigh
t (m
g)
153
Chl
orop
hyll
a co
nten
t (m
g g-1
FW
)C
hlor
ophy
ll b
cont
ent (
mg
g-1 F
W)
Tot
al so
lubl
e ph
enol
ics (
µg g
-1 F
W)
154
Table 4.96: Analysis of variance for the influence of seed priming on osmolytes accumulation in barley under osmotic and salt stressSOV df Mean sum of square
Total soluble proteins
Free proline content
Glycine betaine content
Varieties (V) 1 0.0065** 0.0067** 0.0028*
Osmotic stress (O) 2 0.5102** 0.0440** 0.3887**
Seed priming (T) 3 0.0381** 0.0213** 0.0287**
V×O 2 0.0029** 0.0093** 0.0028*
V×T 3 0.0006ns 0.0004ns 0.0005ns
O×T 6 0.0018** 0.0009* 0.0019**
V×O×T 6 0.0023** 0.0023** 0.0027**
Error 72 0.0005 0.0003 0.0006Total 95
Table 4.97: Analysis of variance for the influence of seed priming on malondialdehyde and Na contents in barley under osmotic and salt stressSOV df Mean sum of square
Malondialdehyde Na contentVarieties (V) 1 293.61** 7340*
Osmotic stress (O) 2 3145.24** 24376762**
Seed priming (T) 3 83.49** 26542**
V×O 2 2.45ns 7757**
V×T 3 50.92** 2749ns
O×T 6 11.16ns 23927**
V×O×T 6 46.89** 2934*
Error 72 9.29 1259Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
155
Tot
al so
lubl
e pr
otei
ns (m
g g-1
FW
)Fr
ee p
rolin
e (µ
mol
g-1
FW )
Gly
cine
bet
aine
(µm
ol g
-1 FW
)
156
Mal
ondi
alde
hyde
(µm
ol g
-1 FW
)N
a co
nten
t (m
g g-1
DW
)
157
4.4. Influence of seed priming in improving the resistance against cadmium stress in barley4.4.1. Seedling growth
Cadmium stress and seed priming significantly affected shoot and root length,
shoot and root fresh weight, and shoot and root dry weight. The tested barley varieties
significantly differed for root length, shoot fresh weight, and shoot dry weight; however,
did not differ significantly for root and shoot fresh weight, and root dry weight. Likewise,
the interaction between varieties and Cd stress was significant for shoot and root length,
shoot and root fresh weight, and root dry weight while non-significant for shoot dry
weight. The interactions between varieties and seed priming, and Cd stress and seed
priming was non-significant for shoot length while significant for root length, shoot and
root fresh weight, and shoot and root dry weight. However, three interaction among
varieties, Cd stress and seed priming was significant for shoot and root length, shoot and
root fresh weight as well as shoot and root dry weight (Table 4.98).
Seedling growth of barley was decreased by Cd toxicity stress, as compared to
control. The reduction in seedling growth was increased with severity of Cd stress in both
varieties. However, Frontier-87 showed more tolerance to Cd under moderate stress while
Haider-93 performed better under severe stress. Seed priming treatments improved the
seedling growth of both barley varieties under all levels of Cd stress, as compared to
control. Under moderate Cd stress, biopriming of Haider-93 caused maximum increase in
shoot length, and shoot fresh and dry weights. However, root length, root fresh and dry
weights were improved most by osmopriming of Haider-93. Under severe Cd stress,
maximum increase in shoot length occurred by biopriming of Frontier-87, while,
maximum increase in shoot fresh and dry weights was caused by osmopriming of Haider-
93. Nonetheless, biopriming of Haider-93 caused greatest improvement in root length,
and root fresh and dry weights (Figures 4.19a-c, 4.20a-c).
4.4.2. Chlorophyll contents
The chlorophyll a and b contents were significantly affected by Cd stress and seed
priming. The varieties significantly differed for chlorophyll a content while did not differ
significantly for chlorophyll b content. However, the interactions between varieties and
Cd stress, and varieties and seed priming were non-significant for both chlorophyll a and
b contents. The interaction between Cd stress and seed priming was non-significant for
chlorophyll a but significant for chlorophyll b content. The there way interaction among
varieties, Cd stress and seed priming was significant for chlorophyll a and b contents
158
(Table 4.99). A substantial reduction in chlorophyll a and b contents of barley was caused
by Cd stress, as compared to control. The decrease in chlorophyll contents was increased
with increase in Cd stress levels. However, greater reductions occurred in Fronteirs-87
under each level of Cd stress. Seed priming improved the chlorophyll a and b contents in
both varieties under Cd stress, as compared to control. Under moderate Cd stress,
biopriming of Haider-93 exhibited greatest improvement in chlorophyll a and b contents.
However, under severe Cd stress, maximum increase in chlorophyll a and b contents was
caused by osmopriming of Haider-93 (Figures 4.21a,b).
4.4.3. Osmolytes accumulation
The total soluble phenolics, total soluble proteins, free proline and glycine betaine
contents were significantly affected by Cd stress and seed priming. However, varieties
significantly differed for total soluble phenolics and total soluble proteins while did not
differ significantly for free proline and glycine betaine contents. Significant interactions
between varieties and Cd stress, and varieties and seed priming occurred for total soluble
proteins while were non-significant for total soluble phenolics, proline and glycine
betaine contents. Nonetheless, interaction between Cd stress and seed priming as well as
three way interaction among varieties, Cd stress and seed priming were significant for
total soluble phenolics, total soluble proteins, free proline and glycine betaine contents
(Tables 4.99, 4.100).
Osmolytes accumulation was increased by Cd stress in both barley varieties, as
compared to control. The osmolytes accumulation was increased with increase in stress
severity. Haider-93 accumulated more osmolytes than Frontier-87. Seed priming
treatments further improved the accumulation of osmolytes in both varieties under all
levels of Cd stress, as compared to control. Under moderate Cd stress, total soluble
phenolics and glycine betaine contents were exalted most by biopriming of Haider-93,
while, maximum increase in total soluble proteins and proline contents was caused by
osmopriming of Haider-93. Under severe Cd stress, the greatest increase in total soluble
phenolics, total soluble proteins and glycine betaine contents was occurred by
osmopriming of Haider-93; however, the influence of biopriming of Haider-93 on glycine
betaine content was at par with osmopriming of Haider-93. Proline content was improved
most by osmopriming of Frontier-87 (Figures 4.21a, 4.22a-c).
4.4.4. Lipid peroxidation and cadmium content
Accumulation of MDA and Cd was significantly affected by Cd toxicity and seed
priming; the varieties also differed significantly for MDA and Cd contents. The 159
interaction between varieties and Cd stress was ssignificant for both MDA and Cd
contents. However, the interaction between varieties and seed priming was significant for
seed priming while non-significant for Cd content. Intercation between Cd stress and seed
priming was non-significant for MDA but significant for Cd content. The three way
interation among varieties, Cd stress and seed priming was significant for both MDA and
Cd contents (Table 4.101). Accumulation of MDA and Cd in barley varieties was
aggravated by Cd stress, as compared to control. The MDA and Cd accumulation was
increased with increase in Cd stress levels (severe > moderate > control). However,
Haider-93 accumulated less MDA as well as Cd than Frontier-87. Moreover, seed
priming decreased the accumulation of MDA and Cd in both varieties under Cd stress, as
compared to control. Under moderate Cd stress, least MDA and Cd accumulation
occurred by biopriming of Haider-93 while under severe stress osmopriming of Haider-93
was superior in decreasing the MDA as well as Cd accumulation (Figures 4.23a,b).
4.4.5. Discussion
Cadmium stress caused a reduction in seedling growth and biomass production in
both barley varieties and the decrease was proportional to the stress severity. Nonetheless,
seed priming improved stress tolerance by improving leaf chlorophyll contents,
accumulation of phenolics, total soluble proteins, proline and glycine betaine, while
reducing MDA and Cd contents as indicated by improved seedling growth of barley, as
compared to control. This might be attributed to enhanced accumulation of transcription
factors and metabolites that trigger the gene expression for osmolytes, heat shock proteins
and antioxidants (Kibinza et al., 2011; Chen and Arora, 2013), which reduces ROS
activity, lipid peroxidation and improves water relations ultimately improving the plant
growth and stress tolerance (Chen and Arora, 2013; Tabassum et al., 2017). In present
study, the Ca2+ used in osmopriming, acts as a secondary messenger that enhances gene
expression for osmolytes accumulation (White and Broadley, 2003). Moreover, Ca2+ acts
in the signaling pathways and regulates the calmodulin like proteins to trigger various
growth mechanisms and protect plants from damaging effects of stress (Sarwat et al.,
2013).
In present study, the biopriming was effective in improving the seedling growth
and stress tolerance of barley through enhanced chlorophyll contents and osmolytes
accumulation. This might be due to endophytic plant growth promoting bacteria used in
biopriming that improves the plant growth by modulating the production of
phytohormones i.e. increasing auxin, cytokinins and gibberellic acid while decreasing the 160
ethylene production by producing ACC deaminase enzyme (Miliute et al., 2015; Santoyo
et al., 2016). Moreover, endophytic bacteria place the metabolism of plants in primed
state that enable greater and rapid accumulation of transcription factors for osmolytes and
stress related genes expression (Theocharis et al., 2012; Miotto-Vilanova et al., 2016).
Endophytic bacteria also produce osmolytes that act synergistically with plant produced
osmolytes under stressed conditions (Dimkpa et al., 2009) which decrease the lipid
peroxidation by ROS activity and improve the plant growth and development (Theocharis
et al., 2012; Montalbán et al., 2017).
In present study, the seed priming increased soluble phenolics and proteins
accumulation which resulted in decreased MDA accumulation, and increased chlorophyll
contents and seedling growth, as compared to unprimed control, under Cd toxicity. The
soluble phenolics contain aromatic ring in their structures which might have protected and
stabilized cellular membranes under stressed conditions (Taiz et al., 2015), enhanced
ROS scavenging in cells (Shetty et al. 2001), and improved the stress tolerance and plant
growth. Likewise, soluble proteins protect the biological membranes and cellular
organelles from oxidative damage to lipids, proteins and nucleic acid (Arafa et al., 2009),
which improves stress tolerance by hydration of cellular structures (Wahid and Close,
2007). In current study, free leaf proline and glycine betaine contents were increased in
barley by seed priming under Cd toxicity stress which are associated with decrease in
MDA accumulation, improved cell membrane stability (Anjum et al., 2017c); moreover,
they improve water relations by osmotic adjustment (Tabassum et al., 2017), ultimately
improving the plant growth and development under stressed conditions (Song et al.,
2017).
Cadmium content in barley was increased with increase in Cd toxicity; however,
seed priming ameliorated the effects of Cd toxicity on plant growth by decreasing the Cd
contents. In osmoprimed plants, Ca2+ might have decreased Cd concentration in barley
due to restricted uptake and/or translocation to aerial plant parts (Abd_Allah et al., 2017).
The Ca+2 also improves the uptake of K while decreases Cd uptake resulting in decreased
Cd contents in plants under Cd toxicity (Kurtyka et al. 2008). However, decrease in Cd
content in bioprimed barley plants could be due to adsorption and immobilization of toxic
ions from solution by endophytic bacteria through production of extracellular proteins
and polysaccharides which can bind and precipitate the metals ions (Burd et al., 1998). In
this way, the endophytic bacteria may have reduced toxic effects of Cd by improving the
growth and dry biomass of host plant (Montalbán et al., 2017).161
Table 4.98: Analysis of variance for the influence of seed priming on seedling growth of barley under cadmium stressSOV df Mean sum of square
Shoot length
Root length
Shoot fresh
weight
Root fresh
weight
Shoot dry
weight
Root dry
weightVarieties (V) 1 0.04ns 65.21* 7030* 70ns 8470.7** 10.0ns
Cadmium stress (C) 2 381.96** 1200.43** 7209818** 667839** 13339.1** 1568.8**
Seed priming (T) 3 18.98** 203.38** 362979** 260575** 4098.7** 477.5**
V×C 2 76.99** 39.67* 6048* 90552** 88.2ns 192.5**
V×T 3 8.59ns 58.42** 5832* 19127** 399.2** 51.0**
C×T 6 8.74ns 182.40** 76073** 56896** 181.3** 116.9**
V×C×T 6 17.34** 28.61* 48060** 39968** 294.5** 68.5**
Error 72 4.24 10.31 1517 799 41.3 2.6Total 95
Table 4.99: Analysis of variance for the influence of seed priming on chlorophyll and total soluble phenolics contents in barley under cadmium stressSOV df Mean sum of square
Chlorophyll a content
Chlorophyll b content
Total soluble phenolics
Varieties (V) 1 0.0201** 0.0001ns 1319.8**
Cadmium stress (C) 2 0.1019** 0.0314** 17076.3**
Seed riming (T) 3 0.0083** 0.0042** 5774.1**
V×C 2 0.0002ns 0.0002ns 19.3ns
V×T 3 0.0002ns 0.0001ns 111.3ns
C×T 6 0.0002ns 0.0002* 109.7*
V×C×T 6 0.0004* 0.0003* 126.9*
Error 72 0.0002 0.0001 45.9Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
162
Shoo
t len
gth
(cm
)R
oot l
engt
h (c
m)
Shoo
t fre
sh w
eigh
t (m
g)
163
Roo
t fre
sh w
eigh
t (m
g)Sh
oot d
ry w
eigh
t (m
g)R
oot d
ry w
eigh
t (m
g)
164
Chl
orop
hyll
a co
nten
t (m
g g-1
FW
)C
hlor
ophy
ll b
cont
ent (
mg
g-1 F
W)
Tot
al so
lubl
e ph
enol
ics (
µg g
-1 F
W)
165
Table 4.100: Analysis of variance for the influence of seed priming on osmolytes accumulation in barley under cadmium stressSOV df Mean sum of square
Total soluble proteins
Free proline content
Glycine betaine content
Varieties (V) 1 0.0035** 0.0011ns 0.0001ns
Cadmium stress (C) 2 0.8827** 0.6065** 0.8822**
Seed priming (T) 3 0.0501** 0.0282** 0.0533**
V×C 2 0.0047** 0.0021ns 0.0008ns
V×T 3 0.0016* 0.0012ns 0.0013ns
C×T 6 0.0029** 0.0034** 0.0015*
V×C×T 6 0.0011* 0.0036** 0.0022**
Error 72 0.0004 0.0007 0.0007Total 95
Table 4.101: Analysis of variance for the influence of seed priming on malondialdehyde and cadmium contents in barley under cadmium stressSOV df Mean sum of square
Malondialdehyde Cadmium contentVarieties (V) 1 53.97** 2372.2**
Cadmium stress (C) 2 5654.79** 195715.9**
Seed priming (T) 3 61.65** 1113.1**
V×C 2 25.47* 545.3**
V×T 3 19.96* 76.3ns
C×T 6 11.35ns 325.5**
V×C×T 6 26.06** 99.8*
Error 72 5.81 41.2Total 95
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
166
Tot
al so
lubl
e pr
otei
ns (m
g g-1
FW
)Fr
ee p
rolin
e (µ
mol
g-1
FW )
Gly
cine
bet
aine
(µm
ol g
-1 FW
)
167
Mal
ondi
alde
hyde
(µm
ol g
-1 FW
)C
d co
nten
t (µg
g-1
DW
)
168
4.5. Influence of seed priming in improving the resistance against terminal heat stress in barley4.5.1. Stand establishment
Seed priming significantly affected final emergence percentage, time taken to
50% emergence, mean emergence time and emergence index of barley (Table 4.102).
