effect of drought stress on the physiology and yield … · effect of drought stress on the...

International Journal of Advancements in Research & Technology, Volume 2, Issue 7, July-2013 419 ISSN 2278-7763

Copyright © 2013 SciResPub. IJOART

Research article

Effect of Drought Stress on the Physiology and Yield of the Pakistani Wheat Germplasms

Ammar Ali1, Nawab Ali2, Nimat Ullah2, Farman Ullah2, Muhammad Adnan3, Zahoor Ahmed Swati1 1Institute of Biotechnology and Genetic Engineering, KPK Agriculture University, Peshawer, Pakistan. 2 Department of Biotechnology and Genetic Engineering, Kohat University of Science & Technology, Kohat, Pakistan. 3Department of Botany, Kohat University of Science & Technology, Kohat, Pakistan.

Abstract

Drought stress is the most important factor and ever-growing problem limiting wheat (Triticum

aestivum L.) productivity worldwide. Wheat has physiological mechanisms that enable them to

adapt drought stress and this adaptation may vary among different genotypes. This study was

performed to investigate the physiological responses in twelve wheat genotypes under drought

stress to identify drought tolerant genotypes. Stress was imposed by growing the genotypes

under four irrigation treatments (T1-380 ml, T2-190 ml, T3-126 ml and T4-95 ml) with each

fifteen days interval. The results revealed that electrolytes leakage was increased and other

physiological characteristics such as turgidity, relative leaf water contents and plant yield were

decreased during the increase in drought stress. The Tatara, ZAS-08, ZAS-42 and Ghaznavi-98

wheat genotypes exhibited the normal physiology and were considered as drought tolerant

genotypes. The drought tolerant genotypes specified in this study will be grown in rain fed

regions in order to improve the crop productivity and will be used in wheat breeding programs to

produce a stress tolerant genotype.

Key words: Triticum aestivum L, Physiological characteristics, Drought stress.

Introduction

Drought stress is one of the most important factors limiting plant growth and crops production

worldwide more than any other biotic or abiotic stress [1, 2]. It is an ever-growing problem that

harshly limits the crop production and result in important agricultural losses especially in arid

and semiarid areas [3]. The response of plants to drought stress is very complicated and they

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manage stress through stress avoidance approaches that depends on genotype. Plants under stress

try to maintain their metabolic and structural capacity to improve their potential under that vary

stress through modified gene expression [4]. Wheat is the most important food crop cultivated

throughout the world and is the major source of proteins and calories which are almost 72% in an

average diet [5]. The current production of wheat is not sufficient to meet the demands of rapidly

growing population [6]. Although, breeders are working hard to improve wheat production,

however increasing wheat production in drought environments has been more complex to

achieve [7].

Yield components and drought resistance are controlled at independent genetic loci, therefore the

identification of physiological traits that are responsible for drought tolerance should be

considered in the breeding programs [8]. Breeding efficiency could be improved if existing

physiological and morphological characteristics associated with yield components under an

environmental stress could be identified and used as selection criteria for traditional plant

breeding [9]. According to the previous literatures, there is an association between physiological

responses and tolerance mechanisms of plants against drought stress i.e. membrane stability [10]

high relative water content [11] pigment content stability [12, 13]. It was reported that drought

tolerant varieties in barley maintained higher relative leaf water content (RLWC) under drought

stress [14]. The breeding approaches to develop new or improved cultivars against stress need a

thorough understanding of the reactions of plant tissues or organs against the specific stress.

Thus, it is very important to identify those wheat genotypes which have the ability to tolerate

water stress. These stress tolerant genotypes can be used as reliable selection criteria in the

breeding programs.

The main objective of this work was to investigate physiological traits that are associated with

drought stress in wheat genotypes and to find out the drought tolerant genotypes that could be

used for yield improvement either by introducing these genotypes in rain fed area or using in

wheat breeding programs.

