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Journal of Soil Salinity and Water QualityJournal of Soil Salinity and Water Quality (JSSWQ) serves as official organ of the Indian Society of Soil Salinity and

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ISSN 0976-0806

Journal of Soil Salinity and Water Quality

Volume 9 2017 Number 2

CONTENTS

1. N and P Release Pattern in Saline-sodic Soil Amended with Gypsum and Municipal … 145-155Solid Waste CompostParul Sundha, Nirmalendu Basak, AK Rai, RK Yadav, DK Sharma and PC Sharma

2. Quantitative Assessment of Soil Salinity Using Electromagnetic Induction Technique … 156-166and Geostatistical ApproachBhaskar Narjary, Pardeep Jangra, Ramesh Abhishek, Neeraj Kumar, R Raju, K Thimappa,RL Meena, Satyendra Kumar, Parveen Kumar, AR Chichmatalpure and SK Kamra

3. Physiological and Biochemical Characterization of Rice Varieties under Salt and … 167-177Drought StressesAshwani Kumar, Charu Lata, SL Krishnamurthy, Arvind Kumar, KRK Prasad and NeerajKulshreshtha

4. Land-use Influences Soil Properties of Sodic Land in Northwest India … 178-186Ashim Datta, Nirmalendu Basak, Anil R Chinchmalatpure, Rakesh Banyal and SK Chaudhari

5. Relative Efficiency of Amendments for Reclamation of Sodic Vertisols and their Effects … 187-193on Crop ProductionUR Khandkar, SC Tiwari, RK Sharma, SK Verma, RL Meena and MJ Kaledhonkar

6. Response of Isabgol (Plantago ovata) to Bioregulators and Varying Water Salinity Levels … 194-199Under Drip IrrigationDeepak Gupta, IJ Gulati, NS Yadav and AK Singh

7. Effect of Different Levels of Fertilizers and Biogas Slurry on Yield and Chemical … 200-204Composition of Wheat Grown under Sodic VertisolsMegha Vishwakarma, UR Khandkar and SC Tiwari

8. Effect of Fertigation on Nitrogen Use Efficiency and Productivity of Tomato Utilizing … 205-212Saline Water through Drip IrrigationNarender Kumar, RK Jhorar, Sanjay Kumar, Rajpaul Yadav, Ram Prakash and Amandeep Singh

9. Effect of Laser Land Leveling on Crop Yield and Water Production Efficiency of Paddy … 213-218(Oryza sativa) in Tungabhadra Project CommandRH Rajkumar, J Vishwanatha, SR Anand, AV Karegoudar, AT Dandekar and MJ Kaledhonkar

10. Direct Seeded Rice Followed by Zero Tillage Rapeseed Increase System Yield and … 219-225Profitability in Coastal Saline SoilsSukanta K. Sarangi, B Maji, UK Mandal, S Mandal and PC Sharma

11. Potassium and Sulfur Dynamics under Surface Drip Fertigated Onion Crop … 226-236Sanjay T Satpute and Man Singh

12. Integrated Farming System in Salt-affected Soils of Tamil Nadu for Sustainable … 237-240Income GenerationM Selvamurugan, M Baskar, P Balasubramaniam, P Pandiyarajan and MJ Kaledhonkar

13. Evaluation of Groundwater Quality for Irrigation in Gulha Block of Kaithal District … 241-248in HaryanaVijay Kant Singh, Ramprakash, Rajpaul , Sanjay Kumar, Kuldeep Singh and Satyavan

14. Characterization of Soils and Cropping Pattern of Coastal West Bengal - A Case … 249-256Study in Canning II BlockR Srinivasan, SK Singh, T Chattopadhyay, SK Gangopadhyay, DC Nayak and S Mukhopadhyay

15. Assessment of Soil Degradations in Coastal Ecosystem of Sundarbans, West Bengal- … 257-269A Case StudyR Srinivasan, SK Singh and DC Nayak

16. Quality of Irrigation Groundwater from Palghar and Dahanu Tehsils of Coastal Konkan … 270-274MV Apraj, KD Patil, MR Wahane and NH Khobragade

N and P Release Pattern in Saline-sodic Soil Amendedwith Gypsum and Municipal Solid Waste Compost

Parul Sundha*, Nirmalendu Basak, AK Rai, RK Yadav,DK Sharma and PC Sharma

ICAR-Central Soil Salinity Research Institute, Karnal-132 001, Haryana, India*Corresponding author E-mail : [email protected]

Abstract

Nitrogen and phosphorus are the major nutrients limiting crop production in saline-sodic soils. The reclamationand nutrient supplying potential of municipal solid waste compost (MSWC) from Karnal and Delhi was studiedin saline-sodic soil (with pH1:2 10.16; electrical conductivity (EC1:2) 3.09 dS m-1; exchangeable sodium percentage77.5) with conjunctive application of gypsum (25% recommended doses of mineral gypsum, GR25) and 10 Mgha-1 MSWC at 60% water holding capacity for three months. Soil showed alkaline reaction for the wholeincubation period. The combined application of GR25 and compost KC and DC are equally effective comparedwith GR50 on declining soil pH1:2. Amended soils upon incubation showed a decrement in aqueous extractableCa2+ while increase in K+ and HCO3

- and CO32- concentration in soil solution. During incubation, N and P were

initially immobilized and after reaching the maxima of immobilization, these entered in mineralization phase.Application of gypsum (GR50 and GR25) caused overall deficit of the N compared to control. Integration ofMSWC with gypsum resulted in increased N content in soil system. Both the composts showed similar valuesof N at different days of incubation. Gypsum caused decline in soil P. MSWC compensated for gypsum induceddeficit, and available P of Karnal (30.7 mg kg-1) and Delhi (29.3 mg kg-1) were at par with control (32.0 mgkg-1). Therefore, this study recommended that application of 10 Mg ha-1 municipal solid waste compost withgypsum GR25 can reduce soil pH and efficiently supply N and P compared to sole gypsum application.

Key words: Gypsum, Municipal solid waste compost, Nitrogen, Phosphorous, Saline-sodic soils

Introduction

Salt-affected soils limit crop production becauseof salinity stress and deficient supply of plantnutrients. The low availability of essential plantnutrients in these soils is because of scantyvegetative cover and low biological transformation(Chhabra, 1996; Kaur et al., 2008). Further, thehigh pH and exchangeable Na (ESP) inhibitnitrification and promote ammoniumvolatilization (Rao and Batra, 1983). Thisunfavorable soil pH also reduces symbiotic Nfixation and favours wasteful transformation ofapplied N (Bharadwaj and Abrol, 1978). Unlikethe nitrogen, Olsen’s extractable soil P is normallyenough in quantity in sodic soil (Chhabra, 1996).Ca-P is the most dominant P fraction in sodic orsaline-sodic soils (Meena et al., 2018). The Na2CO3

and NaHCO3 dissolute native calcium phosphateto release phosphate, is responsible for positiverelation between available PO4

3- and soil pH.

Among the categories of salt-affected soils, sodicand saline-sodic soils are reclaimed with gypsum(CSSRI, 2015). Applications of gypsum largelyimprove aeration, infiltration, soil structure andcurb the impedance effect of ESP and high pH.But, sole application of gypsum can createdisturbance on availability of soil P to plantbecause of insoluble Ca-P formation (Nayak etal., 2013). In such condition, integration oforganic amendments e.g. green manure, farm yardmanure have shown increase in reclamationefficiency and availability of nutrients for plantnutrition (Choudhary et al., 2007).

Rapid urbanization has led to produce nearly62 million tonnes of total solid waste yearly whichmay increase to 436 million tonnes each year by2050 for India (Planning Commission Report,2014). Safe disposal of these wastes has becomemajor challenge for the cities. Therefore,municipal solid waste compost (MSWC) has

Journal of Soil Salinity and Water Quality 9(2), 145-155, 2017

146 Sundha et al.

received priority as safe way of waste disposal andlow-cost choice for organic matter and nutrientsupplement to hungry soils. This can improve thephysico-chemical and biological properties of soilsat low cost (Meena et al., 2018; Rawat et al., 2013).Integrated use of gypsum and organics in sodicsoil can reduce the harmful impact of sodicity andimprove soil fertility for better crop growth (Bharadwajand Abrol, 1978; Tejada et al., 2006; Choudharyet al., 2007). However, limited information isavailable on N and P availability pattern in sodicsoils amended with gypsum and municipal solidwaste compost. Knowledge of how nutrientavailability is affected in gypsum and municipalsolid waste compost amended saline-sodic soilsis important in adopting apt management practicesto satisfy plants’ nutritional needs and improveyields. It has been hypothesized in this paper thatmunicipal solid waste compost (MSWC) withmineral gypsum has potentiality to maintain theN and P availability with offsetting sodicityhazards in sodic soil. Therefore, the objective ofthe present study was to capture the N and P

release pattern in saline-sodic soil amended withgypsum and municipal solid waste compost.

Materials and Methods

Soil sampling and compost collection

Bulk soil (0-20 cm soil layer) was collected fromSaraswati forest range (30°00′04.5′′ N; 76°25′27.3′′E), Kaithal, Haryana, India. The soil was saline-sodic in categories with clayey soil texture. Thephysico-chemical properties of the experimentalsoil are presented in Table 1. This soil was air-dried and crushed to pass through a 2mm sieveand was homogenized by thorough mixing andanalyzed for physico-chemical properties.Characteristics of the municipal solid wastecompost (MSWC) collected from two cities viz.,Karnal (KC) and Delhi (DC) are presented in(Table 2).

Soil incubation experiment

Processed soil was incubated in triplicate withrespective doses of the amendments viz., control

Table 1. Physico-chemical properties of experimental soil

Soil property Unit Value Reference

Sand % 59.3 Gee and Bauder, 2006Silt % 17.4Clay % 23.3pH1:2 - 10.71 Page et al., 1982EC1:2 dS m-1 3.09pHs - 10.16 USSL, 1954ECe dS m-1 12.15Organic C % 0.11 Walkley and Black, 1934KCl extractable N mg kg-1 317.0 Ebina et al., 1983Available P kg ha-1 37.5 Jackson, 1973Available K kg ha-1 174.7CaCO3 % 1.45 Allison and Moodie, 1965Cation Exchange Capacity (CEC) cmolc kg-1 27.2 Tucker, 1985Exchangeable Sodium Percentage (ESP) % 77.5Gypsum Requirement (GR) Mg ha-1 22.7 Schoonover, 1952

Table 2. Chemical composition of composts

Organic amendments pH1:5 EC1:5 Total Total Ash Total Total Total Total TotaldS m-1 organic C N Ca Mg Na K Cl

% g kg-1

Karnal compost (KC) 7.33a 12.0 5.52b 0.64 83.95 40.33a 47.80b 3.87 12.31a 37.87Delhi Compost (DC) 7.09b 11.6 6.89a 0.67 80.15 21.00b 65.10a 3.82 10.98b 42.13

[different lower case letters within columns are significantly different at p≤0.05 according to Tukeys Test for separation of means.]

N and P release in gypsum and municipal solid waste compost amended soil 147

without amendment, 25% recommended dose ofmineral gypsum (GR25); 50% recommended doseof mineral gypsum (GR50); GR25 + 10 Mg ha-1

of Karnal compost (GR25KC10) and GR25 + 10Mg ha-1 of Delhi compost (GR25DC10) at 60%water holding capacity for three months to studythe dynamics of nitrogen and phosphorus. Thethree core volumes of soil samples from entiredepth were taken out at each sampling from potsto maintain the homogeneity of the samples.

Soil analysis

The pH1:2 and EC1:2 of soil and amendments usedwere measured in a 1:2 soil/material-watersuspension with the help of pH meter andconductivity meter (Page et al., 1982). Standardmethods were applied for determination ofconcentration of Ca2+, Mg2+, Na+ and Cl- of soilsaturation extract (Jackson, 1973). Ca2+ and Mg2+

were estimated by atomic absorption spectro-photometer (Schwarzenbach et al., 1946). Na+ andK+ were measured with flame photometer(Jackson, 1973). Chloride (Cl-) was measured byargentometric (Mohr’s) titration as described byJackson (1973). Carbonate (CO3

2-) andbicarbonate (HCO3

-) were determined by methylred and phenolphthalein end point titration,respectively (Jackson, 1973). SO4

2- was measuredas described by Chesnin and Yien (1951) by UV-Vis spectrophotometer (Lab India Analytical UV3000+). For KCl extractable total N estimation, 5g soil sub-sample with 50 ml of 2M KCl wasshaked for one hour and filtered. The filtrate andK2S2O8 (oxidizing solution) in the ratio of 1:1 weredigested at 121°C and analyzed for total N (Ebinaet al., 1983). The product of oxidation was nitrateand it was measured spectrophotmetrically(Forster, 1995). The available P from each soil wasextracted using 2.5 g soil sub-sample with 50 ml0.01 N NaHCO3 solution on an orbital shaker atroom temperature (25°C). The suspensions werethen filtered with Whatman no. 42 and analyzedfor phosphorus colorimetrically using ascorbicacid reductant method (Jackson, 1973). dN anddP were computed subtracting the N and P contentof control from the treatments. All the results wereexpressed on oven dried (105°C) weight basis.Sodium adsorption ratio (SARe) is a mathematicalrelationship shown in following equation, the

concentration of sodium in relation to calciumand magnesium of saturation extract:

where [ ] represents the concentration of cationin cmol(p+)L-1

Statistical analysis

Statistical analysis was performed by the SASprogram. Tukey’s test was used to comparetreatment means. Simple regression equationswere also developed to evaluate the relationshipsamong the response variables.