Final emergence percentage and emergence index were increased while time taken to
50% emergence and mean emergence time of barley was decreased by seed priming, as
compared to unprimed control. Maximum improvement was caused by osmopriming and
it was followed by hydropriming (Table 4.103).
4.5.2. Agronomic attributes
Heat stress and seed priming significantly affected plant height, number of
productive tillers, spike length, number of spikelets and grains per spike, 100-grain
weight, grain and biological yield, and harvest index of barley (Table 4.104, 4.107).
However, interaction between heat stress and seed priming was non-significant for plant
height, number of productive tillers, spike length, number of spikelets per spike and
biological yield; while, significant for number of grains per spike, 100-grain weight, grain
yield and harvest index of barley (Table 4.104, 4.107). Heat stress caused a reduction in
plant height, number of productive tillers, spike length, number of spikelets and grains per
spike, 100-grain weight, grain and biological yield, and harvest index of barley, as
compared to control. However, seed priming treatments improved all these traits, as
compared to unprimed control, and hydropriming was most effective followed by
osmopriming (Tables 4.105, 4.106, 4.108-4.110). Furthermore, the greatest improvement
in number of grains per spike, 100-grain weight and harvest index was caused by
hydropriming and osmopriming at normal temperature and under heat stress, respectively,
as compared to unprimed control (Tables 4.105, 4.106, 4.108-4.110).
4.5.3. Gas exchange attributes
Photosynthesis, stomatal conductance, transpiration, internal CO2 concentration
and stomatal limitation were significantly affected by terminal heat stress at 7 and 14
DAT. However, CUE was not significantly affected at 7 DAT but significantly affected at
14 DAT by heat stress. Seed priming significantly affected photosynthesis and CUE at 7
as well as 14 DAT, while transpiration was significantly affected at 7 DAT only.
Nonetheless, stomatal conductance, stomatal limitation and intercellular CO2
concentration were not affected significantly by seed priming. Interaction of heat stress
169
and seed priming was significant for photosynthesis, transpiration and CUE at both 7 and
14 DAT; while,
170
Table 4.102: Analysis of variance for the influence of seed priming on emergence of barley SOV df Final
emergence percentage
Mean emergence time
Time taken to 50% emergence
Emergence index
Seed priming (T) 2 324.06* 0.594* 0.819* 0.123*
Error 15 67.88 0.128 0.162 0.010Total 17
SOV = Source of variation, df = Degree of freedom, * = Significant at p≤0.05
Table 4.103: Influence of seed priming on emergence attributes of barleyTreatments Final emergence
percentage (%)Mean emergence
time (days)Time taken to 50% emergence (days)
Emergence index
Control 58.34 b 5.29 a 4.71 a 0.68 bHP 69.45 a 4.88 ab 4.14 b 0.89 aOP 72.22 a 4.68 b 4.02 b 0.95 aLSD≤ 0.05 10.139 0.4405 0.4954 0.1229
Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming
Table 4.104: Analysis of variance for the influence of seed priming on growth and yield related traits of barley under terminal heat stressSOV df Plant height No. of
productive tillers
Spike length No. of spikelets per
spikeHeat (H) 1 211.27** 61.361** 1.217* 3.373*
Seed priming (T) 2 88.83* 1.083* 2.170** 11.820**
H×T 2 1.21ns 0.361ns 0.149ns 1.079ns
Error 30 20.56 0.283 0.277 0.700Total 35
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.105: Influence of seed priming on plant height and number of productive tillers per pot of barley under terminal heat stressTreatments Plant height (cm) No. of productive tillers per pot
Control Heat Mean Control Heat MeanControl 49.92 45.23 47.57 B 4.67 2.17 3.42 BHP 54.94 50.63 52.78 A 5.50 2.50 4.00 AOP 54.30 48.76 51.53 A 5.00 2.67 3.83 ABMean 53.05 A 48.21 B 5.06 A 2.44 B
LSD≤ 0.05Heat stress = 3.0869, Seed priming = 3.7807
Heat stress = 0.3624, Seed priming = 0.4438
Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming
171
Table 4.106: Influence of seed priming on spike length and number of spikelets per spike of barley under terminal heat stressTreatments Spike length (cm) No. of spikelets per spike
Control Heat Mean Control Heat MeanControl 9.64 9.20 9.42 B 12.00 11.55 11.78 BHP 10.46 9.92 10.19 A 14.22 12.94 13.58 AOP 10.18 10.07 10.13 A 13.45 13.33 13.39 AMean 10.09 A 9.73 B 13.22 A 12.61 B
LSD≤ 0.05Heat stress = 0.3582, Seed priming = 0.4388
Heat stress = 0.5695, Seed priming = 0.3654
Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming
Table 4.107: Analysis of variance for the influence of seed priming on yield related traits, yield and harvest index of barley under terminal heat stressSOV df No. of
grains per spike
100-grain weight
Grain yield
Biological yield
Harvest index
Heat (H) 1 502.36** 2.127** 69.417** 178.089** 3765.5**
Seed priming (T) 2 22.25** 0.431** 2.121** 7.228** 111.5**
H×T 2 13.03* 0.113* 0.803** 0.628ns 62.8*
Error 30 2.42 0.030 0.131 1.206 16.1Total 35
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.108: Influence of seed priming on number of grains per spike and 100-grain weight of barley under terminal heat stressTreatments No. of grains per spike 100-grain weight (g)
Control Heat Mean Control Heat MeanControl 18.44 b 9.78 e 14.11 B 3.71 ab 3.00 d 3.36 BHP 20.55 a 11.87 d 16.21 A 3.89 a 3.51 bc 3.70 AOP 19.20 ab 14.13 c 16.66 A 3.85 a 3.48 c 3.67 AMean 19.40 A 11.92 B 3.82 A 3.33 B
LSD≤ 0.05Heat stress = 1.0588, Seed priming = 1.2968, Interaction = 1.8339
Heat stress = 0.1176, Seed priming = 0.1441, Interaction = 0.2037
Table 4.109: Influence of seed priming on grain yield and biological yield per pot of barley under terminal heat stressTreatments Grain yield (g per pot) Biological yield (g per pot)
Control Heat Mean Control Heat MeanControl 3.17 c 0.62 e 1.90 B 7.87 3.39 5.63 BHP 4.39 a 1.02 de 2.71 A 9.59 4.70 7.15 AOP 3.71 b 1.29 d 2.50 A 8.65 4.68 6.67 AMean 3.76 A 0.98 B 8.70 A 4.26 B
LSD≤ 0.05Heat stress = 0.2467, Seed priming = 0.3022, Interaction = 0.4273
Heat stress = 0.7477, Seed priming = 0.9158
Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming
172
Table 4.110: Influence of seed priming on harvest index (%) of barley under terminal heat stressTreatments Control Heat MeanControl 40.62 b 18.74 d 29.68 BHP 46.11 a 21.97 d 34.04 AOP 43.22 ab 27.88 c 35.55 AMean 43.32 A 22.86 BLSD≤ 0.05 Heat stress = 2.7293, Seed priming = 3.3427, Interaction = 4.7273
Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming
Table 4.111a: Analysis of variance for the influence of seed priming on gas exchange attributes of barley under terminal heat stressSOV df Photosynthesis Stomatal
conductanceTranspiration
7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DATHeat (H) 1 169.56** 258.19** 0.2467** 0.0920** 77.998** 107.088**
Seed priming (T) 2 93.33** 81.90** 0.0094ns 0.0032ns 9.161** 5.211ns
H×T 2 40.93* 28.55* 0.0134* 0.0028ns 6.095* 6.468*
Error 30 12.01 8.32 0.0039 0.0023 1.687 1.896Total 35
Table 4.111b: Analysis of variance for the influence of seed priming on gas exchange attributes of barley under terminal heat stressSOV df intercellular CO2
concentrationStomatal limitation
Carboxylation use efficiency
7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DATHeat (H) 1 40401** 23053** 0.248** 0.146** 3.03E-05ns 0.0013*
Seed priming (T) 2 579ns 5329ns 0.003ns 0.033ns 2.15E-03** 0.0048**
H×T 2 2416* 3081ns 0.014* 0.019ns 9.35E-04* 0.0007*
Error 30 667 2678 0.004 0.017 2.73E-04 0.0002Total 35
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
173
PN ( μ
mol
CO
2 m
-2 s-1
)gs
(mm
ol H
2O m
-2 s-1
)C
i (μm
ol C
O2 m
ol-1)
174
Tr
(mm
ol H
2O m
-2 s-1
)L
s (%
)C
UE
(mol
m-2 S
-1)
175
significant for stomatal conductance, internal CO2 concentration and stomatal limitation
at 7 DAT but non-significant at 14 DAT (Tables 4.111a,b).
Gas exchange attributes were negatively affected by terminal heat stress as
compared to control; however, seed priming treatments exerted ameliorating effect by
improving the gas exchange attributes. Under no heat stress, maximum improvement in
photosynthesis and CUE was caused by hydropriming at 7 and 14 DAT, as compared to
unprimed control. The greatest improvement in stomatal conductance and transpiration
was recorded by osmopriming at 7 DAT and hydropriming at 14 DAT, as compared to
unprimed control. On the other hand, the greatest decrease in internal CO2 concentration
was caused by hydropriming at 7 DAT and osmopriming at 14 DAT; while, stomatal
limitation was increased in response to seed priming treatments from 7 to 14 DAT, as
compared to unprimed control. However, under terminal heat stress, photosynthesis,
stomatal conductance, transpiration and CUE was improved to a maximum by
hydropriming and osmopriming from 7 to 14 DAT, respectively, as compared to
unprimed control. However, maximum decrease in internal CO2 concentration was caused
by osmopriming at 7 DAT and hydropriming at 14 DAT, as compared to unprimed
control. The stomatal limitation was decreased by hydropriming at 7 DAT; however,
increased by seed priming treatments at 14 DAT, as compared to unprimed control
(Figures 4.24a-f, 4.25a-f).
4.5.4. Chlorophyll a fluorescence attributes
Heat stress significantly affected maximal fluorescence (Fm), variable
fluorescence (Fv), Fv/Fm and ETR at 14 DAT but these attributes were not significantly
affected at 7 DAT; while, minimal fluorescence (Fo) and QY were not affected
significantly by terminal heat stress either at 7 and 14 DAT. Seed priming did not affect
chlorophyll a fluorescence attributes significantly at 7 and 14 DAT. The interaction
between heat stress and seed priming was significant for Fm, Fv and Fv/Fm at 7 DAT
while non-significant for these traits at 14 DAT. Moreover, the interaction of heat stress
and seed priming was significant for ETR at 7 and 14 DAT, while, QY was not
significantly affected at 7 DAT but significantly affected at 14 DAT (Table 4.112a,b).
Terminal heat stress did not decrease the Fm, Fv and Fv/Fm at 7 DAT but at 14
DAT these traits were decreased by heat stress, as compared to control. However, at 7
DAT seed priming partially improved the Fm, Fv and Fv/Fm with maximum
improvement caused by hydropriming under normal and osmopriming under heat stressed
conditions, as compared to unprimed control. Electron transport rate was decreased by 176
heat stress at 14 DAT; while, seed priming improved the ETR at both 7 and 14 DAT, as
compared to
177
Table 4.112a: Analysis of variance for the influence of seed priming on chlorophyll a fluorescence attributes of barley under terminal heat stressSOV df Minimal
fluorescence (F0)Maximal fluorescence
(Fm)Variable
fluorescence (Fv)7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DAT
Heat (H) 1 720.0ns 1626.8ns 67ns 141501** 1225 ns 101867**
Seed priming (T) 2 90.3ns 961.8ns 6274ns 1997ns 5394ns 1965ns
H×T 2 63.7ns 588.0ns 15861* 3826ns 13977* 2910ns
Error 30 203.8 424.6 4676 4736 3477 3286Total 35
Table 4.112b: Analysis of variance for the influence of seed priming on chlorophyll a fluorescence attributes of barley under terminal heat stressSOV df Maximum
efficiency of PSII (Fv/Fm)
Quantum yield of PSII (QY)
Electron transport rate (ETR)
7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DATHeat (H) 1 0.0017ns 0.0235** 2025ns 21025** 0.0007ns 0.0336ns
Seed priming (T) 2 0.0007ns 0.0018ns 7375ns 2003ns 0.0132ns 0.0111ns
H×T 2 0.0018* 0.0015ns 9027* 5986* 0.0015ns 0.0552*
Error 30 0.0005 0.0023 2661 1662 0.0130 0.0148Total 35
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
178
Min
imal
fluo
resc
ence
(Fo)
Max
imal
fluo
resc
ence
(Fm
)V
aria
ble
fluor
esce
nce
(Fv)
179
Max
imum
qua
ntum
yie
ld (F
v/Fm
)Q
uant
um y
ield
of P
SII (
QY
)E
lect
ron
tran
spor
t rat
e (E
TR
)
180
unprimed control. It was noticed that hydropriming was effective in improving ETR
under control while osmopriming was superior under heat stress. Compared with control,
QY was decreased by heat stress at 14 DAT while improved by osmopriming, as
compared to unprimed control (Figures 4.26a-f, 4.27a-f).