Materials and Methods

Physiological Studies

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Twelve wheat genotypes were chosen (Table 1) and seeds were collected from Cimmyt spring

wheat nurseries and sown under four irrigation conditions (T1-380 ml, T2-190 ml, T3-126 ml

and T4-95 ml) with each 15 days interval. After maturation, investigations were made to see the

effect of drought stress on physiological characteristics and yield trait. Physiological

characteristics (Electrolytes leakage, Turgidity, Relative leaf water contents) were measured at

three different stages i.e. 60 days, 95 days and 120 days after sowing.

Electrolytes leakage Electrolyte leakage into the solution was measured in 5 cm2 leaf discs after exposure to various

stress treatments with a Consort C-931 conductivity meter. The leaf discs were incubated in 5 ml

double distilled water for 3 hours at 25oC with shaking and initial conductivity of the solution

was determined. Final conductivity of the solution was determined after autoclaving the samples

(100% electrolyte leakage). The amount of electrolytes leakage attributable to different growth

conditions and varieties were estimated as a percentage of initial to final conductivity.

Electrolytes leakage was calculated by using following formula.

Electrolytes leakage (%) =Initial readingFinal reading × 100

Turgidity:

Calculating turgidity, weighted fresh leaf (W1) and then kept the leaf in distilled water for 24

hours and weighted again (W2). Turgidity was calculated from the following formula.

Turgidity (gm) = W2 − W1

Relative leaf water contents

To measure RLWC, third leaf on main stem of each plant was used. The samples were surface

dried gently with tissue paper, wrapped in polythene bags. Soon after arriving laboratory, leaves

were weighed to measure fresh weight (FW). The samples were then soaked in large plastic tubs

containing distilled water and were left over night at room temperature. Next morning, these

leaves were carefully bloated with tissue paper prior to the determination of turgid weight (TW).

Leaf samples were then oven dried for 48 hours at 80oC. Dried leaves were then weighed to

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record dry weight (DW). Leaf water contents were calculated by following formula (Schonfeld et

al., 1988) [15].

RLWC =Fresh wt− dry wt

Turgid wt− dry wt × 100

Yield Trait

Plants were randomly selected and hand threshed separately, average number of grains per spike and yield per plant were recorded in grams.

Results and Discussion

Drought stress affect wheat productivity grown in dry and semidry areas and reduces plant yield

more than any other environmental stress [16-19]. In this study, significant differences were

reported in total yield per plant (YPP) and number of grains per spike (NGPS) amongst different

varieties in drought stress. Drought stress negatively affect yield per plant and number of grains

per spike, as drought stress increased from T1 to T4, the YPP and NGPS decreased. Yield of

wheat varieties were considerably decreased when they were allowed to grow in minimum

annual rainfall regions [20]. Highest YPP mean values were reported in decreasing order as Tatara

(7.45 gm), Ghaznavi-98 (6.40 gm), Zas-08 (6.17 gm) and Zas-42 (5.70 gm) while lowest YPP

mean values in increasing order as 26-ESWYT-124 (1.52 gm), Zas-34 (2.10 gm) and 38-

IBWSN-1077 (2.47 gm) (Table 2). The result revealed that Tatara, Ghaznavi-98, Zas-08 and

Zas-42 genotypes has given optimal yield per plant at all the four treatments. Similarly numbers

of grains per spike were also reduced with an increase in drought stress. Highest NGPS mean

values were reported in decreasing order as Tatara (25.9), Zas-42 (25.7), SCO-27 (24.3) and Zas-

08 (22.8) and lowest values in increasing order as 38-IBWSN-1059 (14.12), 38-IBWSN-1077

(14.23) and Zas-70 (14.63) (Table 2). This is also supported by the findings of Chandler and

Singh (2008) that numbers of grains per spike were decreased under drought stress [21]. Water

stress has been reported to affect all the yield components, mainly the number of grains per spike

and the number of spikes per plant [22, 23]. It has been recognized that decrease in yield and yield

components under drought stress is a key concern in developing countries of the world [24].