Results and Discussion

Changes in pH1:2 and EC1:2 of incubated soil

In general, pattern of pH1:2 showed an alkalinereaction for the whole incubation period (10.09to 10.40) (Table 3). Soil pH1:2 showed decliningtrend in early 45 days of incubation, after that itgradually increased and all the treatments showedsignificantly greater values compared to the pHvalues of the early incubation period. The increasein pH is because of alkaline hydrolysis of Na-clay(ESP 77.5%) and release of CO3

2- and HCO3- of

Na+, which potentially promoted alkalinehydrolysis (Li and Keren, 2008; Basak et al.,2015a). Untreated control soil had overall greatervalues of pH1:2 (10.24) whereas, application ofGR25 and GR50 declined soil pH1:2 to 10.15 and10.06, respectively. Supplement of Ca throughgypsum helped exchange reaction between Na-clay and Ca and reduced alkaline hydrolysis.GR50 and combined application of GR25 andcompost (KC or DC) were equally effective inlowering pH1:2. Soil pHs was reduced significantlybecause of MSWC application, pHs values forGR25 + MSWC were at par with GR50 butsignificantly less compared to control. Source ofMSWC had no effect on lowering the soil pHs at30 days of incubation (DAI) (Table 4). At 90 DAI,contrast comparison showed significant loweringof the pHs because of MSWC applicationcompared to control, GR50 and GR25. pHs of DCtreated soil was significantly less compared to KC.The supply of Ca and Mg from gypsum/ compost

148 Sundha et al.

Table 3. Effect of gypsum and municipal solid waste compost on soil pH1:2 on incubation

Treatments/ 3rd 7th 13th 20th 30th 45th 60th 75th 90th Meandays

Control 10.25aB 10.20aBC 10.23aBC 10.11aBC 10.19aBC 10.06aC 10.08aBC 10.50aA 10.53aA 10.24P

GR25 10.11bBC 10.11bBC 10.16bB 10.05bCD 10.00aD 9.98bD 10.04abCD 10.45bA 10.45abA 10.15PQ

GR50 10.00cCD 10.02cBC 10.10cB 10.00cB 9.95aCD 9.91cD 9.98bCD 10.31dA 10.24dA 10.06Q

GR25KC10 10.05bcDE 10.08bD 10.15bcC 10.01cEF 9.98aF 9.96bF 10.00abEF 10.35cdB 10.42bcA 10.11Q

GR25DC10 10.04bcCD 10.09bC 10.17bB 10.03cbD 10.01aDE 9.97bE 10.01abDE 10.37cA 10.33cdA 10.11Q

Mean 10.09r 10.10r 10.16q 10.04s 10.03s 9.97t 10.02s 10.40p 10.39p

[GR25: 25% gypsum requirement; GR50: 25% gypsum requirement; GR25KC10: GR25 + Karnal compost @ 10 Mg ha-1; andGR25DC10: GR25 + Delhi compost @ 10 Mg ha-1; Values with different lower case letters (a–c) denote difference between eachtreatment for same incubation days; different upper case letters (A–F) denote difference between days of incubation for sametreatment; upper case superscript P- Q denotes difference in treatments throughout the incubation period; lower cases p- t denotedifference in each incubation period across treatments at p ≤ 0.05 by Tukey’s test]

Table 4. Contrast analysis of soil attributes at 30 and 90 days for different treatments

Treatments pHs ECe Ca2+ Mg2+ Na+ K+ CO32- HCO3

- Cl- SO42-

30 daysControl vs. MSWC 0.046 0.053 0.094 0.167 0.636 0.069 0.032 0.194 0.982 0.628GR50 vs. MSWC 0.207 0.428 0.326 0.428 0.684 0.453 0.345 0.509 0.558 0.719GR25 vs. MSWC 0.116 0.202 0.219 0.741 0.231 0.001 0.649 0.095 0.097 0.574GR25KC10 vs. GR25DC10 0.064 0.226 1.00 0.186 0.298 0.004 0.623 0.924 0.358 0.685

90 daysControl vs. MSWC < 0.0001 0.864 0.033 0.065 0.902 0.006 0.0004 0.053 0.964 0.161GR50 vs. MSWC < 0.0001 0.564 0.825 0.599 0.665 0.330 0.011 0.003 0.560 0.031GR25 vs. MSWC < 0.0004 0.427 0.417 0.851 0.325 0143 0.854 0.107 0.334 0.698GR25KC10 vs. GR25DC10 < 0.0092 0.625 0.634 0.745 0.794 0.458 0.529 0.743 0.699 0.427

Depictions of treatments same as in Table 3

and organic materials of compost favoredexchanged reaction (Chaganti et al., 2015).

The electrical conductivity (EC1:2) of soilshowed nearly stable values (2.94 to 2.32 dS m-1)up to 30th days of incubation (Table 5), after that,a gradual rise with incubation period. Gypsum

on reaction with alkali salts produced solublesulphates (Na2SO4) and hiked soil EC1:2 (Sundhaet al., 2017). In later incubation stage, control soilshowed significant increase in EC1:2, pointing outto dissolve soil minerals. An accompanyingincrease in the K+ and HCO3

- content in saturation

Table 5. Effect of gypsum and municipal solid waste compost on soil EC1:2 (dS m-1) on incubation

Treatments/ days 3rd 7th 13th 20th 30th 45th 60th 75th 90th Mean

Control 2.96aCD 2.77aCD 2.59bD 2.64abD 2.36aD 3.35aCD 3.88aBC 4.93aAB 5.50abA 3.44GR25 2.82aB 2.80aB 2.67abB 2.55bB 2.17aB 3.30aB 4.47aAB 6.00bA 6.37abA 3.68GR50 2.88aC 2.96aC 2.95aC 2.75abC 2.35aC 3.44aBC 5.06aAB 5.01bAB 5.40bA 3.64GR25KC10 3.01aDE 2.79aE 2.95aDE 2.99aDE 2.29aE 3.75aCD 4.26aC 5.20abB 7.43aA 3.85GR25DC10 3.03aB 2.79aB 2.85abB 2.82abB 2.46aB 2.97aB 4.21aA 5.31abA 5.18bA 3.51Mean 2.94t 2.82t 2.80t 2.75t 2.32u 3.36s 4.37r 5.29q 5.98p

[GR25: 25% gypsum requirement; GR50: 25% gypsum requirement; GR25KC10: GR25 + Karnal compost @ 10 Mg ha-1; andGR25DC10: GR25 + Delhi compost @ 10 Mg ha-1; Values with different lower-case letters (a–c) denote difference between eachtreatment for same incubation days; different upper case letters (A–F) denote difference between days of incubation for sametreatment; lower cases p- t denote difference in each incubation period across treatments at p ≤ 0.05 by Tukey’s test]


extract at 90 DAI also supports this observation(Fig. 1). The amended soil showed higher valuesof EC1:2 than control soil. Jalali and Ranjbar (2009)experienced similar results for the soil was greaterEC1:2 compared to control soil.

Ionic composition of aqueous saturation extract

Sodium was dominant cation followed by Mg2+,Ca2+, and K+ for both the incubation periods (30and 90 days) (Fig. 1). Mg2+/ Ca2+ were at par forinitial soil however concentration of both declinedwith increase of incubation. Decrease in Ca2+ wasmore compared to Mg2+ at 90 DAI. This decreasein divalent cations during incubation was mainlybecause of the exchange reaction betweenexchangeable Na and Ca of applied gypsum.Perceptible increase in the K+ was observed at 90DAI compared to 30 DAI. This may be becauseof release of K+ from the exchange complex, anddissolution of the feldspar, muscovite and otherK bearing minerals under alkaline conditions

(Crundwell, 2014). Among the anions, SO42-

remained dominant over Cl-, CO32- and HCO3

-

(Fig. 2). Exchange reaction in incubated soilpartially neutralized CO3

2- to HCO3-. While, SO4

2-

content increased in saturation extract of differenttreatments at 90 DAI. The exchange reactionfurther corroborated with increment inconcentration of Na and SO4

2- and decrement invalue of (CO3

2- + HCO3-) (Singh, 1998). Soil pHs

showed a good correlation with sodiumadsorption ratio (SARe) of saturation extract (R2=0.365) and soil pH1:2 (R2= 0.65) (Fig. 3). In contrastcomparison, MSWC application showedsignificant increase in Ca2+, K+ and HCO3

- contentof saturation extract at 90 DAI compared tocontrol. MSWC also showed greater values forCO3

2- and HCO3- compared to GR50 (Table 4).

Basak et al. (2015b) showed a good agreementbetween pH and SAReq (equilibrium solution)solution at various salinity levels in different salt-affected soils (Table 4).

Fig. 1. Cationic composition of soil saturation extract at 30 and 90 days of incubation

150 Sundha et al.

Fig. 2. Anionic composition of soil saturation extract at 30 and 90 days of incubation

Fig. 3. Relation between SARevs. pHs and pH1:2 vs. pHs

Changes in N of incubated soil

Nitrogen release in soil for different treatmentsup to 90 days of incubation is presented in Table6. Irrespective of treatments overall a decrease intotal N tended up to 30th day followed by an

increase up to 90th day of incubation. The Nrelease pattern showed a quadratic relation withdays of incubation with R2 varied with 0.62 to 0.83(Fig. 4). Incubation of air-dried soil at fieldcapacity under control condition favoured


microbial activity and consumed soil N bymicroflora for growth (Tejada et al., 2006).Therefore, an immobilization in soil N contentcontinued up to 30 days. After that, declining soilbiological activity reduced the N need formicroflora and released N upon lyses andconcomitantly maintained mineralization (Bradyand Weil, 2014). Comparatively higher amountof N was accumulated in soil treated with compost+ GR25 (p= 0.0001) compared to sole gypsum(GR25/50) or control soil (Fig. 5; Table 7).Municipal composts release surplus N upon

decomposition (Busby et al., 2007). Difference inN computed over the control (∆N) showed thatapplication of gypsum (GR50 and GR25) caused

Table 6. Soil N release (mg kg-1) at different days of interval


Control 317.8aA 185.0cB 67.7aD 95.3abCD 65.2aD 145.0abBC 116.5aCD 203.0aB 285.8bA 164.6Q

GR25 267.9aA 259.9aA 89.9aC 65.1bC 63.8aC 72.4bC 102.1 ac 193.9aB 288.9abA 156.0Q

GR50 240.6aBC 268.6abAB 105.6aD 80.4abD 92.6aD 136.8abD 97.2aD 201.0aC 309.6abA 170.2Q

GR25KC10 274.1aA 307.3abA 111.7aB 130.6aB 109.6aB 162.4aB 112.6aB 256.3aA 329.9aA 199.4P

GR25DC10 288.6aA 315.9aA 90.1aB 114.9abB 117.6aB 155.4aB 134.7aB 254.2aA 300.5abA 196.9P

Mean 277.8pq 267.3q 93.0t 97.3t 89.8t 134.4s 112.6st 221.7r 302.9p

[GR25: 25% gypsum requirement; GR50: 25% gypsum requirement; GR25KC10: GR25 + Karnal compost @ 10 Mg ha-1; andGR25DC10: GR25 + Delhi compost @ 10 Mg ha-1; Values with different lower case letters (a–c) denote difference between eachtreatment for same incubation days; different upper case letters (A–F) denote difference between days of incubation for sametreatment; upper case superscript P- Q denotes difference in treatments throughout the incubation period; lower cases p- t denotedifference in each incubation period across treatments at p ≤ 0.05 by Tukey’s test]

Fig. 4. N release as affected by amendments and days of incubation

Table 7. Contrast analysis of soil N and P at differenttreatments in throughout the incubation period

Treatments Soil N Soil P

Control vs. MSWC < 0.0001 0.0857GR50 vs. MSWC < 0.0001 0.0003GR25 vs. MSWC < 0.0001 0.0302KC vs. DC 0.7006 0.3186

152 Sundha et al.

Fig. 5. Amendments induced N release at different day of incubation compared to control soil

overall shortage of the N (-∆N) in incubated soilexcept initial 30 days. Integration of MSWC withgypsum resulted in increased N content in soilsystem and positive ∆N was observed throughoutthe incubation. Both the composts showed similarvalues of N at different days of incubation (Table7). The chemical composition for N (0.64 and0.67%) for experimental composts also showedthe similar values.

Changes in P of incubated soil

Release pattern of soil P varied with incubationperiod and imposed treatment. Control soilshowed greater values of soil P compared togypsum and gypsum + MSWC amended soil(Table 8). Control soil had greater alkalinehydrolysis and showed high soil P (Chhabra,1996). Application of gypsum helped exchangereaction and transformed the soluble P towardscomplex and less soluble calcium phosphate andtends P less available (Tiwari, 2012). Present study

also supports this observation, throughout theincubation period ∆P was negative for all thetreatments, NaHCO3 extractable P was lowest inGR50 followed by GR25 and GR25DC10 andGR25KC10 (Fig. 6). Release of P from theMSWC compensated to some extent the Pshortage in gypsum amended soil and ∆P was lessnegative compared to GR50 and GR25. Pavailability in different treatments also followedthe trend similar to N. Both the nutrients at firstimmobilized and after reaching the maxima ofimmobilization, it enters mineralization phase(Fig. 7). This is likely because of change inmicrobial flora under changing soil reaction andsoil solution composition (Table 1, Fig. 1 and 2).As MSWC supplied P, therefore, KC (30.7 mgkg-1) and DC (29.3 mg kg-1) showed nearly at parvalue of P compared to control (32.0 mg kg-1).Source of MSWC has no effect on the Pavailability (Table 7).

Table 8. Soil P release (mg kg-1) in different day of interval


Control 37.5aA 34.6aAB 27.8aAB 22.8aB 29.1aAB 31.6aAB 32.2aAB 38.0aA 34.2aAB 32.0P

GR25 34.5aA 30.3aAB 27.7aAB 16.8aB 24.2aAB 26.4aAB 21.9aAB 35.8aA 29.9aAB 27.5QP

GR50 32.7aA 30.5aA 26.8aA 18.0aA 21.7aA 26.0aA 24.0aA 26.6bA 25.1aA 25.7R

GR25KC10 35.2aA 35.3aA 31.0aAB 20.3aB 23.0aAB 31.5aAB 32.0aAB 34.5abA 33.2aA 30.7PQ

GR25DC10 36.8aA 34.4aAB 29.3aABC 19.4aD 23.1aCD 31.8aAB 27.5aBC 33.6abAB 28.2aBC 29.3PQR

Mean 35.3p 33.0pq 28.5r 19.5t 24.3s 29.46r 27.5rs 33.7p 30.1qr

[GR25: 25% gypsum requirement; GR50: 25% gypsum requirement; GR25KC10: GR25 + Karnal compost @ 10 Mg ha-1; andGR25DC10: GR25 + Delhi compost @ 10 Mg ha-1; Values with different lower case letters (a–c) denote difference between eachtreatment for same incubation days; different upper case letters (A–F) denote difference between days of incubation for sametreatment; upper case superscript P- R denotes difference in treatments throughout the incubation period; lower cases p- t denotedifference in each incubation period across treatments at p ≤ 0.05 by Tukey’s test]


Fig. 6. Amendments induced P release at different day of incubation compared to control soil

Fig. 7. P release as affected by amendments and days of incubation

154 Sundha et al.

Conclusion

Soil showed alkaline pH on incubation butintegrated application of municipal solid wastecompost (MSWC @ 10 Mg ha-1) and 25% ofgypsum requirement declined soil pH. Amendedsoils upon incubation showed a decrement inaqueous extractable Ca2+ compared to initial soil.Strong alkaline condition during incubationfavoured increase in K+ and HCO3

- and CO32-

concentration in soil solution. Gypsumapplication in sodic soil reduces N and Pavailability, MSWC application with gypsum cancompensate for N and P shortage and reduces thedemand of gypsum for sodic soil reclamation.