4.5.5. Chlorophyll contents
The chlorophyll contents of barley were significantly affected by terminal heat
stress at 7 as well as 14 day after treatment (DAT). Seed priming as well as interaction of
heat stress and seed priming significantly affected chlorophyll a at 14 DAT, and
chlorophyll b and total chlorophyll contents at 7 and 14 DAT. However, chlorophyll a
content was not affected significantly by seed priming, interaction of heat stress and seed
priming at 7 DAT (Table 4.113). Heat stress decreased the biosynthesis of chlorophyll in
barley as compared to control. However, seed priming improved the chlorophyll contents
under normal as well as heat stressed conditions. Chlorophyll a, b and total chlorophyll
contents were improved by hydropriming and osmopriming under normal and under heat
stressed conditions at 7 and 14 DAT, respectively, as compared to unprimed control
(Figures 4.28a-f).
4.5.6. Biochemical attributes
Terminal heat stress significantly affected MDA and cell membrane stability at 7
as well as 14 DAT; while, total soluble phenolics were not significantly affected at 7
DAT while significantly affected at 14 DAT. Likewise, seed priming significantly
affected MFA, total soluble phenolics and cell membrane stability at both 7 and 14 DAT.
However, the interaction between heat stress and seed priming was significant for total
soluble phenolics, MDA and cell membrane stability at both 7 and 14 DAT (Table 4.114).
Heat stress increased the accumulation of phenolics and MDA while decreased cell
membrane stability as compared to control at both 7 and 14 DAT. However, seed priming
ameliorated the negative effects of heat stress by decreasing the accumulation of MDA
while increased the phenolics and cell membrane stability, as compared to unprimed
control. Under no heat stress, hydropriming caused maximum decrease in MDA and
increase in phenolics and cell membrane stability, as compared to unprimed control.
However, under terminal heat stress, osmopriming was superior in decreasing MDA, and
improving phenolics and cell membrane stability at both 7 and 14 DAT, as compared to
unprimed control (Figures 4.29a-f).
181
Table 4.113: Analysis of variance for the influence of seed priming on chlorophyll contents of barley under terminal heat stressSOV df Chlorophyll a Chlorophyll b Total chlorophyll
7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DATHeat (H) 1 0.0961** 0.0374** 0.0107* 0.0030* 0.1708** 0.0633**
Seed priming (T) 2 0.0006ns 0.0034** 0.0071* 0.0037** 0.0098* 0.0135**
H×T 2 0.0001ns 0.0030* 0.0074* 0.0030** 0.0087* 0.0103**
Error 30 0.0003 0.0006 0.0017 0.0004 0.0022 0.0018Total 35
Table 4.114: Analysis of variance for the influence of seed priming on total soluble phenolics, malondialdehyde and cell membrane stability of barley under terminal heat stressSOV df Total soluble
phenolics Malondialdehyde Cell membrane
stability7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DAT
Heat (H) 1 110.8ns 3026.3** 1530.50** 681.21** 33.54** 32.97*
Seed priming (T) 2 2031.6* 1893.8** 101.49** 76.30* 259.17** 634.42**
H×T 2 2125.4* 1098.7* 47.52* 114.08** 7.40* 32.26**
Error 30 538.9 270.0 12.21 19.89 1.95 4.68Total 35
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
182
Chl
orop
hyll
a co
nten
t (m
g g-1
FW
)C
hlor
ophy
ll b
cont
ent (
mg
g-1 F
W)
Tot
al c
hlor
ophy
ll co
nten
t (m
g g-1
FW
)
183
Tot
al so
lubl
e ph
enol
ics (
µg g
-1 F
W)
Mal
ondi
alde
hyde
(µm
ol g
-1 FW
)C
ell m
embr
ane
stab
ility
(%)
184
4.5.7. Discussion
Emergence of barley was enhanced by seed priming as compared to control. There
was an increase in emergence percentage and emergence index while decrease in
emergence time. Seed priming improves the emergence with concomitant decrease in
emergence time by allowing the germination metabolism to occur without actual
germination due to controlled hydration of seed (Farooq et al., 2006a). Better emergence
by seed priming is attributed to improved activity of hydrolytic enzymes and
carbohydrate metabolism (Farooq et al. 2009b). It has been observed that seed priming
causes de novo synthesis of the α-amylase enzyme (Lee and Kim, 2000), while, increases
activities of β-amylase, root system dehydrogenase and catalase enzymes (He et al.,
2002). In present study, the Ca2+ used in osmopriming, is involved in structural integrity
and permeability of cell membrane which results in decreased cell membrane leakage
(Posmyk et al., 2001; Hepler, 2005) resulting in improved germination and seedling
vigour (Ruan et al., 2002a, b).
Terminal heat stress decreased the performance of barley by reducing growth,
yield and photosynthesis while increasing lipid peroxidation. However, seed priming
improved the photosynthesis and ETR while decreased lipid peroxidation through
enhanced accumulation of phenolics ultimately increasing the grain yield and harvest
index. Seed priming improves the stress tolerance by exalting the accumulation of
transcription factors and metabolites which rapidly and greatly up-regulates the gene
expression for osmolytes and antioxidants on exposure to stress (Kibinza et al., 2011;
Chen and Arora, 2013), thereby improving the water relations and decreasing lipid
peroxidation (Tabassum et al., 2017). Moreover, in present study the Ca2+ used in
osmopriming, is involved in enhancing the gene expression for osmolytes, and improves
plant growth and stress tolerance by regulating the calmodulin like proteins in signaling
pathways (White and Broadley, 2003; Sarwat et al., 2013).
In present study, the decrease in photosynthesis by terminal heat stress was
associated with a reduction in stomatal conductance and intercellular CO2 concentration
which might be due to closure of stomata as an early response of plants to heat stress
(Fahad et al., 2017); nonetheless, these reductions were less in seed primed plants
compared with unprimed plants especially at earlier time following heat stress. Wang et
al. (2014) suggested that stomatal conductance is regulated more by leaf tissue water
status rather than ABA production under abiotic stress. Seed priming improves the tissue
water status through osmotic adjustment by exaggerating osmolytes accumulation which 185
enhances stomatal conductance and photosynthesis under stressed conditions (Tabassum
et al., 2017; Abid et al., 2018). In present study improved stomatal conducatance by
osmopriming may be due to Ca2+ signaling which regulates the stomatal aperture because
stomatal closure is induced by increased concentration of external Ca2 + thus affecting the
CO2 exchange rate (Hochmal et al., 2015).
Chlorophyll pigments are degraded by high temperature which causes drastic
reductions in photosynthesis due to decreased CUE of Rubisco and photochemical
efficiency of PSII (Salvucci and Brandner, 2004a,b; Feng et al., 2014). Similarly, in
present study, decrease in chlorophyll contents, CUE, photochemical efficiency of PSII
and photosynthesis occurred under terminal heat stress, as compared to control. However,
seed priming improved biosynthesis of chlorophyll, CUE, Fv/Fm, QY and ETR under
heat stress, as compared to unprimed control. In seed primed plants, cellular membranes
and organelles are better protected by enhanced accumulation of osmolytes and
antioxidants activity resulting in improved chloroplast ultrastructure, chlorophyll
contents, photosynthesis and chlorophyll photochemistry (Dai et al., 2017; Abid et al.,
2018). In present study, improved chlorophyll, photosynthesis and chlorophyll
photochemistry by osmopriming might be attributed to Ca2+ which is structural
component of PSII, and regulates the NADK2 gene that encodes for NAD+ in chloroplast
and deletion or down regulation of this gene results in decreased chlorophyll biosynthesis,
QY and ETR (Hochmal et al., 2015). Moreover, increase in extracellular Ca2+ enhances
the ETR in cyclic electron flow (Terashima et al., 2012).
In present study, heat stress caused a reduction in cell membrane stability due to
increased lipid peroxidation; however, seed priming accumulated phenolics in greater
quantities which improved cell membrane stability and decreased MDA accumulation, as
compared to unprimed control. This might be due to suppression of photosynthesis by
terminal heat stress which leads to greater production of ROS causing oxidative damage
to the cellular membranes, photosynthetic machinery, proteins, lipids and nucleic acid
(Xiong et al., 2002). However, seed priming induces osmolytes and antioxidants defense
which counteracts the ROS activity and lipid peroxidation leading to improved cell
membrane stability (Chen and Arora, 2013). In present study, phenolics were enhanced
by seed priming which contain aromatic ring in their structures with one or more
hydroxyl groups, and protect and stabilize cellular membranes and organelles under
stressed conditions (Taiz et al., 2015), by enhanced scavenging of ROS in cells ultimately
improving stress tolerance and plant growth (Shetty et al. 2001; Song et al., 2017).186
In present study, terminal heat stress imposed deleterious effects on yield and
related traits, and harvest index of barley. However, improved photosynthesis and better
protection of cellular membranes as recorded in present study, and improved water
relations by seed priming might have improved the pollen viability and assimilate
translocation leading to improved grain setting and grain weight (Mohammed and
Tarpley, 2009; Mohammed et al., 2015; Abid et al., 2018). These gains from
osmopriming were translated into higher number of productive tillers, number of grains
and grain weight, which resulted in improved grain yield and harvest index (Tabassum et
al., 2017).
187
4.6. Influence of seed priming on the productivity of late sown barley
4.6.1. Stand establishment
4.6.1.1. Mean emergence time
The mean emergence time was significantly affected by sowing time and seed
priming, during both years. However, the varieties did not differ significantly for mean
emergence time. Likewise, the interactions between sowing time and varieties, sowing
time and seed priming, varieties and seed priming, and three way interaction among
sowing time, varieties and seed priming was non-significant, during both years (Table
4.115). Mean emergence time was substantially increased by late sowing as compared to
optimum sowing, during both years. However, seed priming treatments caused a
reduction in mean emergence time with minimum time elapsed by osmopriming, during
both years (Table 4.116).
4.6.1.2. Time taken to 50% emergence
There was a significant influence of sowing time and seed priming on time taken
for 50%; while, the varieties did not differ significantly for time taken to 50% emergence,
during both years. The interaction between varieties and seed priming was significant
during 2014-15 but non-significant during 2015-16. However, the interactions between
sowing time and varieties, sowing time and seed priming, and three way interaction
among sowing time, varieties and seed priming was non-significant, during both years
(Table 4.115). Time taken to 50% emergence was increased by late sowing than optimum
sowing. However, seed priming treatments decreased time taken to 50% emergence with
maximum reduction caused by osmopriming, as compared to control, during both years.
Furthermore, varieties responded differently to seed priming treatments during 2014-15.
Minimum time taken to 50% emergence was taken by Haider-93 in response to
osmopriming while Fronteirs-87 responded better to biopriming (Tables 4.117a,b).
4.6.1.3. Emergence index
Sowing time and seed priming treatments significantly affected emergence index
while variety did not differ significantly for emergence index, during both years. The
interaction between varieties and seed priming was significant for emergence index
during 2014-15 while non-significant during 2015-16. Whereas, interactions between
sowing time and varieties, sowing time and seed priming, and three way interaction
among sowing time, varieties and seed priming was non-significant for emergence index,
during both years (Table 4.115). Late sowing decreased the emergence index as compared
188
to optimum sowing. However, seed priming improved the emergence index with
maximum
189
Table 4.115: Analysis of variance for the influence of seed priming on emergence of barley under optimum and late sowing time
SOV DF Mean sum of squareMean emergence
timeTime taken to 50%
emergenceEmergence index
2014-15 2015-16 2014-15 2015-16 2014-15 2015-16Replication (R) 3 0.380 0.109 0.176 0.098 94.815 91.519Sowing time (SD) 1 53.053** 53.290** 45.782** 53.144** 1747.136** 1491.118**
Error 1 3 0.003 0.000 0.078 0.059 72.290 70.339Varieties (V) 1 0.000ns 0.002ns 0.015ns 0.044ns 5.377ns 7.223ns
SD×V 1 0.007ns 0.002ns 0.000ns 0.130ns 0.468ns 0.019ns
Error 2 6 0.068 0.030 0.175 0.048 1.121 2.200Priming (T) 3 1.036** 0.720** 1.084** 0.936** 101.937** 42.338**
SD×T 3 0.003ns 0.015ns 0.081ns 0.019ns 1.144ns 0.845ns
V×T 3 0.042ns 0.034ns 0.216* 0.173ns 8.117* 2.455ns
SD×V×T 3 0.003ns 0.013ns 0.002ns 0.084ns 0.006ns 0.062ns
Error 3 36 0.019 0.032 0.042 0.092 1.537 3.944Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.116: Influence of seed priming on mean emergence time (days) of barley under optimum and late sowing timeTreatments
2014-15 2015-16November
30December
30Mean November
30December
30Mean
Control 5.79 7.65 6.72 A 5.90 7.81 6.85 AHP 5.63 7.43 6.53 B 5.58 7.37 6.47 BCOP 5.24 7.05 6.15 D 5.46 7.27 6.36 CBP 5.37 7.19 6.28 C 5.61 7.40 6.51 BMean 5.51 B 7.33 A 5.64 B 7.46 A
Sowing time LSD≤0.05 = 0.0443 (2014-15) and 0.0083 (2015-16), Seed priming LSD≤0.05 = 0.0987 (2014-15) and 0.1277 (2015-16)
Table 4.117a: Influence of seed priming on time taken for 50% (days) emergence of barley under optimum and late sowing timeTreatments 2014-15 2015-16
November 30
December 30
Mean November 30
December 30
Mean
Control 4.94 6.57 5.75 A 5.08 6.95 6.02 AHP 4.60 6.12 5.36 B 4.68 6.52 5.60 BOP 4.30 6.09 5.19 C 4.53 6.39 5.46 BBP 4.29 6.12 5.21 C 4.72 6.44 5.58 BMean 4.53 B 6.22 A 4.75 B 6.58 A
Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 0.2224 (2014-15) and 0.1932 (2015-16), Seed priming LSD≤0.05 = 0.1478 (2014-15) and 0.2177 (2015-16)
190
Table 4.117b: Influence of seed priming on time taken to 50% emergence (days) of barley under optimum and late sowing time (2014-15)Treatments H-93 F-87 MeanControl 5.87 a 5.63 b 5.75 AHP 5.31 c 5.40 c 5.36 BOP 5.07d 5.31 c 5.19 CBP 5.31 c 5.10 d 5.21 CMean 5.39 5.36
Seed priming LSD≤0.05 = 0.1478, Varieties × Seed priming LSD≤0.05 = 0.2090
Table 4.118a: Influence of seed priming on emergence index of barley under optimum and late sowing time
Treatments 2014-15 2015-16November
30December 30 Mean November
30December 30 Mean
Control29.41 19.73
24.57 C 30.28 21.25
25.76 B
HP33.63 23.09
28.36 B 33.60 23.96
28.78 A
OP35.48 24.61
30.05 A 34.43 24.32
29.37 A
BP35.14 24.42
29.78 A 33.66 23.82
28.74 A
Mean 33.41 A 22.97 B 32.99 A 23.34 BSowing time LSD≤0.05 = 6.7645 (2014-15) and 7.7733 (2015-16), Seed priming LSD≤0.05 = 0.8889 (2014-15) and 1.4240 (2015-16)
Table 4.118b: Influence of seed priming on emergence index of barley under optimum and late sowing time (2014-15)Treatments H-93 F-87 MeanControl 25.76 c 23.38 d 24.57 CHP 28.67 ab 28.05 ab 28.36 BOP 30.26 a 29.83 a 30.05 ABP 29.23 a 30.33 a 29.78 AMean 28.48 27.90
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Seed priming LSD≤0.05 = 0.8889, Varieties × Seed priming LSD≤0.05 = 1.2570
191
increased caused by osmopriming, during both years. Furthermore, varieties responded
differently to seed priming treatments regarding emergence index with highest emergence
index produced by Haider-93 in response to osmopriming and Fronteirs-87 in response to
biopriming during 2014-15 (Tables 4.118a,b).