The biotic and abiotic stresses target the cell membrane of plants at first [25]; however, the

drought tolerant plants maintain its integrity and stability in drought stress [26]. Membrane

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stability is important for plant growth and development as it tolerate drought stress against

plants, since drought stress caused water loss from plant tissues which damage membrane

structure and function [27] due to electrolytes leakage. In this study, the lowest mean values of

electrolytes leakage were reported for Zas-42 (9.22%) after 60 days of sowing which increased

to 13.5% and 15.5% after 95 and 120 days of sowing, respectively (Table 2). It revealed that

when plants progressed toward maturity, the electrolytes leakage increased gradually with an

increase in drought stress. The treatments differences were statistically significant at all the three

stages. The genotypic differences and the interaction of the treatments with genotypes (varieties)

were also significant at all the three stages. Electrolytes leakages revealed positive correlations

with drought stress at all three stages as given in Table 2. As drought stress was increased from

T1 to T4, it resulted in an increase in electrolytes leakage. The leakage was due to cell

membranes rupture which becomes more permeable [28]. After 120 days, the lowest electrolyte

leakage was reported for ZAS-42 (15.5%), ZAS-08 (16.4%) and Tatara (17.2%). These wheat

genotypes were considered as drought avoidant genotypes as they avoided drought stress by

maintaining cell membrane stability, resulted in low electrolytes leakage and hence given high

yield. ZAS-70, ZAS-67 and 38-IBWSN-1077 wheat genotypes have the ability of tolerating low

electrolytes leakage to produce reasonable yield. The poor yield of 38-IBWSN-1052, SCO-27

and ZAS-34 wheat genotype under drought stress was related to their inability to avoid or

tolerate stress and high electrolytes leakage that was recorded 23.8%, 23.6% and 23.4%,

respectively. The results obtained from electrolyte leakage in this study revealed that membrane

integrity of drought tolerant genotypes was stable as compared to other genotypes; this

association of electrolyte leakage and drought tolerance was also reported by other researchers

[29, 2].

The RLWC of the leaves indicate the water condition of the cells and have important correlation

with biotic and abiotic stress tolerance [2]. It has been reported that, RLWC of the leaves has

strong association with drought tolerance [30] and it is a good indicator of drought stress than

other physiological and biochemical characteristics of the crop plants [31]. Our results revealed

significant differences in RLWC among varieties at three different stages and showed that,

retention ability of the plant was significantly different at different growth stages. The maximum

RLWC was reported in Tatara 88.5%, 79.3% and 74.2% after 60, 95 and 120 days of sowing,

respectively (Table 2). It showed that RLWC was decreased with the age of plant because

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RLWC was high after 60 days in comparison to 95 and 120 days of the sowing; this is also

supported by other literatures that as plants progressed toward maturity, water retention ability

decreased [31]. Similarly turgidity was also decreased with an increase in drought stress, because

weight of plants was high during 60 days in comparison to 95 and 120 days. This means that

plants were more turgid at 60 days as compared to 95 and 120 days of the sowing (Table 2). This

variation in RLWC of leaf and turgidity may be due to the ability of the tested wheat genotypes

to absorb more water from soil and also to control water loss through the stomata [32]. It may also

be due to the variation in the ability of wheat genotypes to avoid stress by maintaining tissue

turgor osmotically. Highest RLWC after 120 days of sowing was reported in Zas-42 (76.8%),

Tatara (74.2%), Zas-67 (72.4%) and Zas-08 (72.0%) as given in Table 2. This revealed that, at

all the three stages, ZAS-08, ZAS-42, Tatara, and ZAS-67 maintained higher RLWC and is

considered as drought tolerant genotypes while SCO-27, 26-ESWYT-124, 38-IBWSN-1059,

ZAS-34 have low RLWC and is considered moderate drought tolerant genotypes. These results

were supported by Schonfeld et al., (1988) that RLWC may be used as a selection criterion in

breeding for improved drought resistance in wheat genotypes [15].

This study allowed us to recognize those physiological characteristics that are associated with

drought stress, and screen out appropriate wheat genotypes, which can be introduced in arid area

to produce high yield in drought conditions and can be further used in breeding programs to

produce a stress tolerant genotype.