Acknowledgements

The senior author acknowledges the ICAR-Central Soil Salinity Research Institute, Karnal,Haryana India, for providing financial andlogistics support during her research work.Authors are thankful to the Sh. Dinesh Meena,Sh. Raj Kumar and Dr. Naresh K. Arora fortechnical support in analytical works.

References

Allison LE and Moodie CD (1965) Carbonate. In: Black CA(ed) Methods of Soil Analysis. Part 2. Chemical andMicrobiological Properties. American Society ofAgronomy, Madison, pp 1379-1396.

Basak N, Chaudhari SK and Sharma DK (2015a) Impact ofvarying Ca: Mg waters on ionic balance, dispersion, andclay flocculation of salt affected soils. Communicationsin Soil Science Plant Analysis 46: 827-844. doi:10.1080/00103624.2014.1003937.

Basak N, Chaudhari SK and Sharma DK (2015b) Influenceof water quality on exchange phase-solution phasebehavior of texturally different salt-affected soils. Journalof the Indian Society of Soil Science 63(4): 365-372. DOI:10.5958/0974-0228.2015.00048.1

Bharadwaj KKR and Abrol IP (1978) Nitrogen managementin alkali soils. In: Sen SP, Abrol IP and Sinha SK (eds)Nitrogen Assimilation and Crop Productivity. AssociatedPublishing Company, New Delhi, pp 83–86.

Brady NC and Weil RR (2014) Nitrogen and sulfur economyof soils. In: The Nature and Properties of Soils. PearEducation in South Asia, pp 615-670.

Busby RR, Torbert HA and Gebhart DL (2007) Carbon andnitrogen mineralization of non-composted andcomposted municipal solid waste in sandy soils. SoilBiology & Biochemistry 39: 1277–1283. doi:10.1016/j.soilbio.2006.12.003.

Chaganti VN, Crohn DM and S¡imuÚnek J (2015) Leachingand reclamation of a biochar and compost amendedsaline-sodic soil with moderate SAR reclaimed water.Agricultural Water Management 158: 255–265. http://dx.doi.org/10.1016/j.agwat.2015.05.016.

Chesnin L and Yien CH (1951) Turbidimetric determinationof available sulphates. Soil Science Society of AmericaProceedings 15: 149-151.

Chhabra R (1996) Soil Salinity and Water Quality. Oxford &IBH Publications, New Delhi. pp 284.

Choudhary OP, Kaur G and Benb DK (2007) Influence oflong term sodic water irrigation, gypsum, and organicamendments on soil properties and nitrogenmineralization kinetics under rice–wheat system.Communications in Soil Science and Plant Analysis 38:19-20, 2717-2731. DOI: 10.1080/00103620701662968.

Crundwell FK (2014) The mechanism of dissolution ofminerals in acidic and alkaline solutions: Part IIApplication of a new theory to silicates, aluminosilicatesand quartz. Hydrometallurgy 149: 265–275.

CSSRI (2015) Vision 2050. Central Soil Salinity ResearchInstitute (Indian Council of Agricultural Research),Karnal -132 001, India p 31.

Ebina J, Tsutsui T and Shirai T (1983) Simultaneousdetermination of total nitrogen and total phosphorus inwater using peroxodisulfate oxidation. Water Research17: 1721-1726

Forster JC (1995) Soil nitrogen. In: Alef K and Nannipieri,P (eds) Methods in Applied Soil Microbiology andBiochemistry. Academic Press, pp 576.

Gee GW and Bauder JW (2006) Particle-size analysis. In:Klute A (ed) Methods of Soil Analysis. Part 1. 2nd edsAgronomy Monogram. 9. ASA and SSSA, Madison,WI. pp 383-409.

Jackson ML (1973) Soil Chemical Analysis. Prentice Hall India:New Delhi. pp. 498.

Jalali M and Ranjbar F (2009) Effects of sodic water on soilsodicity and nutrient leaching in poultry and sheepmanure amended soils. Geoderma 153 (1–2): 194–204.doi:10.1016/j.geoderma.2009.08.004.

Kaur J, Choudhary OP and Bijay-Singh (2008) Microbialbiomass carbon and some soil properties as influencedby long-term sodic-water irrigation, gypsum, and organicamendments. Australian Journal of Soil Research 46: 141-151. https://doi.org/10.1071/SR07108.

Meena MD, Narjary B, Sheoran P, Jat HS, Joshi PK,Chinchmalatpure AR, Yadav G, Yadav RK and MeenaMK (2018) Changes of phosphorus fractions in salinesoil amended with municipal solid waste compost andmineral fertilizers in a mustard-pearl millet croppingsystem. Catena 160: 32-40. doi.org/10.1016/j.catena.2017.09.002.


Nayak AK, Mishra VK, Sharma DK, Jha SK, Singh CS,Shahabuddin M and Shahid M. (2013) Efficiency ofphosphogypsum and mined gypsum in reclamation andproductivity of rice–wheat cropping system in sodic soil.Communications in Soil Science and Plant Analysis 44(5):909-921, DOI: 10.1080/00103624.2012.747601.

Page AL, Miller RH and Keeney DR (eds) (1982) Methods ofSoil Analysis, Part-2, Second Edition, Soil Science Societyof America, Madison, Wisconsin, USA.

Planning Commission Report (2014) Reports of the taskforce on waste to energy (Vol. I) (in the context ofIntegrated MSW management). Retrieved from http://planningcommission.nic. in/repor ts/genrep/rep_wte1205.pdf

Rao DLN and Batra L (1983) Ammonia volatilization fromapplied nitrogen in alkali soils. Plant and Soil 70(2): 219–228.

Rawat M, Ramanathan AL and Kuriakose T (2013)Characterization of municipal solid waste compost(MSWC) from selected Indian cities-a case study for itssustainable utilization. Journal of Environmental Protection4: 163-171.

Schoonover WR (1952) Examination of Soils for Alkali.University of California, Extension Service, Berkeley,California.

Schwarzenbach G, Biedermann W. and Bangerter F. (1946)Meue einfache Titrimethoden zur Bestimmung derWesserharte. Helvetica Chimica Acta 29: 811–18.doi:10.1002/hlca.19460290406.

Singh NT (1998) Reclamation and management of alkalisoils. In: Tyagi NK and Minhas PS (eds) Agricultural

Salinity Management in India. Central Soil SalinityResearch Institute, Karnal, pp 261-278.

Sundha P, Rai, AK, Basak N, Yadav RK and Sharma DK.(2016) Potentiality of municipal solid waste compostson reclamation of saline-sodic soil under the influenceof water sodicity. Extended Summaries Vol. 2: 4th

International Agronomy Congress, Nov. 22–26, 2016,New Delhi, India.

Tejada M, Garcia C, Gonzalez JL and Hernandez MT (2006)Use of organic amendment as a strategy for saline soilremediation: Influence on the physical, chemical andbiological properties of soil. Soil Biology & Biochemistry38: 1413–1421. doi:10.1016/j.soilbio.2005.10.017.

Tiwari KN (2012) Phosphorous. In: Goswami NN, RattanRK, Dev G, Narayanasamy G, Das DK, Sanyal SK, PalDK and Rao DLN (eds) Fundamental of Soil Science.Indian Society of Soil Science, New Delhi- 110 012, pp413-429.

Tucker BM (1985) The partitioning of exchangeablemagnesium, calcium, and sodium in relation to theireffects on the dispersion of Australian clay subsoils.Australian Journal of Soil Research 23: 405–416.doi:10.1071/SR9850405.

USSL (1954) In: Richards LA (ed), Diagnosis and Improvementof Saline and Alkali Soils. USDA Handbook, Washington,DC pp 60.

Walkley AJ and Black IA (1934) An examination of theDegtjareff method for determining soil organic matterand a proposed modification of the chromic acidtitration method. Soil Science 37: 29-38.

Received in January 2017; Accepted in April 2017

Quantitative Assessment of Soil Salinity Using ElectromagneticInduction Technique and Geostatistical Approach

Bhaskar Narjary1*, Pardeep Jangra1, Ramesh Abhishek1, Neeraj Kumar1, R Raju1,K Thimappa1, RL Meena1, Satyendra Kumar1, Parveen Kumar1,

AR Chichmatalpure2 and SK Kamra1

1ICAR-Central Soil Salinity Research Institute, Karnal-132001, Haryana, India2ICAR-Central Soil Salinity Research Institute, Regional Research Station, Baruch, Gujarat, India

*Corresponding author Email: [email protected]

Abstract

Assessment and monitoring of soil salinity is prerequisite for proper and timely decisions on reclamation andmanagement of saline soil. Electromagnetic induction (EMI) method could be a cost effective and rapid methodfor assessment of soil salinity at large scale. EM-38, an instrument works on electromagnetic induction methods,was used for assessing spatial variation of soil salinity. Survey was carried out in vertical (EMV) and horizontal(EMH) modes at 200 m × 200 m grid spacing over 48 ha area of subsurface drainage site at village Mokhrakherilocated in Rohtak district in Haryana, India. Based on the survey readings of high, moderate and low apparentconductivity, soil samples were collected from 8 sampling location points in field at 15 cm depth increment upto 90 cm depth for calibrating EM-38 observations. The soil samples were analyzed for soil salinity (ECe),cations (Ca2+, Mg2+ and Na+), anions (CO3

2-, HCO3- and Cl-) and SAR using standard procedures. Sodium

(Na+) and chloride (Cl-) ions were strongly correlated with apparent conductivity (EMV and EMH) measured byEM -38 as well as soil salinity (ECe). Therefore, Na+ and Cl- ions were mainly responsible for observed salinityin the field. Multiple regression analysis model based apparent conductivity (EMV and EMH) strongly predictedsoil salinity (ECe). Quantitative evaluation of soil salinity for 0-90 cm profile indicated that more than 91% areaof the field had salinity levels (ECe) above 4 dS m-1. It has been concluded that EM instrument is a reliable andrapid method for characterizing soil salinity at large scale for employing proper and precise reclamation measuresfor its effective utilization.

Key words: Electromagnetic induction (EMI) method, EM-38, Soil salinity, Ordinary kriging

Introduction

Salt-affected soils are the major environmentalproblem of arid and semi-arid regions. In India,nearly 6.72 million ha area is occupied by salt-affected soils out of which saline soils haveoccupied 2.96 million ha and of which 1.75million ha are under inland salinity and 1.2 millionha coastal salinity (Mandal et al., 2009). Theserepresent a serious threat to our ability to increasefood production to meet expanding needs. Toprevent further soil degradation, soil salinitymonitoring is required for proper and timelydecisions on reclamation and salinitymanagement. However, conventional soilsampling and laboratory analysis is timeconsuming (Huang et al., 2015) and expensiveowing to the cost associated with measuring the

electrical conductivity of a saturated soil pasteextract (ECe, dS m-1). During the past 30 years,digital mapping methods have been used to assistconventional soil mapping, and electromagneticinduction (EMI) has been widely used tocharacterize the spatial distribution of soil salinity(ECe) (Narjary et al., 2014; Doolittle and Brevik,2014). In India estimation of soil salinity usingelectromagnetic approach mostly used insubsurface drainage projects in black soil ofBheemarayanagudi, Karnatka (Kuligod et al.,2000), Bapatla, A.P. (Prasad et al., 2000), Rajad,Kota (Sharma et al., 1997), alluvial soil of Indo-Gangetic region (Banerjee et al., 1998). These cost-effective, non-invasive EMI techniques are wellsuited to assess the temporal and spatial variabilityof soil properties such as salinity (Lesch et al.,1992; Johnston et al., 1997; Rhoades et al., 1999;


Electromagnetic and geostatistical techniques for soil salinity assessment 157

Triantafilis et al., 2000; Wittler et al., 2006;Urdanoz and Aragüés, 2012), water content(Kachanoski et al., 1988; Brevik et al., 2006), soiltexture and depth-to-clay mapping (Doolittle et al.,1994; Saey et al., 2009), and in applications toprecision agriculture (Sudduth et al., 2001; Corwinand Lesch, 2003). Estimations of soil salinity fromEMI measurements are more suitable in areaswhere soil salinity is the major dominant soilfactor, and EMI response can be directly relatedto changes in the salinity (Friedman, 2005). Hence,EMI instruments are feasible tools for theappraisal of soil salinity at the farm level ifproperly calibrated to provide low uncertainty inthe predictive equations.

Mapping of soil salinity by classical statisticalmethod is not satisfactory as it does not includeinfluence of neighboring sampling points.Geostatistical spatial model which can take careof influence of neighboring sample locations havebeen introduced as a management and decisiontool for assessment of spatial variation in soilsalinity (Mondal, 2012; Huang et al., 2016).

The objective of this work is to quantify soilsalinity through EMI and development of soilsalinity maps from EMI surveys by geostatisticaltechniques.

Material and Methods

Experimental site

The present study was carried out in subsurfacedrainage area of village Mokhrakheri located inthe Meham block of Rohtak district in Haryana.The district Rohtak is in an alluvial plain of Indo-Gangetic basin in the central part of Haryana.Rohtak district of Haryana lies between 28°40′ to29°05′ north latitudes and 76°13′ to 76051′ eastlongitudes. The district area falls in Yamuna sub-basin of Ganga basin, and is mainly drained bythe artificial drain No. 8 flowing from north tosouth. Jawahar Lal Nehru feeder and Bhalaut sub-branch are main canals of the district. The climateof Rohtak district can be classified as semi-arid,mild and dry winter and hot summer. Meanmaximum temperature is 40.5ºC (May-June)whereas mean minimum temperature is 7ºC(January). The normal annual rainfall in Rohtak

district is about 592 mm. The south west monsoonsets in the last week of June and withdrawstowards the end of September and contributesabout 84% of the annual rainfall. July and Augustare the wettest months. The district area isoccupied by Indo-Gangetic alluvium that isphysiographically a flat terrain. The generalelevation in the district varies between 215 m to222 m above MSL.