4.6.2. Discussion
Late sowing caused a reduction in emergence and seedling establishment due to
prevailing low temperature at the time of sowing. However, seed priming improved the
emergence index with a reduction in emergence time indicating that seed priming has
potential to improve emergence under late sown conditions and prevailing low
temperature. Previous reports have shown that seed priming enhances germination speed,
germination rate and uniformity under optimum and late sown chilling stressed field
conditions (Kant et al., 2006; Farooq et al., 2008a). Seed priming makes the food reserves
readily available for embryo by enhancing carbohydrate metabolism through enhanced
activities of hydrolytic enzymes (Kaur et al., 2005; Farooq et al. 2009b). He et al. (2002)
reported that seed priming improved the α-amylase, β-amylase, catalase and root system
dehydrogenase activities in rice under stressed conditions. In the present study,
osmopriming improved emergence of barley which may be due to Ca2+ that regulates the
cell wall structure, cell membrane integrity and permeability, and mitotic activities
(Hepler, 2005) resulting in well-maintained cell membrane with better and rapid
germination (Posmyk et al., 2001). In present study, improved emergence by biopriming
might be due to endophytic bacteria which might have improved water absorption in
germinating seeds, and produced extracellular hydrolytic enzymes viz. amylase and
protease resulting in enhanced degradation of carbohydrates, proteins and lipids leading
to better germination under normal and stressed conditions (Zhu et al., 2017).
4.6.3. Allometric traits
4.6.3.1. Leaf area index
The LAI was increased progressively and then declined with advancement in crop
maturity. Higher LAI was recorded by optimum sowing than late sowing. It was observed
that maximum LAI was produced at 75 DAS in optimum sowing and 60 DAS in late
sowing, during both years. Likewise, the varieties differed regarding LAI. Fronteir-87
produced greater LAI than Haider-93. However, there was prompt increase in LAI of
Frontier-87 at early growth stages (upto 75 DAS) and started decreasing rapidly
afterwards while in Haider-93 there was slow increase at early growth stages and
192
decrease at later growth stages until maturity. Moreover, seed priming improved the LAI
of both varieties
193
Lea
f are
a in
dex
194
Lea
f are
a in
dex
195
at both sowing times and growth stages as compared to control, during both years.
Haider-93 responded well to osmopriming and Frontier-87 produced highest LAI by
biopriming under both optimum and late sowing times. However, under both optimum
and late sowing conditions maximum LAI was produced by biopriming of Frontier-87
(Figures 4.30, 4.31).
4.6.3.2. Total dry matter
The temporal pattern of TDM accumulation showed an increase upto maturity.
Late sowing caused a reduction in TDM accumulation as compared to optimum sowing,
during both years. Maximum TDM accumulation took place during 45-75 DAS in both
sowing time. There was a differential accumulation of TDM in both varieties. During
2014-15, Haider-93 produced more TDM than Frontier-87 although Frontier-87
accumulated more TDM during early growth stages than Haider-93. However, during
2015-16 Frontier-87 accumulated more TDM than Haider-93 from initial stages to
maturity. Seed priming improved the TDM in both varieties at both sowing times and all
growth stages. It was observed that under optimum sowing maximum TDM accumulation
in both varieties occurred by osmopriming, during both years; however, under late
sowing, maximum increase in TDM accumulation in Haider-93 was caused by
osmopriming during 2014-15 and biopriming during 2015-16 while in Frontier-87
biopriming improved TDM most, during both years. Overall, maximum TDM was
recorded by osmopriming of Haider-93 under optimum sowing time, while, biopriming of
Haider-93 produced similar TDM during 2014-15. However, under late sowing, highest
TDM was produced by osmopriming of Haider-93 during 2014-15 and biopriming of
Frontier-87 during 2015-16. However, biopriming of Haider-93 produced similar TDM
during 2015-16 (Figures 4.32, 4.33).
4.6.3.3. Crop growth rate
Crop growth rate of barley increased with increase in time and then dropped until
maturity. Late sowing caused a reduction in CGR than optimum sowing, during both years.
In optimum sowing, maximum CGR was attained at 45 DAS and then remained stable until
60-75 DAS; while, in late sowing maximum CGR was recorded at 45-60 DAS. The
varieties performed differently regarding CGR. Haider-93 attained maximum CGR at 60-
75 DAS while Frontier-87 attained highest CGR at 45-60 DAS after which it started
declining. Haider-93 exhibited higher CGR than Frontier-87 under both sowing times. Seed
priming improved the CGR of both varieties at both sowing times and all growth stages, as
compared to control. In optimum sowing, maximum improvement in CGR of both varieties 196
was caused by osmopriming, during both years. In late sowing, the osmopriming was
superior in improving CGR of Haider-93 during 2014-15 and biopriming was effective
during 2015-16.
197
Tot
al d
ry m
atte
r (g
m-2)
198
Tot
al d
ry m
atte
r (g
m-2)
199
Cro
p gr
owth
rat
e (g
m-2 d
-1)
200
Cro
p gr
owth
rat
e (g
m-2 d
-1)
201
However, maximum improvement in CGR was recorded by biopriming of Fronter-87
under late sowing, during both years. Overall, maximum CGR was observed by
osmopriming of Haider-93 under optimum sowing time, during both years, and by
osmopriming and biopriming of Haider-93 under late sowing during 2014-15 and 2015-
16, respectively (Figures 4.34, 4.35).
4.6.3.4. Grain filling rate
Grain filling was increased with time and then declined at maturity. Late sowing
caused a drastic reduction in grain filling rate as compared to optimum sowing time.
Maximum grain filling rate occurred at 14-21 days after anthesis (DAA) in both sowing
times, during both years. Moreover, varieties differed in grain filling rate. In Haider-93
greater grain filling rate was observed in early stages of grain filling while in Frontier-87
higher grain filling rate was observed at later stages of grain filling. Seed priming
improved the grain filling rate of both varieties at both sowing times and all growth
stages, as compared to unprimed control. It was observed that at optimum sowing highest
grain filling rate occurred by osmopriming and biopriming of Haider-93 during 2014-15
and 2015-16, respectively. Whereas, in late sowing maximum increase in grain filling rate
was caused by biopriming of Haider-93, during both years (Figures 4.36, 4.37).
4.6.3.5. Grain filling duration
Grain filling duration was significantly affected by sowing time; while, tested
barley varieties also differed significantly, during both years. Seed priming did not affect
grain filling rate during 2014-15 but significantly affected during 2015-16. Likewise,
interaction between sowing time and varieties was significant for grain filling duration
during 2014-15 but non-significant during 2015-16. The interactions between sowing
time and seed priming, and varieties and seed priming were non-significant, during both
years. However, three way interaction among sowing time, varieties and seed priming
was significant, during both year (Table 4.119). Late sowing caused a substantial
decrease in grain filling duration as compared to optimum sowing. Likewise, Haider-93
took less time for grain filling than Frontier-87, during both years. Seed priming was not
influential on grain filling duration during 2014-15 but during 2015-16 biopriming caused
a slight decrease. At optimum sowing, highest grain filling duration was recorded by
osmopriming of Frontiers-87 and least was observed by osmopriming of Haider-93,
during both years. However, at late sowing, highest grain filling duration occurred by
biopriming of Frontier-87 during 2014-15 and hydropriming of Frontier-87 during 2015-
202
16. Whereas, minimum grain filling duration was recorded by biopriming of Haider-93,
during both years, while, G
rain
filli
ng r
ate
(mg
spik
e-1 d
-1)
203
Gra
in fi
lling
rat
e (m
g sp
ike-1
d-1)
204
Table 4.119: Analysis of variance for the influence of seed priming on grain filling duration of barley under optimum and late sowing time
SOV DFMean sum of squares
2014-15 2015-16Replication (R) 3 0.72 1.90Sowing time (SD) 1 1032.02** 462.25**
Error 1 3 1.89 0.42Varieties (V) 1 17.02** 33.06**
SD×V 1 8.27* 1.00ns
Error 2 6 1.22 1.11Priming (T) 3 0.52ns 2.40*
SD×T 3 0.52ns 0.25ns
V×T 3 0.18ns 0.56ns
SD×V×T 3 5.68** 2.17*
Error 3 36 0.78 0.66Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.120: Influence of seed priming on grain filling duration (days) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30
H-93 F-87 H-93 F-87Control 34.25 bc 35.50 ab 28.25 ef 29.25 efHP 33.75 cd 35.50 ab 28.25 ef 28.00 fOP 32.75 d 36.25 a 29.25 ef 28.25 efBP 34.25 bc 34.75 bc 28.00 f 29.50 e
Sowing time × Varieties × Seed priming LSD≤0.05 = 1.2661
Table 4.121: Influence of seed priming on grain filling duration (days) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30
H-93 F-87 H-93 F-87Control 33.75 bc 35.75 a 28.50 fg 30.00 deHP 34.75 ab 35.75 a 29.25 def 30.25 dOP 32.75 c 35.75 a 29.00 efg 29.50 defBP 34.00 b 34.75 ab 28.00 g 29.75 de
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 1.1679
205
hydropriming of Frontier-87 gave similar results during 2014-15 (Tables 4.120, 4.121).
4.6.4. Discussion
In present study, late sowing caused a reduction in TDM and CGR which was
associated with decrease in LAI. Late sowing causes a reduction in plant growth by
exposing the plants to cold stress (Farooq et al., 2008a). Moreover, decrease in LAI in
present study may be attributed to decreased emergence and plant growth by early season
low temperature because LAI is a function of number of plants and leaves per unit area,
and leaf growth rate. However, in present study seed priming improved LAI, TDM and
CGR under both optimum and late sowing. This might be due to enhanced early seedling
vigour and enhanced plant protection from environmental stresses resulting in improved
plant growth and leaf area under normal and stressed conditions (Tabassum et al., 2017).
Furthermore, it was observed that seed priming improved the photosynthetic pigments
which may have resulted in enhanced photosynthesis leading to improved TDM
production and grain yield (Abid et al., 2018).
In current study, osmopriming enhanced LAI, TDM and CGR which might be due
to the Ca2+ which modulates the calmodulin like protiens in signaling pathways and
improves plant growth (Sarwat et al., 2013). Furthermore, Ca2+ is involved in cell wall
structure, cell membrane integrity and permeability, and cell division which regulates the
plant growth and development (Hepler, 2005). Moreover, in this study improved leaf area
and chlorophyll contents by osmopriming may have resulted in better light utilization and
photosynthesis because Ca2+ is also involved in chlorophyll synthesis and photosynthesis
(Hochmal et al., 2015; Dai et al., 2017) thus improving the dry matter production.
Improved plant growth and TDM by biopriming may be attributed to the endophytic
bacteria which improves the plant growth and development by production of plant growth
promoting hormones while decreasing ethylene production, and by improved nutrient
uptake (Miliute et al., 2015). Previous studies have shown that endophytic bacteria
Enterobacter sp. FD17, used in present study, improves the leaf area, chlorophyll
photochemistry, photosynthesis and dry matter production and ultimately crop yield
(Naveed et al., 2014a).
In present study, late sowing decreased the grain filling rate which is attributed to
decreased plant growth, leaf area and grain filling duration. The decreased leaf area
resulted in decreased dry matter accumulation and CGR due to decrease in assimilatory
surface. However, seed priming treatments improved the grain filling rate which may be
attributed to improved LAI and CGR because grain filling duration was not affected by 206
seed priming treatments. It has been observed that seed priming with CaCl2 improves the
leaf area, leaf area duration (LAD) and NAR (Mahboob et al., 2015). Moreover, in present
study improved grain filling rate by seed priming under late sowing conditions might be
attributed to its protective role form high temperature stress because late sowing exposes
the plants to high temperature during grain filling period which negatively affects the starch
synthase enzyme because it is sensitive to temperature more than 20˚C (Keeling et al.,
1994).