Conclusion

It has been concluded that wheat yield was significantly affected by physiological traits in

drought stress conditions. With respect to physiological and yield traits, Tatara, Ghaznavi-98,

ZAS-08 and ZAS-42 wheat genotypes revealed maximum drought tolerance and can be

successfully grown in arid region without much loss of wheat productivity. Thus, screening of

drought tolerant wheat genotypes on the basis of physiological traits may be a useful tool for the

breeding programs.

References

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Table 1: Pedigree of the twelve wheat genotypes including 10 wheat advance lines used in this

study.

Serial

Number

Varieties/Adv.Lines Pedigree Breeding History

1 ZAS-70(16) Inqalab90*2/Tukuru CGSS99B00015F-099Y-099M-

099M-31Y-OB


099Y-099M-29Y-0B


099Y-099M-52Y-OB

4 ZAS-08(08) PBW343*2/Kukum CGSS99B00041F-099Y-099M-

099Y-099M-34Y-OB

5 ZAS-34 N.A N.A

6 26-WSWYT-124 RABE/6/WRM/4/FN/3*TH/K58/2*N/3/AU5-

6869/5/w

CMSS95YOA33OS-0100Y-51-

IDH-OY-O5B-OY

7 38-IBWSN-1098 CBRD/BCN CMSS94B00007S-0300M-

0100Y-0100M-17Y-7M-0Y

8 38-IBWSN-1059 SW89.5277/BORL95/SKAUZ CMSS93Y03172T-19Y-010M-

010Y-010M-3Y-3M-OY

9 38-IBWSN-1077 KUAZ/SITE CMSS933B01068S-9Y-010M-

010Y-010M-2Y-OM-2KBY-

OKBY-OM

10 38-IBWSN-1052 CROC-1/AE.SQUARROSA

(205)//KAUZ/3/ATTILA

CMSS93Y01031S-13Y-5KBY-

010M-010Y-5M-OKBY-OM-

9KBY

11 Ghaznavi-98 Jup/BJy/S/Ures N.A

12 Tatara Jup/ALD/S//KLT/S/3VEE/S N.A

N. A; Not Applicable

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Table 2. The physiological characteristics of twelve wheat genotypes in mean values for different

treatments and different stages (drought stress).

Varieties RLWC (%) Turgidity (gm) Electrolytes leakage (%) NGPS YPP (gm)

After 60 days

After 95 days

After 120 days

After 60 days

After 95 days

After 120 days

After 60 days

After 95 days

After 120 days

Mean

values

Mean

values

SCO-27 76.775 66.775 64.125 0.039 0.036 0.023 18.233 20.475 23.600 24.367 3.378

38-IBWSN-1052

76.125 70.450 65.475 0.037 0.033 0.014 19.342 20.750 23.867 19.875 3.257

38-IBWSN-1077

74.550 70.225 67.300 0.023 0.020 0.013 17.300 19.675 24.575 14.233 2.475

38-IBWSN-1059

68.300 63.100 60.900 0.021 0.018 0.017 15.500 17.800 18.250 14.122 4.300

26-ESWYT-124

70.750 62.450 59.050 0.042 0.039 0.012 16.200 19.575 19.225 19.500 1.525

ZAS-08 72.350 74.942 72.075 0.054 0.051 0.045 10.575 12.875 16.425 22.807 6.175

ZAS-34 71.250 67.450 66.450 0.039 0.036 0.020 19.892 21.825 23.425 16.735 2.105

ZAS-42 73.992 81.223 76.800 0.054 0.050 0.052 09.225 13.500 15.500 25.752 5.700

ZAS-67 71.950 77.680 72.400 0.047 0.080 0.023 16.525 20.025 21.800 16.777 2.875

ZAS-70 79.500 74.913 69.950 0.054 0.049 0.029 17.483 20.325 23.200 14.637 2.875

Ghaznavi-98

78.625 71.960 68.600 0.069 0.064 0.047 13.475 16.300 20.775 18.388 6.400

Tatara 88.525 79.330 74.250 0.079 0.073 0.068 11.217 14.475 17.250 25.940 7.450

RLWC; Relative leaf water content, NGPS; Number of grains per spike, YPP; Yield per plant

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