The study field is located 22 km from Rohtakdistrict (Fig. 1). The soils of the study site aresandy loam and loamy sand texture. The depthof water level in Mokrakheri is less than 1.2 to2.5 m below ground level during pre-monsoonperiod, and less than 1m to 1.5 m during monsoonperiod. The ground water quality of the area issaline in nature. A thick layer of limestone(CaCO3) is present at about 1.5 m below the soilsurface in most of the study area. The site hadbeen lying barren for nearly two decades due tosalinization owing to the presence of a shallowperched water table, particularly during the wetmonsoon months (i.e. July to mid-September).

EMI data collection

In this study, an EM38 survey was conducted atthe village Mokrakheri, Rohtak in the summermonths of 2012. Manual apparent conductivity(EMV and EMH) readings were taken with aGeonics EM38 sensor (Geonics Inc., Mississauga,ON, Canada). The Geonics EM38 has twocoplanar transmitter and receiver coils which are1m apart. In the vertical mode of orientation(EMV), the instrument provides a deeperpenetration depth of measurement i.e. effectiveexploration depths of 1.5m than in the horizontalmode (EMH) of 0.75m (McNeill, 1990). In thisstudy, in each location horizontal (EMH) andvertical (EMV) mode observations were recorded.A total of 20 locations (Fig. 1) were visited andalong transects spaced 100 m apart.

Soil sampling and laboratory analysis

To facilitate calibration between apparentconductivity (EMV and EMH) and the various soilproperties, soil samples were collected at 8 selectedEM-38 measurement sites. At each of the 8 sitessoil samples up to a depth of 0.90 m were collected

158 Narjary et al.

and at the following depth increments: 0 – 0.15,0.15 – 0.30, 0.30 – 0.60 and 0.60 – 0.90 m. Theselection was based on the following range ofobserved apparent conductivity readings (EMH

and EMV) values; low (< 10 dS m-1), intermediate-low (10-20 dS m-1), intermediate (20-35 dS m-1),intermediate-high (35-50 dS m-1) and high (>50dS m-1). Soil samples were air dried and groundedto pass through a 2 mm sieve and analyzed forthe electrical conductivity of saturated soil pasteextract (ECe-dS m-1), exchangeable cations (Ca2+,Mg2+ and Na+) and anions (CO3

2-, HCO3-, Cl-)

using a standard procedure (Bhargava, 2003).Sodium adsorption ratio (SAR) was determinedfrom estimated cations as per the followingrelationship:

… (1)

Data analysis

Descriptive statistical analysis of the apparentelectrical conductivity and soil chemical propertieswas performed using data analysis module ofMicrosoft Excel 2013. Pearson correlation analysisamong apparent conductivities (EMV and EMH)and soil physico-chemical properties for averagesoil profile was done to estimate dominant cation

and anions responsible for soil salinity (ECe).Based on vertical (EMV) and horizontal (EMH)mode of apparent conductivity reading asindependent variables and soil salinity (ECe),dominant cation (Na+ and Ca2+) and anion (Cl)as dependent variables linear prediction modelswere developed through multiple regressionanalysis. Based on coefficient of determinationbetween dependent variables under study with theapparent conductivity, statistical significance ofpredictive model was tested. Statistical analysiswas done using Excel and SAS package.

Geo-statistical analysis

Geo-statistical approach was used to characterizethe variance structure, determination of spatialdistribution, and trend changes of soil salinity.Ordinary kriging (OK) used for determiningspatial dependence soil salinity (Yao and Yang,2010; Gao et al., 2015). The OK method uses asemi-variogram to quantify the spatial dependencebetween neighboring observations

…(2)

Where,

γ (h): The estimated or “experimental” semi-variance value for all pairs at a lag distance h

Fig. 1. EM 38 survey location, Mokrakheri, Rohtak, Haryana, India (Black line are Survey at 100 m × 100 m grid), dotted pointsrepresents sample collection points


z (xi): soil salinity at point i

z (xi+h): soil salinity at other points separated fromxi by a discrete distance h

xi: The geo-referenced positions where z (xi) valueswere measured

n: The number of pairs of observations separatedby the distance h.

Four types of semi-variogram models(Circular, Spherical, Exponential, and Gaussian)were tested using geo-statistical module in Arc-GIS 9.3. For the selection of the best model,predictive performance of the fitted models waschecked based on cross validation tests. The valuesof Mean Standardized Error (MSE), Root MeanSquare Error (RMSE), Average Standard Error(ASE) and Root Mean Square Standardized Error(RMSSE) were estimated to ascertain theperformance of the fitting models (Mahmoodifardet al., 2014). Mean standardized error should beclose to zero if the prediction standard errors arevalid. If RMSE is close to ASE, prediction errorswere correctly assessed. If RMSE is smaller thanASE, then variability of predictions isoverestimated; conversely, if RMSE is greater thanASE, then variability of predictions isunderestimated. The same could be deduced fromthe RMSSE statistic. It should be close to one. IfRMSSE is greater than one, the variability of thepredictions is underestimated; likewise, if it is lessthan one, the variability is overestimated (Gorai

et al., 2015). Various errors are defined by theequation (5-8) given below

…(3)

…(4)

…(5)

…(6)

Where, Z (xi) and Z^ (xi) are observed and predictedvalues of the variable at location xi, and σ2 is thevariance of the predicted variables at xi, and n isthe number of sampling locations.

The parameters of the geostatistical model i.e.,nugget and sill were analyzed for their spatialdependence.


The descriptive statistics were analyzed forapparent conductivity of surveyed EM 38 readingsin vertical (EMv) and horizontal (EMH) mode,profile parameter of soil salinity (ECe), dominantcations (Ca2+, Mg2+, Na+) and anions (CO3

2-,HCO3

-, Cl-) responsible for soil salinity.Basic statistical characteristics are presented inTable 1.

Table 1. Descriptive statistics of EM38 in horizontal (EMH) and vertical (EMV) (dS m-1), Electrical conductivity of soil saturationextract, calcium and magnesium, sodium, carbonate and bicarbonate and chlorine concentration in saturation extract

Parameters n Mean SD Minimum Maximum Skewness Kurtosis

ECa (Survey)EMH 20 62.1 31.3 14 100 -0.6 -1.2EMV 20 47.1 21.6 12 80 -0.3 -1.3ECa (Calibration)EMH 8 66.3 29.9 14 100 -0.9 -0.1EMV 8 51.7 21.2 18 80 -0.3 -0.8

Soil properties in 0-90 cm soil depthECe (dS m-1) 8 24.6 14.3 2.5 43.6 -0.03 -1.0Na+ (meq l-1) 8 522.5 425.6 13.2 1129.2 0.5 -1.4Cl- (meq l-1) 8 247.3 155.2 15.6 434.4 -0.1 -1.6SAR (mmol l–1/2) 8 64.9 44.8 4.4 127.4 0.2 -1.2Ca2++Mg2+ (meq l-1) 8 105.8 52.9 17.6 158.9 -0.5 -1.1CO3

2- (meq l-1) 8 0.2 0.5 0.0 1.3 2.2 5.2

HCO3(meq l-1) 8 1.9 0.4 1.3 2.5 0.04 0.7

160 Narjary et al.

The EMV readings across the study arearanged from 12 to 80 dS m-1 while EMH readingranges from 14 to 100 dS m-1. Higher range ofEMH reading in some pockets of the study arearepresenting enrichment of soil salinity in thesurface layer and the stronger response of EMH

for the upper 60 cm soil layer. Frequencydistribution of apparent conductivity datasetshowed that EMV and EMH were normallydistributed and symmetric with well-behaved tails(Fig. 2), therefore, no transformation was requiredfor further analysis of the data.

Between the two variables, EMH data wasmore skewed (-0.6) (skewness is a measure ofsymmetry) and lower level of kurtosis (-1.2)(kurtosis is a measure of whether the data arepeaked or flat relative to a normal distribution)than EMV, representing greater variability in soilsalinity in upper soil profile. EMV and EMH

readings both exhibited high standard deviation(31.3 and 21.6) due to larger variation in soil

salinity across the study area. Salt concentrationin the saturation extract revealed dominance ofsodium (522.5 meq L-1) than calcium andmagnesium (105.8 meq L-1) and among the anionschloride was the dominant anion (247.3 meq L-1)in the 0-90 cm soil profile. Throughout the soilprofile mean carbonate (CO3

2-) and bicarbonate(HCO3) ion concentration was 0.2 and 1.9 meqL-1, respectively. Mean SAR value in the surveysite was 64.9 mmol L–1/2 which is several timeshigher than the safe limit (< 15 mmol L–1/2).

Relationship of apparent electrical conductivities(EMV and EMH) and salt concentration

Relationship of apparent electrical conductivities(EMV and EMH) with soil salinity (ECe) andsoluble ions was established through Pearsoncorrelation analysis. Soil saturation extractelectrical conductivity (ECe) showed a significantpositive correlation of 0.83 and 0.86 with apparentconductivity in vertical (EMV) and horizontal(EMH) modes, respectively (Table 2).

Fig. 2. Signal histogram EM- 38 reading

Table 2. Pearson correlation analysis among apparent conductivities (EMV and EMH) and soil properties for average soil profile(0-90 cm)

ECe EMV EMH Na Ca2++Mg2+ Cl– CO32– HCO3

– SAR

ECe 1.00EMV 0.83 1.00EMH 0.86 0.85 1.00Na+ 0.96 0.73 0.85 1.00Ca2++Mg2+ 0.96 0.80 0.75 0.88 1.00Cl– 0.99 0.79 0.82 0.96 0.98 1.00CO3

2- -0.61 -0.69 -0.68 -0.46 -0.63 -0.55 1.00HCO3

– -0.22 -0.08 -0.30 -0.17 -0.34 -0.29 0.46 1.00SAR 0.95 0.75 0.91 0.99 0.85 0.93 -0.51 -0.23 1.00

Values in bold are different from 0 with a significance level alpha=0.05 (Units as in Table 1)


High positive correlation of more than 0.7 ofboth EMV and EMH with Na and Cl ions indicatedthat sodium chloride (NaCl) was the majorconstituent responsible for soil salinity (ECe).Calcium and magnesium were the majordominant cations present in the soil after sodium,showed a positive correlation of 0.8 and 0.75 withEMV and EMH, respectively. Among the anionscarbonate was negatively correlated with apparentconductivity. In the soil properties, soil salinity(ECe) was correlated strongly with sodium (r =0.96), calcium + magnesium (0.96) and chloride(r = 0.99). ECe, on the other hand, was moderatelynegatively correlated with carbonate (r = 0.68).In the study area, SAR had strongly positivecorrelation of 0.75, 0.91 and 0.95 with EMV, EMH

and ECe, respectively.

Presence of higher amount of sodium thancalcium and magnesium in the soil may pose ionictoxicity to the plant. High evaporative demand andshallow saline ground water conditions in manyarid and semi-arid regions lead to rise of solublesalts like NaCl to within the root zone resultingin higher Na concentration than Ca and Mg andconsequently enhancement of soil salinity.

Estimation of soil salinity (ECe), from apparentelectrical conductivities (EMV and EMH)observations

In the present study, the multiple regressionanalysis was performed for strongly correlated soilsalinity (ECe), dominant cations (sodium andcalcium + magnesium) and anion (chloride) asthe dependent variable and apparent conductivityin vertical (EMV) and horiozontal (EMH) readingas independent variables by using SPSS (Table 3).

Significant positive coefficient ofdetermination 0.77 was estimated for predictionof soil salinity (ECe) from apparent electrical

conductivity (EMV and EMH). Soluble sodium(Na) and calcium + magnesium (Ca2++Mg2+)showed a positive and significant coefficient ofdetermination 0.73 and 0.66, respectively withapparent electrical conductivities (EMV and EMH)(Table3). Chloride (Cl–) was the main anioncontributing to soil salinity and significant positivecoefficient of determination 0.7 estimated forprediction of chloride content from apparentconductivity readings (EMV and EMH). Similarapproaches have been reported for estimation ofsoil salinity from electromagnetic inductionmethod (Corwin and Rhoades, 1982, 1984;Rhoades et al., 1990; Slavich, 1990; Slavich andPetterson, 1990; Hendrickx et al., 1992; McKenzieet al., 1997; Lesch et al., 1998; Triantafilis et al.,2000).

Semi-variogram analysis

Developed multiple regression model equationswere utilized for obtaining estimates of soil salinity(ECe), sodium (Na+), Calcium+Magnesium(Ca2++Mg2+) and Chloride (Cl–) ions at non-sampled points and ordinary kriging (OK)interpolation method was employed for generatingbulk average (0-0.90 m) spatial map of soil salinity(ECe), Na+, Ca2++Mg2+ and Cl– ions, responsiblefor salinity in that area.