4.6.5. Agronomic attributes
4.6.5.1. Plant height
A significant influence of sowing time and seed priming was noticed for plant
height of barley; while barley varieties also significantly differed for plant height, during
both years. The interaction between sowing time and varieties was significant during
2014-15 but non-significant during 2015-16. Interaction between sowing time and seed
priming was non-significant, during both years. Whereas, interaction between varieties
and seed priming, and three way interaction among sowing time, varieties and seed
priming were non-significant during 2014-15 but significant during 2015-16 (Table
4.122). Late sowing decreased the plant height than optimum sowing. Taller plants were
produced by Frontier-87 than Haider-93. Seed priming increased the plant height of both
varieties at both sowing times, as compared to unprimed control. During 2014-15,
biopriming and osmopriming of Frontier-87 produced tallest plants at optimum sowing
and late sowing, respectively. However, during 2015-16, tallest plants were noticed by
biopriming of Frontier-87 and Haider-93 at optimum sowing and late sowing,
respectively (Tables 4.123a-4.124).
4.6.5.2. Number of productive tillers m-2
Number of productive tillers m-2 was affected significantly by sowing time and
seed priming; barley varieties also significantly differed for number of productive tillers,
during both years. The interaction between sowing time and varieties was significant
during 2014-15 but non-significant during 2015-16. The interactions between sowing
time and seed priming, and varieties and seed priming were non-significant, during both
years. However, three way interaction among sowing time, varieties and seed priming
was significant, during both years (Table 4.122). The production of productive tillers was
decreased by late sowing than optimum sowing. Higher number of productive tillers was
produced by Haider-93 than Frontier-87. Number of productive tillers of both varieties
was increased by seed priming at both sowing times, as compared to unprimed control. 207
Highest number of productive tillers was produced by osmopriming of Haider-93 at
optimum sowing, during both years, while at late sowing, osmopriming and biopriming of
Haider-93 caused maximum increase in number of productive tillers during 2014-15 and
2015-16,
208
Table 4.122: Analysis of variance for the influence of seed priming on plant height and number of productive tillers per m2 of barley under optimum and late sowing time
SOV DFMean sum of squares
Plant height Number of productive tillers per m2
2014-15 2015-16 2014-15 2015-16Replication (R) 3 127.79 48.95 49.02 138.28Sowing time (SD) 1 11236.00** 5645.08** 40876.75** 88553.11**
Error 1 3 133.97 31.43 76.96 452.83Varieties (V) 1 192.31** 92.62* 399.10* 1115.81**
SD×V 1 15.27* 5.25ns 1685.10** 44.0ns
Error 2 6 2.42 12.75 39.58 52.08Priming (T) 3 85.58* 431.10** 13920.40** 6408.34**
SD×T 3 73.24ns 50.38ns 98.42ns 273.07ns
V×T 3 14.06ns 64.11* 8.55ns 42.01ns
SD×V×T 3 17.43ns 63.12* 283.13** 566.82*
Error 3 36 26.03 21.14 54.46 174.75Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.123a: Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30 MeanH-93 109.35 b 83.83 d 96.59 BF-87 113.79 a 86.32 c 100.05 AMean 111.57 A 85.07 B
Sowing time LSD≤0.05 = 9.2088, Varieties LSD≤0.05 = 0.9508, Sowing time × Varieties LSD≤0.05 = 1.3446
Table 4.123b: Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30 MeanControl 108.76 80.95 94.86 BHP 113.45 85.61 99.53 AOP 109.46 89.18 99.32 ABP 114.61 84.54 99.58 AMean 111.57 A 85.07 B
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 9.2088, Seed priming LSD≤0.05 = 3.6584
209
Table 4.124: Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30
H-93 F-87 H-93 F-87Control 88.75 b 90.50 b 67.76 f 79.35 deHP 97.75 a 101.08 a 73.01 ef 77.95 deOP 99.67 a 99.92 a 81.48 cd 84.30 bcdBP 101.50 a 103.50 a 87.99 bc 80.57 d
Sowing time × Varieties × Seed priming LSD≤0.05 = 6.5942
Table 4.125: Influence of seed priming on number of productive tillers per m2 of barley under optimum and late sowing time
Treat-ments
2014-15 2015-16November 30 December 30 November 30 December 30
H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control
354.02 ef 351.11 f 307.26 h 303.48 h 358.28 c 350.46 c 285.07 f 281.52 f
HP411.01 b 390.86 c 340.04 g
350.52 fg 388.93 b 379.70 b 314.44 de 299.74 ef
OP 425.16 a 412.50 b 371.90 d 374.78 d 421.34 a 393.40 b 319.34 d 326.85 dBP 425.06 a 399.75 c 352.81 f 364.30 de 385.73 b 390.67 b 331.21 d 315.18 de
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 10.5832 (2014-15) and 18.9575 (2015-16)
210
respectively (Table 4.125).
4.6.5.3. Spike length
Sowing time and seed priming treatments significantly affected spike length,
during both years. However, tested barley varieties did not differ significantly for spike
length during both years. The interaction between varieties and seed priming was non-
significant for spike length, during both years. The interactions between sowing time and
varieties, sowing time and seed priming, and three way interaction among sowing time,
varieties and seed priming was significant for spike length, during both years (Table
4.126). Late sowing decreased the spike length as compared to optimum sowing. Longer
spikes were produced by Haider-93 than Frontier-87. Seed priming enhanced the spike
length of both barley varieties at both sowing times, as compared to unprimed control.
Maximum increase in spike length was recorded by biopriming of Haider-93 at optimum
sowing, during both years. However, at late sowing the greatest increase in spike length
was observed by osmopriming of Frontier-87 during 2014-15 and biopriming of Haider-
93 during 2015-16 (Table 4.127).
4.6.5.4. Number of spikelets per spike
Sowing time and seed priming treatments significantly affected the number of
spikelets per spike, during both years. The varieties significantly differed during 2014-15
while did not differ significantly during 2015-16 for number of spikelets per spike.
Interactions between sowing time and varieties, and sowing time and seed priming were
significant during 2014-15 but non-significant during 2015-16. The interaction between
varieties and seed priming was non-significant for number of spikelets per spike during
2014-15 while significant during 2015-16. The three way interaction among sowing time,
varieties and seed priming was significant, during both years (Table 4.126). Late sowing
lowered the number of spikelets per spike as compared to optimum sowing. Higher
number of spikelets were produced by Haider-93 than Frontier-87. Number of spikelets
per spike of both varieties were improved by seed priming at both sowing times, as
compared to unprimed control. At optimum sowing osmopriming of Haider-93 while at
late sowing biopriming of Haider-93 caused greatest increase in number of spikelets per
spike, during both years. However osmopriming of Haider-93 at late sowing produced
similar results for number of spikelets per spike during 2015-16 (Table 4.128).
4.6.5.5. Number of grains per spike
211
There was a significant effect of sowing time and seed priming on number of
grains per spike; tested barley varieties also differed significantly for number of grains
per spike,
212
Table 4.126: Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under optimum and late sowing time
SOV DFMean sum of squares
Spike length Number of spikelets per spike2014-15 2015-16 2014-15 2015-16
Replication (R) 3 0.162 0.052 0.799 0.675Sowing time (SD) 1 43.346** 101.884** 823.475** 530.151**
Error 1 3 0.188 0.123 2.691 0.412Varieties (V) 1 0.082ns 1.706ns 31.767** 2.481ns
SD×V 1 13.811** 1.739* 0.032ns 0.903ns
Error 2 6 0.072 0.286 0.886 0.801Priming (T) 3 17.972** 7.938** 54.501** 49.995**
SD×T 3 1.739** 1.088** 4.697* 1.094ns
V×T 3 0.733ns 0.287ns 1.111ns 2.466**
SD×V×T 3 1.055* 0.495* 3.810* 1.825*
Error 3 36 0.348 0.154 1.262 0.483Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.127: Influence of seed priming on spike length (cm) of barley under optimum and late sowing time
Treatments
2014-15 2015-16November 30 December 30 November 30 December 30
H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 8.83 e 8.70 e 7.29 h 7.52 gh 9.80 e 9.75 e 8.06 h 7.90 hHP 10.28 cd 8.45 ef 7.62 fgh 8.44 ef 11.90 ab 10.95 d 8.33 gh 8.88 fgOP 11.04 bc 10.24 cd 8.75 e 10.03 d 12.03 ab 11.58 bc 8.90 f 8.78 fgBP 11.96 a 11.29 ab 8.15 efg 9.83 d 12.25 a 11.08 cd 9.28 ef 9.03 f
Sowing time × Varieties × Seed priming LSD≤0.05 = 0.8465 (2014-15) and 0.5633 (2015-16)
Table 4.128: Influence of seed priming on number of spikelets per spike of barley under optimum and late sowing time
Treatments
2014-15 2015-16November 30 December 30 November 30 December 30
H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 16.50 e 15.40 ef 10.84 ij 9.50 j 17.50 e 16.88 e 11.93 h 11.53 hHP 20.17
bc 18.38 d13.05
gh11.50
hi 19.00 d 21.00 bc 15.00 fg 14.50 gOP
22.50 a19.43
cd13.05
gh12.17
hi 22.00 a 21.00 bc 15.50 f 14.63 fgBP 20.67
bc21.18
ab 14.38 fg12.33
hi21.50
ab 20.50 c 15.50 f 14.75 fgValues sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 1.6110 (2014-15) and 0.9969 (2015-16)
213
during both years. The interactions between sowing time and varieties, and sowing time
and seed priming were significant for number of grains per spike, during both years while
interaction between varieties and seed priming was significant during 2014-15 and non-
significant during 2015-16. The three way interaction among sowing time, varieties and
seed priming was significant, during both years (Table 4.129). A reduction in number of
grains per spike was observed by late sowing as compared to optimum sowing. The
variety Haider-93 produced more number of grains per spike than Frontier-87. However,
seed priming exhibited increase in number of grains per spike of both varieties at both
sowing times, as compared to unprimed control. Highest number of grains per spike were
produced by osmopriming and hydropriming of Haider-93 at optimum sowing during
2014-15 and 2015-16, respectively. However, at late sowing osmopriming of Haider-93
exhibited greatest increase in number of grains per spike, during both years (Table 4.130).
4.6.5.6. 1000-grain weight
The 1000-grain weight was significantly affected by sowing time and seed
priming; the varieties also differed significantly differed for 100-grains weight, during
both years. However, the interactions between sowing time and varieties, sowing time
and seed priming, varieties and seed priming, and three way interaction among sowing
time, varieties and seed priming was non-significant during 2014-15 while significant
during 2015-16 (Table 4.129). Late sowing caused a reduction in 1000-grain weight as
compared to optimum sowing. Variety Haider-93 produced higher 1000-grain weight
than Frontier-87. The seed priming caused an increase in 1000-grain weight of both
varieties at both sowing times, as compared to unprimed control. At optimum sowing,
osmopriming and biopriming of Haider-93 showed highest increase in 1000-grain weight
of barley during 2014-15 and 2015-16, respectively. Whereas, at late sowing biopriming
of Haider-93 caused the greatest increase in 1000-grain weight, during both years (Table
4.131a-4.132).
4.6.5.7. Grain yield
There was a significant effect of sowing time and seed priming treatments on
grain yield; while, varieties also significantly differed for grain yield, during both years.
Interaction between varieties and seed priming was non-significant during 2014-15 but
significant during 2015-16. However, the interactions between sowing time and varieties,
sowing time and seed priming, and three way interaction among sowing time, varieties
and seed priming was significant for grain yield, during both years (Table 4.133). There
was a substantial reduction in grain yield by late sowing than optimum sowing. The 214
variety Haider-93 produced more grain yield than Frontier-87. Grain yield was
significantly improved by seed priming of both varieties at both sowing times, as
compared to unprimed control. The grain yield was increased most by osmopriming of
Haider-93 at optimum sowing, during both years. However, at late sowing osmopriming
of Haider-93 and biopriming of Frontier-87 exhibited maximum improvement in grain
yield during 2014-15 and 2015-16, respectively (Table 4.134).
4.6.5.8. Straw yield
Sowing time and seed priming significantly affected straw yield while varieties
did not differ significantly, during both years. Interactions between sowing time and
varieties, and varieties and seed priming were non-significant while interaction between
sowing time and seed priming was significant, during both years. However, three way
interaction among sowing time, varieties and seed priming was significant during 2014-
15 but non-significant during 2015-16 (Table 4.133). Late sowing resulted in lower straw
yield as compared to optimum sowing. Variety Frontier-87 produced greater straw yield
than Haider-93. Straw yield was bettered by seed priming of both varieties at both sowing
times, as compared to unprimed control. During 2014-15, straw yield was improved most
by biopriming and osmopriming of Haider-93 at optimum sowing and late sowing,
respectively (Tables 4.135, 4.136).
4.6.5.9. Biological yield
A significant effect of sowing time and seed priming was observed for biological
yield of barley. Tested barley varieties differed significantly during 2014-15 while did not
differ significantly during 2015-16. The interactions between sowing time and varieties,
and varieties and seed priming were non-significant, during both years. Interaction
between sowing time and seed priming was significant for biological yield, during both
years. The three way interaction among sowing time, varieties and seed priming was
significant during 2014-15 but non-significant during 2015-16 (Table 4.137). Lower
biological yield was noticed by late sowing than optimum sowing. Higher biological yield
was recorded by variety Haider-93 during 2014-15 and by Frontier-87 during 2015-16.
Seed priming enhanced the biological yield of both varieties at both sowing times, as
compared to unprimed control. During 2014-15, biological yield was enhanced most by
biopriming and osmopriming of Haider-93, at early and late sowing, respectively (Tables
4.138, 4.139).
4.6.5.10. Harvest index
215
There was a significant effect of sowing time and seed priming on harvest index;
tested barley varieties also differed significantly for harvest index, during both years. The
interactions between sowing time and varieties, and varieties and seed priming were non-
significant, during both years while interaction between sowing time and seed priming
was significant during 2014-15 but non-significant during 2015-16. The three way
interaction among sowing time, varieties and seed priming was significant, during both
years (Table 4.137). Harvest index was decreased by late sowing as compared to
optimum sowing. Higher harvest index was exhibited by Haider-93. Seed priming
enhanced the harvest index of both varieties at both sowing times, as compared to
unprimed control. At optimum sowing, highest harvest index was recorded by
osmopriming and biopriming of Haider-93 during 2014-15 and 2015-16, respectively. At
late sowing, maximum harvest index was observed by biopriming of Haider-93 and
Frontier-87 during 2014-15 and 2015-16, respectively (Table 4.140).
4.6.6. Discussion
Late sowing caused a decrease in plant height, yield and harvest index of barley
varieties. This could be due to cold temperature during early vegetative stage which
results in decreased plant growth (Farooq et al., 2008a). However, in present study seed
priming improved plant height in both early and late sown conditions. Seed priming
improves the plant growth by early head start and improved stress tolerance by increased
accumulation of osmolytes and antioxidants activity, under stressed conditions (Chen and
Arora, 2013). In osmoprimed plants, higher plant height is attributed to role of Ca2+ in cell
wall structure, cell membrane integrity and mitotic activities (Hepler, 2005). Moreover,
Ca2+ regulates the calmodulin like proteins in signaling pathways and improves the plant
growth under stressed conditions (Sarwat et al., 2013). In biopriming, the endophytic
bacteria migt have promoted the growth by enhancing nutrient uptake through
solubilization and producing plant growth promoting hormones such as auxins, cytokinins
and gibberellic acid while suppressing the ethylene production by synthesis of ACC
deaminase enzyme (Miliute et al., 2015).
In present study, the late sowing caused a reduction in yield and harvest index of
both varieties; while, Haider-93 performed better in this regard. The decrease in grain yield
under late sown conditions was associated with decreased emergence and stand
establishment, number of productive tillers and grains, and grain weight; nonetheless, seed
primed plants showed less reductions than unprimed plants. Higher total and productive
tillers due to seed priming were the result of early better plant growth events such as early 216
vigorous seedling growth and development (Kaur et al., 2005; Farooq et al., 2006b).
Moreover, Ca2+ could have improved the photosynthesis, protected biological membranes
and cell organelles through enhanced osmolytes accumulation and antioxidants activity
217
Table 4.129: Analysis of variance for the influence of seed priming on number of grains per spike and 1000-grain weight of barley under optimum and late sowing time
SOV DFMean sum of squares
Number of grains per spike 1000-grain weight2014-15 2015-16 2014-15 2015-16
Replication (R) 3 0.673 3.313 0.490 0.457Sowing time (SD) 1 160.687** 79.901** 219.114** 113.263**
Error 1 3 4.588 0.452 1.272 0.188Varieties (V) 1 108.134** 42.136** 11.458* 38.347**
SD×V 1 4.177* 4.521* 0.083ns 5.700*
Error 2 6 0.501 0.637 1.743 0.597Priming (T) 3 82.686** 24.476** 11.228** 20.161**
SD×T 3 3.616ns 14.434** 2.244ns 1.885**
V×T 3 1.284ns 4.352* 0.529ns 5.258**
SD×V×T 3 4.078* 4.515* 1.722ns 1.061*
Error 3 36 1.385 1.297 0.904 0.324Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.130: Influence of seed priming on number of grains per spike of barley under optimum and late sowing time
Treatments
2014-15 2015-16November 30 December 30 November 30 December 30
H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 39.09 ghi 37.84 ij 37.93 hij 35.38 k 40.21 bcd 39.83 cd 36.15 e 34.11 fHP 42.88 cd 40.84 ef 40.30 fg 36.47 jk 42.12 a 39.90 cd 39.20 cd 38.78 dOP 45.49 a 43.75 bc 42.88 cd 38.29 hi 41.73 ab 40.23 bcd 41.74 ab 36.94 eBP
45.36 ab 42.03 de 41.08 ef39.61 fgh 40.29 bcd 40.03 cd 40.45 bc 39.09 cd
Sowing time × Varieties × Seed priming LSD≤0.05 = 1.6877 (2014-15) and 1.6333 (2015-16)
Table 4.131a: Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2014-15)Treatments H-93 F-87 MeanControl 30.66 29.70 30.18 CHP 31.40 31.04 31.22 BOP 32.42 31.19 31.81 ABBP 32.49 31.66 32.07 AMean 31.74 A 30.90 B
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties LSD≤0.05 = 0.8077, Seed priming LSD≤0.05 = 0.6818
218
Table 4.131b: Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30 MeanH-93 33.56 29.93 31.74 AF-87 32.78 29.01 30.90 BMean 33.17 A 29.47 B
Sowing time LSD≤0.05 = 0.8975, Varieties LSD≤0.05 = 0.8077
Table 4.132: Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30
H-93 F-87 H-93 F-87Control 31.19 cd 29.92 efg 28.72 h 27.47 iHP 33.03 b 30.59 de 30.23 ef 29.32 ghOP 33.45 b 32.81 b 29.41 gh 29.57 fgBP 35.32 a 31.10 cd 31.60 c 29.81 efg
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 0.8167
Table 4.133: Analysis of variance for the influence of seed priming on grain yield and straw yield of barley under optimum and late sowing time
SOV DFMean sum of squares
Grain yield Straw yield2014-15 2015-16 2014-15 2015-16
Replication (R) 3 0.0036 0.0030 0.0024 0.1183Sowing time (SD) 1 9.6643** 6.2375** 10.8406** 7.6521**
Error 1 3 0.0026 0.0026 0.1447 0.0686Varieties (V) 1 0.3615** 0.0798** 0.0298ns 0.5532ns
SD×V 1 0.0147* 0.0841** 0.2916ns 0.0329ns
Error 2 6 0.0031 0.0015 0.0710 0.1219Priming (T) 3 2.5372** 1.7752** 2.9967** 2.0697**
SD×T 3 0.0624** 0.1198** 0.2740** 0.2479*
V×T 3 0.0107* 0.0194** 0.1106ns 0.0326ns
SD×V×T 3 0.0146* 0.0093* 0.3605** 0.1424ns
Error 3 36 0.0034 0.0031 0.0528 0.0697Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
219
Table 4.134: Influence of seed priming on grain yield (t ha-1) of barley under optimum and late sowing time
Treatments 2014-15 2015-16November 30 December 30 November 30 December 30H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87
Control 2.75 g 2.65 h 2.13 j 1.99 k 2.67 gh 2.63 hi 1.98 k 2.00 kHP 3.29 d 3.13 e 2.51 i 2.46 i 3.01 d 2.87 e 2.33 j 2.39 jOP 3.85 a 3.64 b 2.93 f 2.70 gh 3.56 a 3.36 b 2.69 gh 2.55 iBP 3.69 b 3.42 c 2.77 g 2.71 gh 3.28 b 3.10 c 2.74 fg 2.80 ef
Sowing time × Varieties × Seed priming LSD≤0.05 = 0.0839 (2014-15) and 0.0799 (2015-16)
Table 4.135: Influence of seed priming on straw yield (t ha -1) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30
H-93 F-87 H-93 F-87Control 5.42 fg 5.48 fg 4.78 i 4.77 iHP 5.81 de 6.23 bc 5.48 fg 5.07 hiOP 6.40 abc 6.45 ab 6.07 cd 5.45 fgBP 6.63 a 6.48 ab 5.18 gh 5.51 ef
Sowing time × Varieties × Seed priming LSD≤0.05 = 0.3295
Table 4.136: Influence of seed priming on straw yield (t ha -1) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30 MeanControl 5.61 b 4.64 c 5.12 BHP 5.39 bc 4.69 c 5.04 BOP 6.13 a 5.40 bc 5.77 ABP 5.80 b 5.43 bc 5.61 AMean 5.73 A 5.04 B
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 0.2083, Seed priming LSD≤0.05 = 0.1893, Sowing time × Seed priming LSD≤0.05
= 0.2677
220
Table 4.137: Analysis of variance for the influence of seed priming on biological yield and harvest index of barley under optimum and late sowing time
SOV DFMean sum of squares
Biological yield Harvest index2014-15 2015-16 2014-15 2015-16
Replication (R) 3 0.0036 0.1595 0.325 0.936Sowing time (SD) 1 41.0721** 27.7071** 120.122** 81.993**
Error 1 3 0.1311 0.0789 3.087 1.246Varieties (V) 1 0.5948* 0.2082ns 15.054* 25.756**
SD×V 1 0.1754ns 0.0129ns 5.966ns 7.209ns
Error 2 6 0.0789 0.1443 1.168 1.535Priming (T) 3 11.0172** 7.1492** 32.991** 47.100**
SD×T 3 0.3674** 0.5963** 5.433** 2.298ns
V×T 3 0.1667ns 0.0956ns 1.097ns 0.178ns
SD×V×T 3 0.4357** 0.1206ns 5.035** 4.010*
Error 3 36 0.0622 0.0810 0.851 1.054Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.138: Influence of seed priming on biological yield (t ha -1) of barley under optimum and late sowing time (2014-15)
Treatments November 30 December 30H-93 F-87 H-93 F-87
Control 8.17 e 8.14 e 6.92 g 6.76 gHP 9.10 cd 9.36 c 7.98 e 7.53 fOP 10.24 ab 10.09 ab 9.00 d 8.15 eBP 10.32 a 9.89 b 7.95 e 8.21 e
Sowing time × Varieties × Seed priming LSD≤0.05 = 0.3576
Table 4.139: Influence of seed priming on biological yield (t ha -1) of barley under optimum and late sowing time (2015-16)
Treatments November 30 December 30 MeanControl 8.26 c 6.63 f 7.44 DHP 8.33 c 7.05 e 7.69 COP 9.59 a 8.02 cd 8.81 ABP 8.98 b 8.20 c 8.59 BMean 8.79 A 7.47 B
Sowing time LSD≤0.05 = 0.2235, Seed priming LSD≤0.05 = 0.2041, Sowing time × Seed priming LSD≤0.05
= 0.2886
Table 4.140: Influence of seed priming on harvest index (%) of barley under optimum and late sowing time
Treatments
2014-15 2015-16November 30 December 30 November 30 December 30
H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 33.65 def 32.65 fg 30.89 h 29.42i 32.92 fg 31.30 hi 30.29 ij 29.75 jHP 36.15 b 33.48 ef 31.39 gh 32.74 f 35.95 abc 34.67 cde 33.98 def 33.05 fgOP 37.56 a 36.12 b 32.52 fg 33.12 f 36.77 ab 35.40 bcd 33.53 ef 31.88 ghBP 35.73 bc 34.52 cde 34.89 bcd 32.96 f 37.31 a 33.81 ef 33.40 ef 34.14 def
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 1.3226 (2014-15) and 1.4721 (2015-16)
221
which was translated into greater number of grains, grain weight and yield under normal
and stressed conditions (Dolatabadian et al., 2013). Similar, results were reported by
Farooq et al. (2008a) that osmopriming with CaCl2 improved the grain yield and harvest
index of wheat under late sown field conditions by ameliorating the damaging effects of
chilling stress.
In present study, the improved grain yield and harvest index by endophytic
bacteria in biopriming under late sown conditions is attributed to improved number of
productive tillers and grains, and grain weight. The improved number of productive tillers
by biopriming is attributed to improved early seedling establishment and growth
promotion by endophytic bacteria (Santoyo et al., 2016). Moreover, biopriming improves
the water relations of plants, enhances chlorophyll synthesis, and improves
photosynthesis and chlorophyll photochemistry resulting in improved number of grains
and grain weight which ultimately leads to better grain yield (Belimov et al., 2009;
Naveed et al., 2014a; Gagné-Bourque et al., 2016). Similar, results were reported by
Naveed et al. (2014c) that endophytic bacterial Burkholderia phytofrmans strain PsJN
improved the photosynthesis, nutrients uptake, water relations, and yield and related traits
of wheat under drought stress.
4.6.7. Chlorophyll contents
4.6.7.1. Chlorophyll a content
Chlorophyll a content was significantly affected by sowing time and seed priming,
during both years; however, varieties did not differ significantly during 2014-15 but
significantly differed during 2015-16. Interaction between sowing time and varieties, and
varieties and seed priming was significant during 2014-15 but non-significant during
2015-16. However, interactions between sowing time and seed priming, and three way
interaction among sowing time, varieties and seed priming was significant, during both
years (Table 4.141). Chlorophyll a content was decreased by late sowing than optimum
sowing. The variety Haider-93 produced higher chlorophyll a content than Frontier-87.
Moreover, chlorophyll a content was improved by seed priming treatments in both
varieties at both sowing times, as compared to unprimed control. At optimum sowing,
biopriming and hydropriming of Haider-93 caused the great improvement in chlorophyll
a content during 2014-15 and 2015-16, respectively. However, at late sowing biopriming
of Haider-93 resulted in maximum increase in chlorophyll a content, during both years
(Table 4.142).
4.6.7.2. Chlorophyll b content222
A significant effect of sowing time was observed for chlorophyll a content, during
both years; seed priming significantly affected chlorophyll b content during 2014-15 but
did not affect during 2015-16. Tested barley varieties significantly differed, during both
years. Interactions between sowing time and varieties, and sowing time and seed priming
were non-significant, during both years. Interaction between varieties and seed priming
and three way interaction among sowing time, varieties and seed priming was significant,
during both years (Table 4.141). Late sowing partially caused a reduction in chlorophyll b
than optimum sowing. Chlorophyll b content in variety Haider-93 was higher than
Frontier-87. The seed priming treatments enhanced the chlorophyll b content in both
varieties at both sowing times, as compared to unprimed control. Chlorophyll b content
was improved most by biopriming of Haider-93 during 2014-15, while, by biopriming of
Frontier-87 during 2015-16. However, at late sowing biopriming and osmopriming of
Haider-93 was most effective in improving chlorophyll b content during 2014-15 and
2015-16, respectively (Table 4.143).
4.6.8. Discussion
Photosynthesis is extremely important for plants to keep the growth and
development in pace under stressed conditions. However, abiotic stresses cause
deleterious effects on photosynthesis by damaging the photosynthetic machinery and
inhibiting the biosynthesis of photosynthetic pigments (Prasad et al., 2011b). In present
study the late sowing caused a decrease in chlorophyll contents in both varieties of barley
which might be attributed to low temperature during early vegetative growth (Farooq et
al., 2008a). It has been observed that low temperature causes a decrease in the
biosynthesis of chlorophyll contents due to suppressed gene expression for chlorophyll
synthesis (Yang et al., 2005). Similarly, Ahmed and Fayyaz-ul-Hassan (2015) reported a
decrease in chlorophyll content in wheat under late sown conditions. However, in present
study, seed priming improved the chlorophyll contents in both barley varieties under
normal as well as late sown conditions. This might be attributed to the protective role of
seed priming through enhanced osmolytes accumulation and antioxidants activities under
stressed conditions (Chen and Arora, 2013).