The experimental semivariogram c (h) whichmeasures the spatial autocorrelation between datapairs as a function of the displacement betweenthe pairs was calculated and the scatter plot of c(h) vs. h (lag distance) was generated for differentmodels and the model with the best fitting andthe smallest nugget value was selected (Goovaerts,2001). In this study, spherical was found the bestfitted semi-variogram model for all the variables.The fitted Semi-variogram models of soil salinity(ECe), Na, Ca2++Mg2+ and Cl– are shown in Fig(3a -3d), and their parameters summarized inTable 4. The semi-variogram parameters werecross validated by leaving one sample out andpredicting for that sample location based on restof the samples. The cross validation results ofordinary krigged map of ECe, Na+, Ca2++Mg2+

and Cl–, presented in Table 4, showed acceptableaccuracy with MSE close to zero, ASE closer toRMSE and RMSSE close to one. It indicates thatspatial prediction using semi-variogram

Table 3. Multiple linear regressions for estimating saturatedpaste electrical conductivity (ECe), dominant cations(Na+ and Ca2++Mg2+) and anions (Cl–) fromelectromagnetic induction (EMI) readings in bulkaverage (0-90 cm) soil profile

ECe = -5.41+ 0.24 ECV + 0.26 ECH (R2 = 0.77) (p = 0.025)Na+ = -287.3 + 0.4 EC V + 11.9 ECH (R2 =0.73) (p = 0.038)Ca2++Mg2+ = 0.9 + 1.5 ECV + 0.4 ECH (R2 = 0.66) (p = 0.07)Cl– = -63.9 + 2.7 ECV + 2.6 ECH (R2 =0.7) (p =0.049)

162 Narjary et al.

Fig 3a. Semivariogram of bulk average (0-90) cm layer soilsalinity (ECe in dS m-1)

Fig 3b. Semivariogram of bulk average (0-90) cm layer Na+1

(meq l-1) concentration

Fig 3c. Semivariogram of bulk average (0-90) cm layer Ca+Mg(meq l-1) concentration

Fig 3d. Semivariogram of bulk average (0-90) cm layer Cl (meql-1) concentration

Table 4. Semi-variogram models, parameter and cross validation for ordinary krigging of soil salinity (ECe), Na, Ca+Mg and Clion, at root zone soil profile (0-90 cm)

Variables Model Nuggets(C0) Sill (C0+C) MSE ASE RMSE RMSSE

ECe Spherical 0 206.6 0.02 8.8 6.3 0.73Na+ Spherical 0 144777 0.02 232.1 156.3 0.67Ca2++Mg2+ Spherical 0 2435.8 0.02 30.83 25.62 0.87Cl– Spherical 0 22654.6 0.02 92.58 66.6 0.73

parameters is better than assuming mean ofobserved value as the property value for anyunsampled location. This also shows that semi-variogram parameters obtained from fitting ofexperimental semi-variogram values were fairlyreasonable to describe the spatial variation. Strongspatial dependence of soil salinity in the study areamight be attributed to spatial homogeneity ofstructural factor such as parent material,topography, ground water salinity and water tabledepth. Strong spatial dependence of soil salinityhas been reported by many researchers (Yao andYang, 2010; Gao et al., 2015).

Categorization and spatial distribution map of soilsalinity (ECe), Na+, Ca2++Mg2+ and Cl–

Spatial distribution maps of soil salinity, Na+,Cl– and SAR for 0-90 cm soil profile are presentedin Fig. 4a to 4d. Soil salinity and other 3 variablesexhibited strip patterns with well-defined andfragmented patches, indicating strong spatialvariability. Soil salinity (ECe) is characterizedbased on the soil salinity classification of Abrol etal. (1988). In quantitative terms, 4% of the fieldhad salinity (ECe) of less than 4 dS m-1, 6%between 4 to 8 dS m-1, 12% between 8-16 dS m-1,78% more than 16 dS m-1 (Table 5).


Fig. 4a. Bulk average (0-90 cm) soil salinity (ECe) map ofMokrakheri

Fig. 4b. Bulk average (0-90 cm) Na+ map of Mokrakheri

Fig. 4c. Bulk average (0-90 cm) Ca+Mg map of Mokrakheri

Fig. 4d. Bulk average (0-90 cm) Cl map of Mokrakheri

Most of the saline area found in south westcorner of the land, which is a depression area andsalt accumulated. NaCl was the main saltcontributing to soil salinity, 91% area having Na+

concentration more than 100 meq l-1; whereas 87%area having Cl- concentration more than 100 meql-1. Presence of excessive amount of monovalentNa+ than divalent Ca2+ or Mg2+ cations wasresponsible for high salinity in the area. Meanprofile (0- 90cm) Ca2++Mg2+ maps indicate that67% area had Ca2++Mg2+ levels higher than 100meq l-1. Categorization of the study area accordingto its salinity, dominate cations and anions wouldhelp in quantifying the extent, nature anddistribution of saline area and scientificmanagement for its effective utilization.

164 Narjary et al.

Conclusion

By using geostatistical technique in a GISenvironment, spatial distribution of soil salinityat the field scale was mapped and quantitativelyevaluated. Dominant cation and anion responsiblefor soil salinity were identified using Pearsoncorrelation analysis and noticed that sodium (Na+)and chloride (Cl–) ions were mainly responsiblefor observed salinity in the field. By using multipleregression analysis model soil salinity, dominantcations (Na) i.e. Sodium (Na+) and Calcium +Magnesium (Ca2++Mg2+) and anion (Cl–) werepredicted and compared with the conventional wetchemistry methods. Quantitative evaluation of thefield revealed that about 96% of the field area wasaffected by salinity (ECe more than 4 dS m-1).

Considering the soil conditions of high initialsalinity, the EM instruments was reliable profilesalinity assessment tools for salinized soil in ourstudy area. The overall results of the investigationindicate that EM instrument is a reliable and rapidmethod for characterizing soil salinity at largescale for employing proper and precisereclamation measures for its effective utilization.

Acknowledgements

The present study is a part of the research project“Guidance in Identification of Problem Areas andDesign and Evaluation of Subsurface Drainage Projectsin Haryana”. The authors thank the HaryanaOperational Pilot project (HOPP), Haryana fortheir financial support.

References

Abrol IP, Yadav JSP and Massoud FI (1988) Salt-affected

Soils and their Management. FAO soils bulletin 39, Foodand Agriculture Organization, Rome.

Banerjee S, Das DK, Yadav BR, Gupta N, ChandrasekharanH, Ganjoo AK and Singh R (1998) Estimation of soilsalinity at IARl farm by Inductive Electro- magnetictechnique. Journal of Indian Society of Soil Science 46:llO-115.

Bhargava GP (2003) Training manual for undertaking studieson genesis of sodic /alkali soils. Technical Bulletin:CSSRI/Karnal/ 2003/, pp-111.

Brevik EC, Fenton TE and Lazari A (2006) Soil electricalconductivity as a function of soil water content andimplications for soil mapping. Precision Agriculture 7:393–404.

Corwin D L and Rhoades J D (1982) An improved techniquefor determining soil electrical conductivity-depthrelations from above-ground electromagneticmeasurements. Soil Science Society of America Journal 46:517-520.

Corwin DL and Lesch SM (2003) Application of soilelectrical conductivity to precision agriculture: theory,principles, and guidelines. Agronomy Journal 95(3): 455–471.

Corwin DL and Rhoades JD (1984) Measurement of invertedelectrical conductivity profiles using electromagneticinduction. Soil Science Society of America Journal 48: 288–291.

Doolittle JA and Brevik EC (2014) The use ofelectromagnetic induction techniques in soils studies.Geoderma 223: 33–45.

Doolittle JA, Sudduth KA, Kitchen NR and Indorante SJ(1994) Estimating depth to claypans usingelectromagnetic inductive methods. Journal of Soil WaterConservation 49(6): 552–555.

Friedman SP (2005) Soil properties influencing apparentelectrical conductivity: A review. Computer and Electronicsin Agriculture 46: 45–70.

Table 5. Classification and distribution of salinity (ECe), Na+, Ca2++Mg2+ and Cl– ion, of root zone soil profile (0-90 cm)

ECe Fields area of each salinization ECe (dS m-1) classiûcation (%)0-4 4-8 8-16 16-384 6 12 78

Na+ Fields area of each Na+ (meq l-1) ion classification (%)0- 100 100 - 200 200-300 300-400 400-500 500-600 600-700 700-800 800-900

9 7 6 6 7 8 16 21 20Ca2++Mg2+ Fields area of each Ca2++Mg2+ (meq l-1) ion classification (%)

25-50 50-75 75-100 100-125 125-1509 11 13 27 40

Cl– Fields area of each Cl– (meq l-1) ion classification (%)0-100 100-200 200-300 300-400

13 15 27 45


Goovaerts P (2001) Geostatistical modelling of uncertaintyin soil science.Geoderma 103: 3–26.

Gorai T, Ahmed N, Patra A K, Sahoo R N, Sarangi A, MeenaM C and Sharma R K (2015) Site specific nutrientmanagement of an intensively cultivated farm usinggeostatistical approach. Proceedings of the NationalAcademy of Sciences, India Section B Biological Science:doi:10.1007/s40011-015-0590-1

GuoY, Huang J, Zhou S and Hongyi L (2015) Mappingspatial variability of soil salinity in a coastal paddy fieldbased on electromagnetic sensors. PLoS ONE 10(5):e0127996. doi:10.1371/journal.pone.0127996

Hendrickx JMH, Baerends B, Raza ZI, Sadig M andChaudhry MA (1992) Soil salinity assessment byelectromagnetic induction of irrigated land. Soil ScienceSociety of America Journal 56: 1933–1941.

Huang J, Mehrjardi T R, Minasny B and Triantafilis J (2015)Modeling soil salinity along a hillslope in Iran byinversion of EM38 data. Soil Science Society of AmericaJournal 79: 1142-1153.

Huang J, Prochazka MJ and Triantafilis J (2016) Irrigationsalinity hazard assessment and risk mapping in the lowerMacintyre Valley, Australia. Science of the TotalEnvironment 551: 460-473.

Johnston MA, Savage MJ, Moolman JH and du Plessis HM(1997) Evaluation of calibration methods for interpretingsoil salinity from electromagnetic inductionmeasurements. Soil Science Society of America Journal 61:1627–1633.

Kachanoski RG, Gregorich EG and van Wesenbeeck IJ(1988) Estimating spatial variations of soil water contentusing noncontacting electromagnetic inductive methods.Canadian Journal of Soil Science 68: 715–722.

Kuligod VB, Salimath SB, Vijayashekhar K, Upperi SN andBalakrishnan P (2000) Calibration of inductiveelectromagnetic meter for determining electricalconductivity in vertisols of Upper Krishna projectcommand area. Proceedings of EM38 Workshop, NewDelhi, India. pp 24-27.

Lesch SM, Herrero J, and Rhoades JD, 1998. Monitoringfor temporal changes in soil salinity usingelectromagnetic induction techniques. Soil Science Societyof America Journal 62: 232–242.

Lesch SM, Rhoades JD, Lund LJ and Corwin DL (1992)Mapping soil salinity using calibrated electromagneticinduction measurements. Science Society of AmericaJournal 56: 540-548.

Mahmoodifard Z, Nazemi AH, Sadraddini SA and ShahbaziF (2014) Assessment of spatial and temporal distributionof groundwater salinity and alkalinity using ordinaryKriging; Case study: Ardabil Plain Aquifer. AgricultureScience Development 3: 244-250.

Mandal A K (2012) Delineation and characterization of saltaffected and waterlogged areas in the Indo-Gangeticplain of central Haryana (District Kurukshetra) forreclamation and management. Journal of Soil Salinity andWater Quality 4: 21–25.

Mandal AK, Sharma RC and Singh G (2009) Assessmentof salt affected soils in India using GIS. GeocartoInternational 24: 437–456.

McKenzie RC, George RJ, Woods SA, Cannon ME andBennett DL (1997) Use of the electromagnetic-inductionmeter (EM38) as a tool in managing salinization.Hydrogeology Journal 5: 37–50.

McNeill JD (1990) Geonics EM-38 Ground ConductivityMeter: EM38 Operating Manual: Geonics Limited.

Narjary B, Basak N, Jangra P and Meena MD (2014) Geo-physical tool (EM-38) for rapid appraisal of soil salinity.E book on Advanced technologies in land and waterremediation and management. (http://proj.iasri.res.in/cbp/ebook22.aspx?trainingApprovedId=SC-2014-498&trainingTitle=A dvanced+technologies+in+land+and+water+remediation+and+management).

Prasad R, Prasad B, Anitha PRK, Sambaiah GA and RatnamM (2000) Estimation of soil salinity at Konanki ORPsite under Nagarjuna Sagar Project Right CanalCommand Area by EM-38 meter - A case study.Proceedings of EM38 Workshop, New Delhi, India. pp27-30.

Rhoades JD and Corwin DL (1990) Soil electricalconductivity: effects of soil properties and applicationto soil salinity appraisal. Communication in Soil Scienceand Plant Analysis 21: 837–860.

Rhoades JD, Chanduvi F and Lesch S (1999) Soil salinityassessment: methods and interpretation of electricalconductivity measurements. FAO Irrigation andDrainage Paper #57. Food and Agriculture Organizationof the United Nations, Rome, Italy, pp. 1–150.

Saey T, Simpson D, Vermeersch H, Cockx L and VanMeirvenne M (2009) Comparing the EM38DD andDUALEM-21S sensors for depth-to-clay mapping. SoilScience Society of America Journal 73 (1): 7–12.

Sharma PN, Rana JS, Mathur DS, Sharma CP and GuptaVK (1997) Soil salinity measurement using the electro-magnetic induction method in the Chambal Commandarea. In: Hooja R, Visvanatha NA and Mundra SN (eds).Managing Drainage and Irrigation. pp 283 -288.

Slavich PG (1990) Determining ECa – depth profiles fromelectromagnetic induction measurements. AustralianJournal of Soil Research 28: 443–452.

Slavich PG and Petterson GH (1990) Estimating averagerootzone salinity from electromagnetic induction (EM-38) measurements. Australian Journal of Soil Research 28:453–463.

166 Narjary et al.

Sudduth KA, Drummond ST and Kitchen NR (2001)Accuracy issues in electromagnetic induction sensingof soil electrical conductivity for precision agriculture.Computer and Electronics in Agriculture 31: 239–264.

Triantaûlis J, Laslett GM and Mcbratney AB (2000)Calibrating an electromagnetic induction instrument tomeasure salinity in soil under irrigated cotton. ScienceSociety of America Journal 64: 1009–1017.

Urdanoz V and Aragüés R (2012) Comparison of GeonicsEM38 and Dualem 1S electromagnetic induction sensorsfor the measurement of salinity and other soil properties.Soil Use and Management 28: 108–112.

Wittler JM, Cardon GE, Gates TK, Cooper CA andSutherland PL (2006) Calibration of electromagnetic

induction for regional assessment of soil water salinityin an irrigated valley. Journal of Irrigation and DrainageEngineering 132: 436-444.

Yao R and Yang J (2010) Quantitative evaluation of soilsalinity and its spatial distribution using electromagneticinduction method. Agriculture Water Management97:1961–1970.

Yao R and Yang JS (2010) Quantitative evaluation of soilsalinity and its spatial distribution using electromagneticinduction method. Agriculture Water Management 97:1961-1970.