In present study, osmopriming improvedd the chlorophyll contents, as compared
to unprimed control. It has been observed that osmopriming improves the protection of
cellular membranes and organelles from stress caused oxidative burst resulting in
improved chloroplast ultrastructure, chlorophyll synthesis, chlorophyll photochemistry
and photosynthesis (Dai et al., 2017; Abid et al., 2018). Moreover, Ca2+ regulates the 223
NADK2 gene which encodes for NAD+ in chloroplast and deletion or down regulation of
this gene results in decreased chlorophyll biosynthesis and photosynthesis (Hochmal et
al., 2015).
224
Table 4.141: Analysis of variance for the influence of seed priming on chlorophyll contents of barley under optimum and late sowing time
SOV DFMean sum of squares
Chlorophyll a Chlorophyll b2014-15 2015-16 2014-15 2015-16
Replication (R) 3 0.00014 0.00001 0.00012 0.00025Sowing time (SD) 1 0.01960** 0.01756* 0.01210** 0.01210**
Error 1 3 0.00005 0.00107 0.00004 0.00013Varieties (V) 1 0.00010ns 0.01000** 0.00391** 0.00226*
SD×V 1 0.00490** 0.00006ns 0.00010ns 0.00090ns
Error 2 6 0.00020 0.00035 0.00022 0.00021Priming (T) 3 0.00524** 0.00257* 0.00142** 0.00021ns
SD×T 3 0.00088** 0.00289* 0.00016ns 0.00020ns
V×T 3 0.00382** 0.00064ns 0.00042* 0.00123**
SD×V×T 3 0.00208** 0.00408** 0.00029* 0.00055**
Error 3 36 0.00017 0.00074 0.00010 0.00012Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.142: Influence of seed priming on leaf chlorophyll a content (mg g-1 FW) of barley under optimum and late sowing time
Treatments
2014-15 2015-16November 30 December 30 November 30 December 30H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87
Control0.27 b 0.26 bc 0.18 g 0.25 cd
0.30 abc 0.27 b-e 0.24 ef 0.21 f
HP 0.26 bc 0.27 b 0.21 f 0.24 de 0.33 a 0.27 b-e 0.25 de 0.25 deOP 0.26 bc 0.25 cd 0.26 bcd 0.22 ef 0.29 bcd 0.25 de 0.27 b-e 0.25 deBP
0.33 a 0.26 bc 0.27 bc 0.27 bc 0.27 b-e 0.31 ab0.30 abc 0.25 de
Sowing time × Varieties × Seed priming LSD≤0.05 = 0.0187 (2014-15) and 0.0390 (2015-16)
Table 4.143: Influence of seed priming on leaf chlorophyll b content (mg g-1 FW) of barley under optimum and late sowing time
Treatments 2014-15 2015-16November 30 December 30 November 30 December 30
H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 0.13 de 0.14 cd 0.13 de 0.11 f 0.17 bc 0.16 c-f 0.16 c-f 0.14 gHP 0.17 ab 0.16 bc 0.14 cd 0.12 ef 0.19 ab 0.17 cd 0.15 d-g 0.14 gOP 0.17 ab 0.15 c 0.13 de 0.13 de 0.19 ab 0.18 bc 0.18 bc 0.13 hBP 0.18 a 0.15 c 0.15 c 0.12 ef 0.17 bc 0.20 a 0.15 d-g 0.15 efg
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 0.0142 (2014-15) and 0.0156 (2015-16)
225
226
Similar to our results, Rehman et al. (2015) reported that seed priming with CaCl2 and
moringa leaf extract improved the leaf chlorophyll content under normal and late sown
conditions. In current study biopriming also improved the chlorophyll contents, as
compared to unprimed control, which might be due to endophytic bacteria that decreases
chlorophyll degradation by inhibiting the production of ethylene through production of
ACC deaminase enzyme rendering the plants stay green for longer periods (Dimpka et al.,
2009). Similarly, Nadeem et al. (2007) observed that seed inoculation of maize with ACC
deaminase containing Pseudomonas syringae, P. fluorescens and E. aerogenes improved
the proline, water relations and chlorophyll contents under normal and salt stressed
conditions.
4.6.9. Grain proximate analysis
4.6.9.1. Grain crude protein content
Sowing time and seed priming treatments significantly affected grain crude
protein content, during both years; barley varieties significantly differed during 2014-15
but did not differ significantly during 2015-16. Interaction between sowing time and
varieties was non-significant during 2014-15 but significant during 2015-16. Interaction
between sowing time and seed priming was non-significant, during both growing seasons.
Interaction between varieties and seed priming, and three way interaction among sowing
time, varieties and seed priming was significant during 2014-15 but non-significant
during 2015-16 (Table 4.144). Grain crude protein content was decreased by late sowing
than optimum sowing. The variety Haider-93 produced more grain protein content than
Frontier-87. The seed priming treatments improved the grain crude protein content of
both varieties at both sowing times, as compared to unprimed control. During 2014-15,
osmopriming of Haider-93 and biopriming of Frontires-87 led to maximum increase in
grain crude protein content at early and late sowing, respectively. During 2015-16, late
sowing decreased the protein content while seed priming improved the grain protein
content. Moreover, at optimum sowing Haider-93 produced more grain protein content
while at late sowing Frontier-87 produced more grain protein content (Tables 4.145,
4.146b).
4.6.9.2. Grain starch content
The grain starch content was significantly affected by sowing time and seed
priming; however, barley varieties did not differ significantly, during both years.
Similarly, the interactions between sowing time and varieties, sowing time and seed
priming, varieties and seed priming, and three way interaction among sowing time, 227
varieties and seed priming was non-significant, during both years (Table 4.144). Grain
starch content was lowered by late sowing as compared to optimum sowing, during both
years. However, seed priming treatments improved the grain starch content, as compared
to unprimed control. The greatest improvement was caused by biopriming. However,
osmopriming and hydropriming produced similar results, during both years (Table 4.147).
4.6.10. Discussion
Grain quality in terms of protein and starch contents was negatively affected by
late sowing of barley. This might be attributed to decreased photosynthesis, nutrient
uptake and plant growth by late sowing. It has been observed that early planted barley
have more grain protein contents due to healthier plants with longer root systems that
cause higher uptake of residual nitrogen and have more time for grain filling as compared
to late sowing (Ozturk et al., 2008). Similarly, Seleiman et al. (2011) reported that late
sowing reduced the grain carbohydrates, as compared to optimum sowing. Moreover, late
sowing exposes the plants to terminal heat stress that shortens the grain development
period as a result poor quality and shriveled grains are achieved (Ehdaie et al., 2006;
Kaur and Behl, 2010; Farooq et al., 2011). In late sowing, high temperature during grain
development caused an increase in the ratio of amylose to amylopectin but decreased the
ratio of glutenin to gliadin ratio that negatively affected the dough elasticity (Hurkman et
al., 2003).
In present study, seed priming improved the grain protein as well starch contents
of barley under normal and late sown conditions. The improved grain protein and starch
contents by seed priming might be attributed to better chlorophyll contents, enhanced
LAI, CGR and improved grain filling rate as observed in present study. Similar results
were reported by Mahboob et al. (2015) that seed priming with CaCl2, salicylic acid and
moringa leaf extract improved the crude protein content in maize under normal and late
sowing conditions by enhancing LAD and NAR. Seed priming might have improved the
grain starch content by decreasing the damaging effects of high temperature during grain
filling period in late sown barley because starch synthase enzyme which is involved in
starch synthesis and accumulation is highly sensitive to high temperatures and its activity
is decreased by temperature exceeding 20°C (Keeling et al., 1994). In present study, the
improved grain protein and starch contents may be attributed to endophytic bacteria
which enhances nutrient uptake and assimilation (Santoyo et al., 2016), and enhances
photosynthesis and nitrate reductase activity (Marcos et al., 2016).
4.6.11. Economic and marginal analysis228
The economic analysis revealed that late sowing caused a reduction in net benefits
and BCR in both barley varieties. However, varieties performed differently regarding
grain yield and net benefits. Haider-93 gave higher net benefits and BCR under both
normal and
229
Table 4.144: Analysis of variance for the influence of seed priming on grain crude protein and starch contents of barley under optimum and late sowing time
SOV DFMean sum of squares
Grain crude protein content Grain starch content2014-15 2015-16 2014-15 2015-16
Replication (R) 3 0.064 4.054 37.154 39.880Sowing time (SD) 1 3.730** 7.798** 384.356* 405.720*
Error 1 3 0.017 0.021 29.294 27.196Varieties (V) 1 0.447* 0.656ns 2.016ns 5.108ns
SD×V 1 0.046ns 1.243* 53.071ns 34.810ns
Error 2 6 0.070 0.155 33.527 32.816Priming (T) 3 1.962** 3.236** 102.793* 120.098*
SD×T 3 0.050ns 0.283ns 23.924ns 33.001ns
V×T 3 0.621** 0.113ns 32.832ns 42.239ns
SD×V×T 3 0.254* 0.346ns 32.413ns 22.091ns
Error 3 36 0.088 0.315 33.419 33.589Total 63
SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant
Table 4.145: Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30
H-93 F-87 H-93 F-87Control 10.65 de 10.69 cde 10.16 fg 10.04 gHP 11.47 a 11.17 ab 10.96 bcd 10.53 efOP 11.48 a 10.97 bcd 11.11 abc 10.46 efgBP 11.40 a 11.29 ab 10.62 de 11.37 ab
Sowing time × Varieties × Seed priming LSD≤0.05 = 0.4245
Table 4.146a: Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30 MeanH-93 11.23 a 10.26 c 10.74F-87 10.75 b 10.33 c 10.54Mean 10.99 A 10.29 B
Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 0.1148, Sowing time × Varieties LSD≤0.05 = 0.3410
230
Table 4.146b: Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2015-16)Treatments H-93 F-87 MeanControl 10.04 10.02 10.03 CHP 10.86 10.56 10.71 BOP 11.30 10.93 11.11 ABP 10.77 10.66 10.72 ABMean 10.74 10.54
Seed priming LSD≤0.05 = 0.4023
Table 4.147: Influence of seed priming on grain starch content (%) of barley under optimum and late sowing time
Treatments 2014-15 2015-16November 30 December 30 Mean November 30 December 30 Mean
Control 57.76 54.88 56.32 B 58.11 54.80 56.45 BHP 59.06 55.89 57.47 AB 59.95 57.27 58.61 AOP 60.54 56.46 58.50 A 60.74 56.40 58.57 ABP 61.05 57.24 59.14 A 61.57 57.51 59.54 AMean 59.60 A 56.12 B 60.09 A 56.49 B
Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 4.3061 (2014-15) and 4.1491 (2015-16), Seed priming LSD≤0.05 = 4.1451 (2014-15) and 0.0443 (2015-16)
231
late sowing conditions which was related to higher grain yield than Frontier-87.
Moreover, seed priming improved the net benefits and BCR of both varieties under both
sowing times by improving the grain yield despite of higher cost of production by seed
priming treatments than control and hydropriming. However, at optimum sowing time,
highest net returns and BCR was recorded by osmopriming of Haider-93 and it was
followed by osmopriming of Frontier-87. Whereas, at late sowing, osmopriming of
Haider-93 gave highest net returns and BCR, and it was followed by biopriming of
Frontier-87 (Table 4.148).
The marginal analysis revealed that MRR was decreased by late sowing in both
varieties. Haider-93 gave higher MRR than Frontier-87. Moreover, osmopriming gave the
highest MRR in early sown crop while hydropriming was superior in late sown crop.
Biopriming gave the MRR in both sowing times but it could not exceed hydropriming and
osmopriming. In optimum sowing, osmopriming of Haider-93 gave highest MRR and it
was followed by osmopriming of Frontier-87. However, in late sowing, hydropriming
Haider-93 produced highest MRR and it was followed by hydropriming of Frontier-87
(Table 4.149).
4.6.12. Discussion
In present study, late sowing of both varieties substantially decreased net returns
and BCR by significantly decreasing the grain and straw yield due to poor plant growth
and development. However, Haider-93 gave more net returns and BCR than Frontier-87
which was associated with higher grain yield due to more tolerance to adverse climatic
conditions due to late sowing. Moreover, seed priming especially osmopriming improved
the net returns under optimum and late sowing conditions, as compared to unprimed
control. Seed priming treatments produced more net returns despite of high initial cost
which was compensated by higher grain yield. Aune et al. (2011) observed increase in
economic returns by seed priming in sorghum and pearl millet owing to increased yield
and concluded that it is a low cost, low risk technique which can be adopted by poor
farmers. Similarly, Jafar et al. (2012) reported improvement in economic returns by
osmopriming with CaCl2 under normal as well as saline conditions indicating that it has
the potential to improve the grain yield as well as economic returns in a range of growing
conditions. In conclusion seed priming can be adopted to improve the crop performance
and economic returns under optimum as well as late sown conditions.
232
Table 4.148: Economic analysisTreatments Grain
yield(t ha-1)
Adjusted grain yield
(t ha-1)
Straw yield
(t ha-1)
Adjusted straw yield
(t ha-1)
Gross income
(Rs.)
Fixed cost(Rs.)
Variable cost(Rs.)
Total cost(Rs.)
Net benefits
(Rs.)