Received in February 2017; Accepted in May 2017

Physiological and Biochemical Characterization of RiceVarieties under Salt and Drought Stresses

Ashwani Kumar1, *, Charu Lata1, SL Krishnamurthy1, Arvind Kumar1,KRK Prasad1 and Neeraj Kulshreshtha2

1ICAR-Central Soil Salinity Research Institute, Karnal – 132001, Haryana, India2ICAR-Sugarcane Breeding Institute, Regional Centre, Karnal – 132001, Haryana, India

*Corresponding author E-mail: [email protected]

Abstract

A well-focused approach combining the physiological and biochemical aspects of stress tolerance is essential toevaluate the drastic effects of salinity and drought. This strategy involves comparative investigation of variousmorphological, physiological, biochemical responses together with ionic relationship at vegetative stage undersalt stress coupled with drought. Two salt-tolerant (CSR 10 and CSR 36) and two susceptible (IR 29 and Pusa44) varieties of rice were subjected to salt stress coupled with drought stress conditions. Results showed significantdecline in growth, chlorophyll content, number of tillers, productive tillers, biomass and yield in sensitivevarieties, while tolerant varieties were less affected due to stress conditions. Total soluble sugars, proline andprotein content increased with inclined stress in all the varieties, which showed osmotic adjustment in terms ofaccumulation of compatible solutes. The varieties CSR 10 and CSR 36 accumulated less Na+ ion in leavesunder stress. Under combined stresses, the highest value of K+/Na+ ratio was recorded in CSR 36, whereas,lowest in IR 29. In comparison with control treatment, at 100mM NaCl along with 25% water deficit (WD) and50% WD, highest reduction in grain yield was shown by IR 29 (96.6%) followed by Pusa 44 (80.64% and98.6%), CSR 36 (44.86% and 52.7%) and CSR 10 (21.0% and 28.3%). Study concluded that growth parameters,physiological and biochemical traits had a significant varietal variation, indicating that these parameters couldbe used as screening criteria for selecting the tolerant and sensitive cultivars exposed to water limiting stresses(salinity and drought).

Key words: Water deficit, Salinity, Biochemical responses, Chlorophyll conten, Yield attributes, Rice varieties.

Introduction

The global demand for cereals is expected to risein the future as countries become wealthier andthe population rises. Crop yields are not increasingquickly enough to support estimated global needsand world agriculture is facing a stiff challengeof producing 70% more food for an estimatedadditional 2.3 billion people by 2050. Climatechange and environmental concerns are becomingthe key issues to sustainability of agriculturealtering congenial crop growth conditions, causingoccasional/frequent crop failure and decreasingcrop yields more than half of the anticipatedharvestable yields (Wu et al., 2011). Rice is theprimary food grain consumed by almost half ofthe world’s population. Rice productivity andsustainability fluctuate greatly in time and spacebecause the crop’s cultivation under diverse

weather/ecological conditions owing to continualthreat by a series of abiotic and biotic stresses,particularly in the era of global climate change.Among the abiotic stresses, water deficit stress dueto drought/soil salinization is probably the mostdevastating environmental concern limiting cropproduction particularly in arid and semi-aridproduction ecologies (Hartmann et al., 2005).Osmotic adjustment by accumulating compatiblesolutes has been considered as an importantphysiological plant adaptation to increased salinitytolerance (Ashraf and Harris, 2004) and droughtresistance (Zhang et al., 2009), which as suchfacilitate extracting water, maintaining cell turgor,gas exchange and growth even in drierenvironments (Chaves et al., 2003). Soluble sugarsand proline are two most important compatiblesolutes within plants (Hessini et al., 2009; Kumaret al., 2016b), having significant role in adjusting


168 Kumar et al.

soil water potential and regulating osmoticpotential (Martin et al., 1993) to counter theadverse micro-climatic situations. Besides theirroles in osmotic adjustment, they may also protectmembranes from damages and stabilize thestructures and activities of proteins and enzymes(Hessini et al., 2009; Kumar et al., 2015).

With the rapid growth in human populationconsuming rice and the deteriorating soil healthand ground water quality around the globe, thereis an urgent need to understand the crop’s responsetowards these environmental abuses and playingcritical role in narrowing down the targetable yieldpotentials. Taking this into consideration,experiment was conducted to evaluate the effectsof combined salinity and water deficit irrigationon rice to address the shortage of water resourcesand increasing water and soil salinity in arid andsemi-arid zones. The exploitation of availablegermplasm has the great significance in identifyingthe genotypes/varieties performing well evenunder stress conditions and understanding thephysiological and biochemical mechanismsinfluencing plant’s growth in stress environments(drought/salinity) is still a major challenge. Withthe ultimate goal to grow rice plant with bettersuitability towards changing environmental inputs,intensive efforts are being employed to identifyand develop appropriate physiological andbiochemical tools to understand the keymechanism of tolerance in rice varieties (sensitivevs. tolerant) in context of Indian agriculture andsimilar environments.


Experimental site and climate

Present study was performed in clay/porcelainpots in net house of Crop Improvement Division,ICAR-Central Soil Salinity Research Institute,Karnal, Haryana, India. The region witnesses sub-tropical and sub-humid climate with hot summers.The mean monthly maximum temperaturetouched 32-34°C while minimum temperatureremained 22-24°C during the study period. Theaverage annual rainfall of the area is around 740mm of which nearly 80% is received during a shorttime span of July to mid-September which isassociated with high relative humidity. The pan

evaporation normally exceeds rainfall throughoutthe year except for the monsoonal months.

Plant material, growth conditions andexperimental details

Four rice varieties, two salt-tolerant (CSR 10 andCSR 36) and two salt-sensitive (IR 29 and Pusa44) were selected to evaluate their relativetolerance against the salt-stress coupled withdrought (water deficit) and to identify the keyphysiological and biochemical traits influencingcrop growth and development during the stressperiods. A total of seven treatments including twoconcentrations of sodium chloride (NaCl) i.e. 50and 100 mM alone and in combination with 25%and 50% water deficit (WD) along with absolutecontrol were superimposed on test varieties in arandomized complete block design with 5replications in 20 kg capacity clay/porcelain pots.The net house was covered with a high qualitytransparent polythene sheet to avoid the rain waterentry and to maintain the desired salinity andwater deficit stress as per treatments. Surfacesterilized seeds each of CSR 10, CSR 36, IR 29and Pusa 44 were directly sown and raised in pots.Plants were supplied with Hoagland nutrientsolution before imposition of stress as describedby Hoagland and Arnon (1950). Drought stresswas created by gradually decreasing the watersupply to the pots. Drought treatments wereimposed by 100% saturation of soil in pots firstand then withholding irrigation supply till thedepletion of water to 25 and 50% of water in soil(25 and 50% water scarcity). Osmotic stress wasimposed 3 weeks after sowing of seeds.

Imposed treatments

Water deficit: 20 kg capacity clay/porcelain potsfilled with 16 kg soil (ECe 0.47; pH 7.8; fieldcapacity 28% v/v) at bulk density of 1.45 g cc-1

which has ~ 40% porosity. Initially 6.5 litre water(up to field capacity) was given in the pots atweekly interval and evaporation was notedthrough pan. During the entire study period panevaporation was 2-3 mm day-1 i.e. 21 mm week-1.On this basis, 25 and 50 per cent water deficittreatments were induced.

Salt treatment: Based on the water requirementof the pots, 50 mM NaCl and 100 mM NaCl

Biochemical responses of rice varieties under salt and drought stresses 169

concentration was given to pots at regular weeklyinterval. At final harvest, 50 mM NaClconcentration pots had mean salinity level aboutECe: 3.7 dS m-1 and 100 mM NaCl pots had ECe:7.9 dS m-1.

Biometric observations

The data on growth, physiological andbiochemical parameters were taken 2 weeks afterthe imposition of stress treatments. Treatment-wise fully expanded leaves were sampledseparately for measurement of chlorophyll contentusing DMSO (Dimethyl sulphoxide) as describedby Hiscox and Israelstam (1979). Freshlyharvested plant samples (leaves) were weighed andanalysed for total soluble sugars (Yemm andWillis, 1954), proline (Bates et al., 1973) andprotein content (Bradford, 1976). Ionic (Na+ andK+) contents were determined from well groundplant material using di-acid mixture(HNO3:HClO4 3:1) on flame-photometer (PFP7,Jenway, Bibby Scientific, UK). Leaf chloridecontent was determined volumetrically bymodified method of Chhabra (1973).

Statistical analysis

All the data were subjected to statistical analysisusing statistical programme SAS Version 9.3 (SASInstitute Inc., Cary, NC, USA) using Duncan’smultiple range test.


Morpho-physiological parameters

Water deficit occurred because of salinity anddrought, and influenced the absorption/utilizationphenomenon to such an extent that the tolerancemechanisms employed by growing plants in astressful environment were quite inadequate tomaintain their normal physiological growthinducing fundamental changes in water relations,biochemical and physiological processes(Yordanov et al., 2003).

Plant height

Leaves, which are the main organs forphotosynthesis and transpiration, play animportant role in regulating the plant growth anddevelopment, especially under stress conditions

(Pitann et al., 2009). The data presented in Table1 revealed that plants exposed to salt stress alone(T2 and T3) and in combination with drought (T4-T7) showed significant reduction in plant heightat harvest, in comparison to non-stressed plants(control). The mean maximum reduction (37.0%)in plant height was noticed with application of100 mM NaCl + 50% WD (T7) in all the testvarieties. Among varieties, least reduction in plantheight (16.0%) was observed in CSR 10 withimposition of stress treatments followed by CSR36 (17.4%), IR 29 (23.7%) and Pusa 44 (25.9%).Imposition of salt stress (irrespective of varieties)resulted in shorter plants (8.8%) in contrast tounstressed plants, however 25 and 50% WD alongwith induced salt stress further reduced the plantstature by 20 and 33.5%, respectively over thepreceding one. Pitann et al. (2009) also reportedthe inhibited cell division, expansion, increasedH-pumping and apoplastic pH because of stressinduced plant growth.

Total chlorophyll content

The total chlorophyll content (ChlT) has beenknown as an index for evaluation of plant growth;therefore, decrease in its concentration can beconsidered as a stomata non-limiting factor understress conditions. Water deficit coupled with saltstress imposed at the vegetative stage, significantlydecreased total chlorophyll content though thereductions were found to be varietal specific (Table1). Consistent and significant reduction in ChlT

values was observed with the increase in theintensity of salt stress alone or along with waterdeficit (25 or 50% WD). Among varieties, meanmaximum reduction (42.11%) in ChlT wasrecorded in IR 29 followed by CSR 36 (40.36%),Pusa 44 (38.1%) and the minimum being in CSR10 (18.1%). ChlT decreased with the stressintensification irrespective of the test varieties.Across different stress treatments, CSR 10 hadrelatively higher values of ChlT (19.55 µg/ml) instressed environments in comparison to others.Lower ChlT in Pusa 44, CSR 36 and IR 29 undersalt stress conditions could be ascribed to increasedactivity of chlorophyll-degrading chlorophyllaseenzyme and inhibition of chlorophyll-synthesisALA synthase enzyme (Santos, 2004). A decrease

170 Kumar et al.

Table 1. Growth, physiological and yield attributes of four rice varieties under interactive salinity and drought stresses

Variety Treatments Plant Chlorophyll Number Number of Biomass Grainheight content of tillers productive (g plant-1) yield(cm) (µg ml-1) plant-1 tillers plant-1 plant-1 (g)

CSR 10 Control (T1) 92.20d 23.87c 9.38a 8.80a 26.75b 12.83a

50 mM NaCl (T2) 84.35ij 20.94e 8.35c 7.28d 22.51ef 12.62b

100 mM NaCl (T3) 83.05k 18.12gh 7.79e 5.68f 18.34ij 11.43c

50 mM NaCl + 25 % WD (T4) 80.35mn 16.25i 7.92d 6.90e 19.39hi 10.83d

100 mM NaCl + 25 % WD (T5) 76.35p 14.72j 6.65de 4.42j 15.94k 9.65f

50 mM NaCl + 50 % WD (T6) 72.15r 10.63m 5.99n 3.57o 14.91kl 10.13e

100 mM NaCl + 50 % WD (T7) 68.22s 9.16n 4.68p 2.02s 13.43lm 9.18g

General Mean 79.52 19.55 7.25 5.5 18.75 10.95

LSD (p≤0.05) 1.029 0.5051 0.0836 0.1315 2.1717 0.187

CSR 36 Control (T1) 109.90a 27.23b 10.72c 9.90b 25.97bc 14.82a

50 mM NaCl (T2) 103.12b 24.00c 9.47f 8.08f 20.38gh 14.34b

100 mM NaCl (T3) 95.59c 23.09c 8.84h 7.34h 19.92ghi 11.84c

50 mM NaCl + 25 % WD (T4) 90.67e 19.48f 9.06h 7.74g 23.75de 10.52d

100 mM NaCl + 25 % WD (T5) 88.34f 16.26i 8.97j 5.14k 16.27k 7.52f

50 mM NaCl + 50 % WD (T6) 85.46h 14.39jk 5.37l 2.88m 14.73kl 8.14e

100 mM NaCl + 50 % WD (T7) 81.79l 12.40l 3.98o 1.49q 13.39lm 7.05g

General Mean 93.55 16.24 8.06 6.1 19.20 10.60

LSD (p≤0.05) 0.034 1.2382 0.1552 0.1413 1.3184 0.1897

IR 29 Control (T1) 87.12g 27.21b 9.08d 8.31c 24.49cd 14.92a

50 mM NaCl (T2) 84.78hi 21.35de 8.12g 5.27i 16.59jk 11.76b

100 mM NaCl (T3) 81.02m 17.35h 5.67m 3.52m 10.78nop 6.16d

50 mM NaCl + 25 % WD (T4) 77.28o 15.73i 6.68j 3.26n 14.99kl 7.07c

100 mM NaCl + 25 % WD (T5) 58.96u 13.70k 5.23n 1.90r 12.59mn 3.25e

50 mM NaCl + 50 % WD (T6) 52.41v 10.16m 0.85r 0.10u 10.53op 0.24f

100 mM NaCl + 50 % WD (T7) 44.42x 4.72o 0.67r 0.10u 8.07qr 0.21f

General Mean 69.29 15.75 5.19 3.21 14.01 6.23

LSD (p≤0.05) 1.1469 1.1141 0.1624 0.0989 2.593 0.0947

Pusa 44 Control (T1) 92.34d 31.52a 9.70b 8.70b 29.80a 20.14a

50 mM NaCl (T2) 83.98j 27.14b 7.92h 3.75l 21.54fg 15.83b

100 mM NaCl (T3) 79.72n 21.92d 6.29k 2.62p 11.63mno 9.69d

50 mM NaCl + 25 % WD (T4) 75.09q 18.94fg 7.25i 2.98o 14.71kl 11.69c

100 mM NaCl + 25 % WD (T5) 64.26t 14.33jk 5.66m 2.58p 11.26no 4.95e

50 mM NaCl + 50 % WD (T6) 58.97u 12.38l 3.52q 0.66t 8.85pq 3.86f

100 mM NaCl + 50 % WD (T7) 48.48w 10.36m 0.10s 0.10u 6.61r 0.30g

General Mean 71.83 19.51 5.78 3.06 14.91 9.49

LSD (p≤0.05) 0.9932 1.3222 0.4046 0.1028 3.1166 0.1227

Means with at least one letter common are not statistically significant (p≤0.05)) using LSD Test

of total chlorophyll with drought stress implies alowered capacity for light harvesting. Since theproduction of reactive oxygen species is mainlydriven by excess energy absorption in thephotosynthetic apparatus, this might be avoidedby degrading the absorbing pigments (Herbingeret al., 2002).

Yield attributes

Total number of tillers and productive tillers

Tillering is an essential plant growth componentcontributing to final crop harvest. Maximumnumber of tillers were recorded with all varietiesin control treatment but had significant differences


(p≤0.01) between themselves due to treatmenteffects. On an average, number of tillers reducedfrom 12.9 to 75.9% depending on the stresstreatments in comparison to control (unstressed)with the minimum with 100 mM NaCl + 50%WD. In general, tolerant varieties (CSR 10 andCSR 36) performed relatively better than sensitiveones (IR 29 and Pusa 44) following the order ofCSR 36> CSR 10> IR 29> Pusa 44 (Table 1). It isinteresting to note that drastic reduction in tilleringwas observed in case of Pusa 44 (94.3%) with theincrease in salt stress from 50mM NaCl to 100mMNaCl coupled with 50% WD (T6 to T7) indicatingthe more sensitive nature of this variety amongthe tested ones towards water deficit.

Stress treatments significantly influenced theproduction of effective tillers plant-1 comparedto unstressed plants (control) in all the testvarieties. On an average, CSR 36 possessed thehighest number of productive tillers (6.1 plant-1)closely followed by CSR 10 (5.5 plant-1), bothbeing significantly superior to IR 26 and Pusa 44(3.2 and 3.1 plant-1). Averaged over varieties,drastic reduction in production pattern wasobserved with the increase in salt stress andsubsequent imposition of water deficit with themaximum reduction (89.3%) being noted withstress induction through application of 100 mMNaCl + 50% WD (Table 1). Virtually no effectivetillers were produced (~98% reduction) in case ofboth sensitive varieties (IR 29 and Pusa 44) withalmost 77-85% reduction in tolerant ones (CSR10and CSR 36). Salt-tolerant varieties (CSR 10 andCSR 36) produced more productive tillers (Table1) than that of sensitive varieties (IR 29 and Pusa44) and this can be used as a selection (simpleand non-destructive) criterion to assess thetolerance limits of evaluated varieties (Asgari etal., 2012).

Biomass accumulation and grain yield

Highly sig-nificant differences in response to testvarieties and induced stress treatment individuallyas well as cumulatively were observed foraccumulated biomass in rice (Table 1). The effectof salt stress (NaCl concentration) coupled withdrought (25 and 50% WD) was more profoundwhen it was applied at vegetative stage, as shownby the significant reduction in accumulated

biomass when compared to the well-wateredtreatment. The highest reduction was observed inPusa 44 (70.27% and 77.85%) and IR 29 (57% and67.04%) and the lowest reduction in CSR 10(44.3% and 49.8%) and CSR 36 (43.3% and48.4%) at 50 per cent water deficit with 50 and100 mM NaCl as compared to the respectivecontrol (Table 1).

Salt stress coupled with drought hastened thenormal plant growth and development, dry matterproduction and finally the yield. Grain yield wassignificantly influenced by treatment (varieties andstress) effects. The mean comparison of grain yield(Table 1) showed that tolerant varieties performedcomparatively well in comparison to sensitive onesfollowing the order of CSR 10> CSR 36> Pusa44> IR 29. Consistent and significant reductionin grain yield was observed in all test varieties byintensification of salt stress coupled withincreasing water deficit (25 and 50% WD)recording highest reduction (73.8%) in case of 100mM NaCl with 50% WD (T7). At the same levelof stress treatment 100 mM NaCl with 50% WD,yield reduction ranging from as low as 28.3%(CSR 10) to as high as 98.7% (IR 29 and Pusa 44)was recorded. Varieties exhibited significantvariability for biomass accumulation and grainyield under the influence of varying degree of saltstress and water deficit either individually and incombination. This could be ascribed to decreasedpollen viability and stigma receptivity leading topoor seed setting, chaffy grains and reduced seedweight under stress conditions ultimatelyculminating in lower crop yields (Saini, 1997). El-Hendawy et al. (2005) also observed genotypicvariability for yield differences under stressenvironments.

Biochemical attributes

Plant adaptations through accumulation ofcompatible solutes are another strategy towithstand stress conditions where they functionin osmotic adjustment and osmo-protection(Patade et al., 2008; Kumar et al., 2016a).

Total soluble sugars

Biochemical analysis of leaves of different ricevarieties for total soluble sugars (TSS), exhibited

172 Kumar et al.

differential response to variable stress conditions,exhibiting relatively higher values in tolerantvarieties (CSR 10 and CSR 36) compared tosensitive ones (IR 29 and Pusa 44) following thetrend of CSR 36> CSR 10> IR 29> Pusa 44 (Fig.1). Total soluble sugars significantly increased withthe increase in salt stress alone or along withdrought regardless of the NaCl concentration andwater deficit (T2-T7 treatments) in comparison tounstressed plants (T1). Averaged over varieties,highest values of TSS (44.95 mg g FW-1) wasobserved with application of 100 mM NaCl + 50%WD with 32.6% increase over the controltreatment (T1). Elevated sugar levels under stressconditions might contribute towards turgormaintenance (Spyropoulos, 1982; Burke, 2007).

Proline content

Proline is one of the most important organic solutethat plays an important role in osmotic balancingunder stress conditions. Gradual increase inproline content in all test varieties was noticed withthe stress intensification (Fig. 2). Prolonged waterdeficit conditions significantly increased prolinecontent by 71.2 and 130.2% under mild (25% WD)and/or severe stress (50% WD) coupled with saltstress, respectively. It is interesting point to notethat sensitive varieties accumulated more prolinethan the tolerant ones (Fig. 2). At the same levelof 100 mM NaCl + 50% WD (T7), prolineaccumulation increased by 2.23, 2.05, 2.43 and2.75-fold in CSR 10, CSR 36, IR 29 and Pusa 44with respect to control and followed the order Pusa

Fig. 1. Effect of salt stress coupled with drought on total soluble sugars in different rice varieties

Fig. 2. Effect of salt stress coupled with drought on proline content in different rice varieties


44 > IR 29 > CSR 10 > CSR 36. It is interestingto note that sensitive varieties (IR 29 and Pusa44) accumulated more proline content thantolerant ones (CSR 10 and CSR 36) to compensateor balance the intracellular osmotic potential(Chen et al., 2007) necessary for cell expansionunder stress conditions (Matysik et al., 2002,Sairam and Tyagi, 2004).

Total soluble proteins

Proteins accumulations are particularly importantfor cell survival under stress conditions and causesmembrane stabilization (Kumar et al., 2015).Within varieties, variations in protein content wereobserved across stress treatments, though itsignificantly increased with the increase inconcentration of salt stress alone or along withwater deficit (Fig. 3). Highest protein content (6.50mg g DW-1) was observed with 100 mM NaCl +50% WD (T7) stress level with 64.6% higher tothat obtained in case of unstressed plants (control).Among varieties, total soluble proteins were foundto be highest (5.80 mg g DW-1) in CSR 36 and thelowest (4.90 mg g DW-1) in case of IR 29.Consistent improvement in protein content of ricevarieties showed continuous increasing trend butvaried at all the levels of stress treatment. Theincrement in protein content from control to 100mM NaCl + 50% WD stress level was found tobe nearly similar (60%) in all varieties except forCSR 36 (67.9% increase). Maximum protein

accumulation was observed in CSR 36 and CSR10 (6.91 mg g DW-1) while minimum in IR 29 (6.01mg g DW-1) at 100 mM NaCl+50% WD (Fig. 3).

Ionic relations

It is well documented that in addition toaccumulation of compatible organic solutes, anenhancement in specific inorganic ions and K+/Na+ discrimination under stress conditionsconstitutes an important mechanism of planttolerance (Flowers et al., 1977).

Leaf Na+ concentration

Stress treatment started when the seedlings were21 days old and had 4-5 green healthy leaves.Increasing stress level significantly increased theuptake of leaf Na+ concentration in all testvarieties. In general, the sensitive varieties (Pusa44 and IR 29) accumulated higher concentrationof Na+ in their leaves as compared to tolerant ones(CSR 10 and CSR 36) at all the stress levels rangingfrom well-watered plants to 50% WD along with50 mM and 100 mM NaCl. Irrespective of thevarieties, leaf Na+ concentration was the highest(0.55% DW) with maintenance of 100 mM NaCl+ 50% WD stress level (Fig. 4). At the same levelof 100 mM NaCl +50% WD, sensitive varietiesIR 29 and Pusa 44 maintained significantly higherNa+ concentration (0.65% DW), whereas, thetolerant CSR 36 accumulated the lowest amountof Na+ concentration (0.42% DW).

Fig. 3. Effect of salt stress coupled with drought on total soluble proteins in different rice varieties

174 Kumar et al.

Fig. 4. Effect of salt stress coupled with drought on Na+ concentration in different rice varieties

Fig. 5. Effect of salt stress coupled with drought on K+ concentration in different rice varieties

Leaf K+ concentration

The data presented in Fig. 5, revealed that NaCland WD induced osmotic stress treatmentssignificantly influenced the ionic concentration,and the leaf K+ concentration declinedsignificantly (p≤0.01) with the increasing stresslevels. Highest leaf K+ concentration (0.96% DW)was observed in well-watered plants (T1) and thelowest in case of induced stress through 100 mMNaCl +50% WD (T7). Leaf K+ concentrationdiffered significantly across all test varieties, beingthe lowest under IR 29 (0.58% DW) and highestin case of CSR 36 (0.76% DW). Significantdifferences in leaf K+ concentrations were noticedamong the differential treatment effects of NaCl

and WD in relation to the ion concentration. Atthe highest stress conditions (T7), K+ concentration(% DW basis) decreased from 1.0 to 0.43% in CSR10, 1.05 to 0.48% in CSR 36, 0.85 to 0.36% in IR29 and 0.92 to 0.43% in Pusa 44 in comparison tothe control (Fig. 5).

In the present study, the salt tolerant varieties(CSR 10 and CSR 36) maintained lowconcentration of Na+ in their leaves than those ofsalt sensitive lines, when exposed to stress. BothNa+ and K+ ions compete for entry into plant rootcells and the replacement of K+ by Na+ often leadsto nutritional imbalances having significantnegative effects on plant growth under stressconditions, where concentrations of Na+ often


exceed those of K+ (Tunuturk et al., 2011). It isgenerally known that the maintenance of low leafNa+ concentration and K+/Na+ ratio is animportant aspect of stress tolerance (Kumar et al.,2016a). Due to high uptake and accumulation ofNa+ and antagonistically low uptake, translocationand accumulation of K+ and enhanced K+ effluxunder salt stress coupled with drought suppressedgrowth by decreasing the capacity of osmoticadjustment and turgor maintenance or byinhibiting metabolic activities in salt sensitivevarieties (Kumar et al., 2016b). The diminutionof K+ concentration in tissue may also be due todirect competition between K+ and Na+ at plasmamembrane, inhibition of Na+ on K+ transportprocess in xylem tissues and/or Na+ induced K+

efflux from the roots (Mann et al., 2015).

Leaf Cl – concentration

Plant exposed to stress conditions for longerperiods generally leads to higher concentration ofchloride load in the aerial parts, particularly theleaves. Genotypic differences were observed forleaf Cl- concentration under NaCl and WDinduced osmotic stress treatments. Indeed, CSR10 accumulated least leaf Cl- content (2.66% DW)while IR 29 had a statistically higher (5.31% DW)concentration among the tested varieties acrossinduced stress levels. Leaf Cl- content increasedwith the increasing degree of salt stress coupledwith WD and the maximum Cl- accumulation was

observed in IR 29 (10.8% DW) followed by Pusa44 (10.62% DW), CSR 36 (6.02% DW) and CSR10 (5.66% DW) at 100 mM NaCl + 50% WD (Fig.6).

Excessive accumulation of Na+ and Cl” in theleaves has been considered highly harmful fornormal metabolism of plants, and tolerantgenotypes have the capacity of successful saltexclusion. The less accumulation of Na+ and Cl”

shown by tolerant varieties under stresses mightprobably be due to the better control of root systemfor absorption of these ions (Salim and Pitman,1983), a higher salt retention in roots or a strongerre-translocation of these ions to the roots viaphloem (Lessani and Marschner, 1978).

Conclusions

In the present study, growth parameters, andphysiological and biochemical traits had asignificant varietal variation and the cumulativeeffect of salt and drought stress exhibited asignificant decline in growth, chlorophyll content,number of tillers, productive tillers, biomass andyield which were drastically reduced in sensitivevarieties, while tolerant varieties were less affected.Rice variety CSR 10 performed comparativelybetter in terms of grain yield in comparison toother ones following the order of CSR 10> CSR36> Pusa 44> IR 29 exposed to water limitingstresses (salinity and drought).

Fig. 6. Effect of salt stress coupled with drought on Cl- concentration in different rice varieties

176 Kumar et al.

Acknowledgements

The authors are thankful to Head, CropImprovement Division and Director, ICAR-CSSRI for providing the required researchfacilities to conduct this study.

References

Asgari HR, Cornelisb W and Van Dammec P (2012) Saltstress effect on wheat (Triticum aestivum L.) growth andleaf ion concentrations. International Journal of PlantProduction 6(2): 195-208.

Ashraf M and Harris PJC (2004) Potential biochemicalindicators of salinity tolerance in plants. Plant Science166: 3-16.

Bates LS, Waldren RP and Teare ID (1973) Rapiddetermination of free proline for water-stress studies.Plant Soil 39: 205-207.

Bradford MM (1976) A rapid and sensitive method for thequantification of microgram quantities of proteinutilizing the principle of protein-dye binding. AnalyticalBiochemistry 72: 248-254.