BCR
November 30 H-93 Control 2.71 2.44 5.43 4.89 128029 66902 9747 76649 51380 1.67HP 3.15 2.84 5.59 5.03 138556 66902 11590 78492 60064 1.77OP 3.70 3.33 6.26 5.64 161459 66902 16727 83629 77830 1.93BP 3.48 3.14 6.08 5.47 152757 66902 16541 83443 69314 1.83
F-87 Control 2.64 2.38 5.63 5.06 120340 66902 9502 76404 43937 1.58HP 3.00 2.70 5.82 5.24 134177 66902 11050 77951 56225 1.72OP 3.50 3.15 6.29 5.66 154300 66902 16000 82902 71399 1.86BP 3.25 2.93 6.27 5.65 145334 66902 15711 82613 62722 1.76
December 30 H-93 Control 2.05 1.85 4.67 4.20 94948 66902 7395 74297 20652 1.28HP 2.42 2.18 5.00 4.50 109541 66902 8953 75855 33687 1.44OP 2.81 2.53 5.71 5.14 126706 66902 13502 80403 46303 1.58BP 2.75 2.48 5.31 4.78 123003 66902 13909 80811 42193 1.52
F-87 Control 1.99 1.79 4.75 4.27 93128 66902 7176 74077 19051 1.26HP 2.43 2.18 4.95 4.46 109614 66902 8982 75883 33731 1.44OP 2.63 2.36 5.46 4.91 119071 66902 12852 79754 39317 1.49BP 2.75 2.48 5.46 4.91 123671 66902 13911 80813 42859 1.53
H-93: Haider-93, F-87: Frontier-87, HP: Hydropriming, OP: osmopriming, BP: Biopriming, BCR: Benefit cost ratio
233
Table 4.149: Marginal analysisTreatments Variabl
e cost (Rs.)
Marginal variable cost (Rs.)
Net field
benefits (Rs.)
Marginal net field benefits
(Rs.)
Marginal rate of return
(%)November 30 H-
93Control 9747 - 118282 - -HP 11590 1843 126966 8684 471BP 16541 4951 136216 9250 187OP 16727 186 144732 8516 4578
F-87 Control 9502 - 110838 - -HP 11050 1548 123127 12289 794BP 15711 4661 129623 6496 139OP 16000 289 138300 8677 3001
December 30 H-93
Control 7395 - 87553 - -HP 8953 1558 100588 13035 837OP 13502 4549 113205 12616 277BP 13909 407 109094 - D
F-87 Control 7176 - 85953 - -HP 8982 1806 100632 14680 813OP 12852 3871 106219 5587 144BP 13911 1059 109760 3541 334
H-93: Haider-93, F-87: Frontier-87, HP: Hydropriming, OP: osmopriming, BP: Biopriming
234
CHAPTER 5
SUMMARY
Studies on evaluating the potential of seed priming in improving the performance
of barley varieties under late sown and abiotic stress conditions was evaluated at green
house and field of University of Agriculture, Faisalabad, and glass house of Texas A&M
University, USA. In pot experiments, the potential of seed priming in improving the
tolerance of barley against drought, salinity and terminal heat stress was explored. In
hydroponics experiments effect of seed priming on performance of barley under osmotic,
salt and Cd stress was evaluated. The pot and hydroponics experiments were conducted
by using completely randomized design (CRD) with factorial arrangement and four
replications, except the experiment conducted to determine effect of seed priming on
barley under terminal heat stress, in which six replications were used. Data were collected
regarding emergence, growth, yield, photosynthesis, chlorophyll fluorescence,
chlorophyll contents, osmolytes, lipid peroxidation, ion toxicity, water relations and grain
nutrient contents. In field experiment, the influence of seed priming on the performance
of barley under optimum and late sown conditions was explored. The experiment was
conducted with randomized complete block design (RCBD) with split-split plot
arrangement having four replications and the net plot size of 6 m × 2.7 m. Data regarding
emergence, growth, allometry, grain filling, yield and related traits, and grain protein and
starch contents were collected using standard procedures. Data were analyzed statistically
using the Fisher’s analysis of variance (ANOVA) technique and the least significant
difference (LSD) test at 5% probability was used for comparison of treatments’ means.
Economic analysis was carried out to assess the economic feasibility. Brief description of
results from different experiments is given below:
Experiment 1: Potential role of seed priming in improving the resistance against
drought in barley
Seeds of two barley varieties (Haider-93 and Frontier-87) primed with water
(hydropriming), CaCl2 (osmopriming) and Enterobacter sp. strain FD17 (biopriming)
were sown in pots. Dry seed was taken as control. After seedling establishment, drought
levels (80, 60 and 40% water holding capacity) were imposed. Drought stress decreased
the plant growth, yield, chlorophyll contents, cell membrane stability, disturbed water
relations and decreased grain nutrient contents while enhanced osmolytes accumulation
235
and lipid peroxidation in both varieties of barley and the deleterious effects were
increased with increase in its severity. However, the negative effects of drought stress
were more pronounced in Frontier-87 than Haider-93. Seed priming improved the
emergence, plant height, leaf area, number of productive tillers, number of grains per
spike, 100-grain weight, grain yield, harvest index and chlorophyll contents under well-
watered and drought stress conditions, as compared to unprimed control. Moreover, seed
priming improved the water relation traits viz. leaf relative water content, leaf water
potential, leaf osmotic potential and leaf pressure potential, and cell membrane stability
by enhanced accumulation of osmolytes i.e. phenolics, total soluble proteins, free proline
and glycine betaine, and decreased lipid peroxidation in both barley varieties under severe
drought stress, as compared to unprimed control. The order of improvement in yield and
related traits by seed priming treatments was biopriming > osmopriming > hydropriming
> control. In addition, biopriming effectively improved the grain Zn, Mn and B contents
under well-watered and drought conditions, as compared to unprimed control.
Experiment 2: Potential role of seed priming in improving the salt resistance in
barley
In this experiment seeds of two barley varieties (Haider-93 and Frontier-87)
primed with water (hydropriming), CaCl2 (osmopriming) and Enterobacter sp. strain
FD17 (biopriming) were sown in pots. Dry seed was taken as control. After seedling
establishment salinity levels (50, 100 and 150 mM NaCl) were imposed. Salinity caused a
reduction in growth, yield, biosynthesis of chlorophyll, perturbed water relations and
decreased grain nutrient contents while exalted osmolytes, MDA and Na accumulation in
barley. The damaging effect of salinity was increased with increase in its severity.
Although salinity imposed its deleterious effects on both varieties but its negative effects
were more prominent on Frontier-87. Seed priming improved the emergence, plant
growth, number of productive tillers, number of grains per spike, 100-grain weight, and
grain yield and harvest index in both varieties under salt stress, as compared to unprimed
control. Seed priming improved the biosynthesis of chlorophyll a and b, leaf relative
water content, leaf water potential, leaf osmotic potential and leaf pressure potential by
exaggerated accumulation of osmolytes such as phenolics, total soluble proteins, free
proline and glycine betaine contents in both varieties under salt stress, as compared to
unprimed control. Cell membrane stability was improved by seed priming through
decreased lipid peroxidation under salt stress. Furthermore, seed priming decreased the
ion toxicity by lowering the Na content while increasing the K content in both barley 236
varieties, as compared to unprimed control. Barley performance regarding yield and
related traits under moderate salinity was improved the most by biopriming while under
severe salinity by osmopriming. Moreover, biopriming improved the grain Zn, Mn and B
contents under normal and salt stress conditions, as compared to unprimed control.
Experiment 3: Potential role of seed priming in improving the resistance against
osmotic and salt stresses in barley
The experiment was carried out in hydroponics. Seedlings of two barley varieties
(Haider-93 and Frontier-87) primed with water (hydropriming), CaCl2 (osmopriming) and
Enterobacter sp. strain FD17 (biopriming) were raised in sand filled polythene bags. Dry
seed was taken as control. After seedling establishment the seedlings were transplanted in
hydroponics, and osmotic (-0.8 MPa using PEG) and ionic (-0.8 MPa using NaCl)
stresses were imposed. Osmotic and salt stress decreased the seedling growth, biomass
production, and chlorophyll a and b contents while increased the accumulation of
osmolytes and MDA in both varieties. Salt stress also caused ion toxicity through
enhanced accumulation of Na in barley plants. However, more reductions in biomass
were observed in Frontier-87. Seed priming improved the shoot and root length, and fresh
and dry biomass, chlorophyll a and b contents, and accumulation of phenolics, total
soluble proteins, free proline and glycine betaine while reduced the MDA content under
both osmotic and salt stress, and Na content under salt stress, as compared to unprimed
control. Among all seed priming treatments the biopriming was most effective in
improving barley performance under osmotic stress while osmopriming was superior in
improving barley stress tolerance against salt stress.
Experiment 4: Potential role of seed priming in improving the resistance against
cadmium stress in barley
The experiment was carried out in hydroponics. Seedlings of two barley varieties
(Haider-93 and Frontier-87) primed with water (hydropriming), CaCl2 (osmopriming) and
Enterobacter sp. strain FD17 (biopriming) were raised in sand filled polythene bags. Dry
seed was taken as control. After seedling establishment the seedlings were transplanted in
hydroponics, and Cd toxicity stress levels (viz. 0, 8 and 12 mg L-1 water) were imposed.
Cadmium stress reduced seedling growth and biomass production, chlorophyll
biosynthesis and increased the osmolytes, MDA and Cd accumulation in tested barley
varieties depending on its severity. However, reductions in biomass of Haider-93 were
less as compared to Frontier-87. Furthermore, seed priming improved the shoot length
root length, and shoot and root fresh and dry biomass, chlorophyll a and b contents, 237
phenolics, total soluble proteins, free proline and glycine betaine contents while
decreased MDA and Cd contents in both varieties under Cd toxicity stress, as compared
to unprimed control. The order of improvement in barley stress tolerance was biopriming
> osmopriming > hydropriming > control.
Experiment 5: Potential role of seed priming in improving the resistance against
terminal heat stress in barley
Seeds of USA cultivar Solum were primed with water (hydropriming) and CaCl2
(osmopriming), and sown in pots. Dry seed was taken as control. At reproductive stage
two levels of heat stress viz. control (25/18°C day/night) and high temperature (35/25°C
day/night) were applied. Terminal heat stress decreased the plant growth, yield,
photosynthesis, chlorophyll fluorescence, chlorophyll contents and cell membrane
stability while increasing lipid peroxidation, as compared to control. However, seed
priming improved plant height, number of productive tillers, number of grains per spike,
100-grain weight, grain yield and harvest index under terminal heat stress, as compared to
unprimed control. Moreover, seed priming improved the photosynthesis by enhancing
stomatal conductance, intercellular CO2 concentration, transpiration and CUE, as
compared to unprimed control. Chlorophyll contents, QY and ETR was improved by seed
priming which led to enhanced photosynthetic efficiency of barley under normal and
terminal heat stress conditions. Seed priming also improved the cell membrane stability
by enhancing the phenolics contents and decreasing the lipid peroxidation as compared to
unprimed control, under heat stress. The order of improvement in growth, yield
photosynthesis and stress tolerance was osmopriming > hydropriming > control.
Experiment 6: Influence of seed priming on the productivity of late sown barley
Seeds of two barley varieties (Haider-93 and Frontier-87) primed with water
(hydropriming), CaCl2 (osmopriming) and Enterobacter sp. strain FD17 (biopriming)
were sown in field at November 30 and December 30. Dry seed was taken as control.
Late sowing decreased emergence, growth, yield, dry matter accumulation, grain filling
duration, chlorophyll contents, and grain protein and starch contents in both barley
varieties, as compared to optimum sowing time. Haider-93 performed better regarding
growth and yield under late sown conditions than Frntier-87. Seed priming improved the
emergence, plant growth, LAI, TDM accumulation, CGR, grain filling rate, yield and
related traits, and grain protein and starch contents under both optimum and late sowing,
ascompared to unprimed control. The greatest improvement in grain yield and harvest
index was caused by osmopriming followed by biopriming. The economic analysis 238
revealed that late sowing decreased the economic returns and BCR which was improved
by seed priming treatments. Among all, biopriming caused maximum improvement in
BCR under both optimum and late sown conditions; while, highest MRR was produced
by osmopriming under optimum sowing time and hydropriming under late sowing.
Conclusion
Abiotic stresses and late sowing decreased the plant growth and yield of barley by
negatively affecting the plant physiological processes and grain filling attributes.
However, seed priming effectively improved the growth and productivity of barley
varieties under stressed conditions by improving the osmolytes accumulation, chlorophyll
contents, water relations, nutrient relations, photosynthesis, grain filling rate and
decreasing the lipid peroxidation under stressed conditions.
239
Future research thrusts
Proteomic and metabolomic basis of seed priming in inducing resistance against
abiotic stresses should be investigated
Influence of seed priming especially biopriming on root growth traits should be
explored
Enzymes responsible for grain formation (alpha-amylase, starch synthase and starch
synthetase) should be investigated under late sown conditions
240
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Appendix 1: Fixed cost (Experiment 6)Sr.
No.
Operation/input No./Amount/
Quantity per ha
Rate/unit
(Rs.)
Cost/ha
(Rs.)
1 Land preparation operations
Ploughing 2 1475 2950
Planking 1 740 740
2 Seed and sowing operations
Seed 75 40 3000
Drill charges 1 1477 1477
3 Fertilizer cost
Fertilizer bags
Urea 1.6 1850 2923
DAP 1.5 3750 5700
SOP 1.0 2370 2370
Transportation charges 4.1 20 82
Fertilizer application charges 1 man day 400 400
4 Irrigation charges
Canal water charges - - 200
Water channel cleaning 1 man per day 400 400
5 Plant protection measures
Herbicide 2.5 L 650/L 1625
Application charges 1 man per 1/2 day 400 200
6 Markup on investment 9% annual 27830 2505
7 Land rent @ Rs. 62500 per anum 5 months 5208 26040
8 Agricultural income tax for 5 months - - 40
9 Harvesting charges 7.5 mounds 1600 12000
10 Artisan charges 10 kg 40 1000
11 Marketing cost - - 1500
12 Management cost 5 months 350 1750
Gross cost - - 66902
276
Appendix 2: Variable cost (Experiment 6)Treatments Cost of seed
priming (Rs.)Threshing
charges (Rs.)Total variable
cost (Rs.)
November 30 H-93 Control 0 9747 9747HP 250 11340 11590BP 3400 13327 16727OP 4000 12541 16541
F-87 Control 0 9502 9502HP 250 10800 11050BP 3400 12600 16000OP 4000 11711 15711
December 30 H-93 Control 0 7395 7395HP 250 8703 8953OP 3400 10102 13502BP 4000 9909 13909
F-87 Control 0 7176 7176HP 250 8732 8982OP 3400 9452 12852BP 4000 9911 13911
H-93: Haider-93, F-87: Frontier-87, HP: Hydropriming, OP: osmopriming, BP: Biopriming
277
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