Burke JJ (2007) Evaluation of source leaf responses to water-deficit stresses in cotton using a novel stressbioassay. Plant Physiology 143: 108–121.

Chhabra R (1973) Kinetics of absorption of chloride andphosphorus, their interaction and effect on growth andcomposition of tomato plants. Ph.D. Thesis, KUL,Belgium.

Chaves MM, Maroco JP and Pereira JS (2003)Understanding plant responses to drought – from genesto the whole plant. Functional Plant Biology 30: 239–264.

Chen Z, Cuin TA, Zhou M, Twomey A, Naidu BP andShabala S (2007) Compatible solute accumulation andstress-mitigating effects in barley genotypes contrastingin their salt tolerance. Journal of Experimental Botany58(15-16): 4245-4255.

El-Hendawy SE, Hua Y, Yakout GM, Awad AM, HafizbSE and Schmidhalter U (2005) Evaluating salt toleranceof wheat genotypes using multiple parameters. EuropeanJournal of Agronomy 22: 243-253.

Flowers TJ, Troke PF and Yeo AR (1977) The mechanismsof salt tolerance in halophytes. Ann Rev Plant Physiology28: 89-121.

Hartmann T, College M and Lumsden P (2005) Responsesof different varieties of Lolium perenne to salinity. AnnualConference of the Society for Experimental Biology,Lancashire.

Herbinger K, Tausz M, Wonisch A, Soja G, Sorger A andGrill D (2002) Complex interactive effects of droughtand ozone stress on the antioxidant defence systems oftwo wheat cultivars. Plant Physiology and Biochemistry 40:691–696.

Hessini K, Martínez JP, Gandour M, Albouchi A, Soltani Aand Abdelly C (2009) Effect of water stress on growth,osmotic adjustment, cell wall elasticity and water-useefficiency in Spartina alterniflora. Environmental andExperimental Botany 67: 312–319.

Hiscox JD and Israelstam GF (1979) A method for theextraction of chlorophyll from leaf tissue withoutmaceration. Canadian Journal of Botany 52: 332–334.

Hoagland DR and Arnon DI (1950) The water culturemethod of growing plants without soil. CaliforniaAgricultural Experimental Station Circular 347: 1–32.

Kumar A, Kumar A, Lata C and Kumar S (2016a) Eco-physiological responses of Aeluropus lagopoides (grasshalophyte) and Suaeda nudiflora (non-grass halophyte)under individual and interactive sodic and salt stress.South African Journal of Botany 105: 36-44.

Kumar A, Krishnamurthy SL, Lata C, Kumar P, Devi R,Kulshrestha N, Yadav RK and Sharma SK (2016b) Effectof dual stress (salinity and drought) on gas exchangeattributes and chlorophyll fluorescence characteristicsin rice. Indian Journal of Agricultural Sciences 86(6): 19-27.

Kumar A, Sharma SK, Lata C, Sheokand S and KulshreshtaN (2015) Combined effect of boron and salt onpolypeptide resolutions in wheat varieties differing intheir tolerance. Indian Journal of Agricultural Sciences85(12): 1626–32.

Lessani H and Marschner H (1978) Relation between salttolerance and long-distance transport of sodium andchloride in various crop species. Australian Journal ofPlant Physiology 5: 27-37.

Mann A, Bishi SK, Mahatma MK and Kumar A (2015)Metabolomics and salt stress tolerance in plants. In:Managing Salt Tolerance in Plants: Molecular and GenomicPerspectives. Taylor and Francis Group, LLC. pp 251-266.

Martin M, Miceli F, Morgan JA, Scalet M and Zerbi G (1993)Synthesis of osmotically active substrates in winterwheat leaves as related to drought resistance of differentgenotypes. Journal of Agricultural Crop Science 171: 176-184.

Matysik J, Bhalu AB and Mohanty P (2002) Molecularmechanisms of quenching of reactive oxygen species byproline under stress in plants. Current Science 82: 525–532.

Patade VY, Suprasanna P and Bapat VA (2008) Effects ofsalt stress in relation to osmotic adjustment on sugarcane(Saccharum officinarum L.) callus cultures. Plant GrowthRegulation 55: 169-173.

Pitann B, Kranz T and Muhling KH (2009) The apoplasticpH and its significance in adaptation to salinity in maize(Zeas mays): comparison of fluorescence microscopy andpH-sensitive microelectrodes. Plant Science 176: 497-504.


Saini HS (1997) Effect of water stress on male gametophytedevel-opment in plants. Sexual Plant Reproduction 1: 67-73.

Sairam RK and Tyagi NK (2004) A Physiology andmolecular biology of salinity stress tolerance in plants.Current Science 86: 407–20.

Salim M and Pitman MG (1983) Effects of salinity on ion-uptake and growth of mungbean plants (Vigna radiataL.). Australian Journal of Plant Physiology 10: 395-407.

Santos VC (2004) Regulation of chlorophyll biosynthesis anddegradation by salt stress in sunflower leaves. ScientiaHorticulture 103(1): 93-99.

Spyropoulos CG (1982) Control of sucrose metabolism inpolyethylene glycol stressed carob (Ceratonia siliqua L.)young seedling. The role of sucrose. Journal ofExperimental Botany 33: 1210–1219.

Tunuturk M, Tuncturk R, Yildirim B and Ciftci V (2011)Effect of salinity stress on plant fresh weight and nutrient

composition of some Canola (Brassica napus L.)cultivars. African Journal of Biotechnology 10: 1827-1832.

Wu C, Wang Q, Xie B, Wang Z, Cui J and Hu T (2011)Effects of drought and salt stress on seed germinationof three leguminous species. African Journal ofBiotechnology 10: 17954-17961.

Yemn EW and Willis AJ (1954) The estimation ofcarbohydrates in plant extracts by anthrone. BiochemicalJournal 57: 508-514.

Yordanov I, Velikova V and Tsonev T (2003) Plant responsesto drought and stress tolerance. Bulgarian Journal of PlantPhysiology (Special issue): 187-206.

Zhang J, Dell B, Conocono E, Waters I, Setter T and AppelsR (2009) Water deficits in wheat: fructan exohydrolase(1-FEH) mRNA expression and relationship to solublecarbohydrate concentrations in two varieties. NewPhytology 81(4): 843–850.

Received in April, 2017; Accepted in June 2017

Land-use Influences Soil Properties of Sodic Landin Northwest India

Ashim Datta1 *, Nirmalendu Basak1, Anil R Chinchmalatpure2,Rakesh Banyal1 and SK Chaudhari3

1Division of Soil and Crop Management, ICAR-Central Soil Salinity Research Institute, Karnal-132 001, Haryana, India2Regional Research Station, ICAR-Central Soil Salinity Research Institute, Bharuch-392 012, Gujarat, India

3Division of Natural Resource Management, Krishi Anusandhan Bhawan-II, New Delhi-110 012, India*Corresponding author E-mail: [email protected]

Abstract

Characterization and classification of soil resources are essential for sustainable land use planning as well asimplementation of reclamation measures in problem soils. Changes in soil properties up to 200 cm of soildepth were studied in different land uses of gypsum treated reclaimed rice-wheat, Eucalyptus, Fallow and rice-wheat (R-W) at farmer’s field in Indo-Gangetic Plain of Western India and compared with the soil data asobtained in 1982. Significant improvement in soil chemical properties with respect to 1982 was observed. Soilunder Eucalyptus showed lowest BD (1.59 Mg m-3) than fallow (1.62 Mg m-3) and both rice-wheat (1.64 Mgm-3) system. As gypsum was applied at surface soil, soil pHs (pH of soil saturation paste) remained alkaline indeeper soil layers. Surface soil of reclaimed R-W showed lower values of pHs (8.08) compared to fallow (8.14),Eucalyptus (8.17) and untreated R-W (8.54). Concentration of aqueous saturation paste extractable sodiumwas greater than Mg2+, Ca2+ and K+. Cl- and SO4

2- were two dominant anions in aqueous extract. An appreciablequantity of CO3

2- was found in land use of R-W farmer’s field. All land use showed a decrement in value insodium adsorption ration (SAR) along soil depth. SAR was positively correlated with pHs of saturation paste(R2=0.50). Therefore, these findings reiterated the effectiveness of gypsum for reclamation of sodic lands andalso Eucalyptus plantation proved to be the best agroforestry- based technology in tackling the vast sodic landsin Northwest India.

Key words: Land-use, Salt-affected soils, Sodium adsorption ratio, Eucalyptus, Gypsum, Agroforestry

Introduction

Salt-affected soils are impediments to agriculturalproduction. These soils include saline, sodic,saline-sodic and acid- sulfate soils. Among themsaline soils having high concentration of solublesalts, occupy approximately 3.1% (397 millionhectare) of the world’s land area (FAO, 1995).About 40-60% of world’s salt-affected lands aresaline and sodic in nature (Tanji, 1990). In India,saline and sodic soils account for approximately2.95 and 3.79 million hectares, respectively andtogether constituted 6.74 million ha area in India(CSSRI, 2015). Crop growth and productivity aregreatly affected by salinity and sodicity, resultingin annual losses of ` 230 billion in India alone(Sharma et al., 2015). By 2050 the losses are likelyto increase manifold with projected increase insalt-affected soils to 16.2 million ha. In India,

population is increasing but the net cultivable arearemains more or less constant. Therefore, to feedthis huge population of the country, salt-affectedsoils should be reclaimed and brought underproductive cultivation. Moreover, presentlyclimate change coupled with soil salinity/sodicitywill significantly affect the crop productivity inrainfed areas of dry semiarid regions.

One of the major drivers of several processesof environmental change is land use as itinfluences basic resources within the landscape,including the soil resources. Vast area of land canbe rapidly deteriorated due to poor soilmanagement, thereby often becoming a majorthreat to rural subsistence in many developing anddeveloped countries. Conversely, impact of landuse changes on soil can occur so unnoticed thatland managers hardly contemplate initiating


Land-use influences soil properties of sodic land 179

ameliorative measures (González et al., 2014). Forefficient remediation or reclamation of disturbedor damaged soils, knowledge and understandingof soil properties and processes are essential. Soilsprovide multiple ecosystem services, allowingsustained food and fibre production, anddelivering climate regulation, flood regulation,improved air and water quality, reducing soilerosion, and provide a reservoir for biodiversity(Smith et al., 2015).

All soils are subject to some degree of humandisturbance, either directly through land-use andland management, or indirectly through responsesto human-induced global change such as pollutionand climate change. Human impacts on soilslargely emerge from the need to meet the food,fibre, and fuel demands of a growing populationincluding an increase in meat consumption asdeveloping nations become wealthier, theproduction of biofuels, and increasing areas ofurbanization. Reclamation of salt-affected soilsthrough different means such as gypsumtechnology for sodic soil management, differenttolerant tree/crop species for saline soilrehabilitation etc. has also resulted changes in landuse. This has altogether led to conversion ofnatural degraded land to managed land(extensification) and intensification of agriculturaland other management practices on existing landsuch as increasing nutrient and water inputs andincreasing harvest frequency to increase yields perhectare.

The ICAR-CSSRI has been working onreclamation of salt affected soils since 1969 andis successful in keeping its foot print in the historyof agriculture production in India. In 1978, theinstitute had taken over the Gudha farm about 20km away from Karnal in Panipat district to set upits experiments. So many experiments wereconducted till 1992 and after that CSSRI had givenback the land to the Panchayat. Till 2007, the farmwas kept fallow and since 2008, rice-wheatcropping system has been followed by the farmersin those lands. Many reclamation technologieswere tested during that time and standardized forfarmers’ use. The effect of those technologies onsoil salinity parameters at present time in thoseareas is essential to understand what changes havebeen taken place during these times. Moreover,

area under salinity increased considerably in spiteof reclamation efforts resulting in about 20% ofsalt-affected irrigated land, so careful monitoringof the soil salinity is essential (Metternicht andZinck, 2003). Keeping all this in view, an attempthas been made to study the salinity parametersunder different existing land uses in Gudda farm,Panipat district of Haryana.


Physiography, climate and soil of study area

The Gudha farm is located in Panipat district ofHaryana (29°29′30′′ lat and 76°56′ long; about 237m above m sl). The research farm was constituteda part of the common village Panchayat landwhich was earlier used as a grazing land and hadgone out of cultivation due to the developmentof sodicity. The area represents a typical sub-tropical, semi-arid, monsoonic type of climatecharacterized by dry summer, hot rainy season,warm autumn and cool winter. More than 80%of the annual rainfall is received in 3 monsoonmonths of July, August and September. There isample sunshine throughout the year. The panevaporation exceeds the rainfall except in themonth of July and August.

The topography is almost flat. The farm areais surrounded by a network of canals and issituated in a local depression. The water tablefluctuates between 4-5 m and ground water is ofgood quality. The soil of Gudha farm typicallyrepresents large areas of sodic soils of the Indo-Gangetic alluvial plains. Based on the profile studyof the experimental plots the physicochemicalproperties are mentioned below. It is evident thatthe soil is characterized by excess of sodiumcarbonate, low calcium, high pH and presence ofhard calcareous pan in lower depths. The initialsoil chemical properties are presented in Table 1as adopted from Singh (1984).

Soil sample collection and analysis

Soils samples from four land uses were collectedwith auger from 0-20, 20-40, 40-60, 60-80, 80-100,100-120, 120-140, 140-160, 160-180 and 180-200cm depths (Fig. 1). The samples were air dried,ground and sieved by 2.0 mm sieve and kept inplastic container for analysis.

180 Datta et al.

Table 1. Soil chemical properties of the experimental plot before start of the experiment in July, 1982 (as adopted from Singh,1984)

Soil pH1:2 EC1:2 Cations and anions of soil saturation extract (me L-1) Sodium sodiumdepth (dS m-1) Na+ Ca2+ Mg2+ K+ CO3

2- HCO3- Cl- SO4

2- adsorption ratio of(cm) saturation extract

(SARe) mmol1/2 L-1/2

0-16 10.5 2.97 380.0 0.35 0.49 0.30 204.0 94.0 64.0 17.0 586.016-36 10.4 2.86 190.0 0.9 0.84 0.36 58.0 29.0 54.0 33.0 204.036-60 10.3 2.22 126.0 1.65 1.67 0.52 26.0 31.0 45.0 24.0 98.060-118 10.1 1.10 32.0 0.40 0.87 0.68 5.0 14.0 10.0 3.0 40.0118-156 10.1 0.81 22.0 0.20 0.27 0.76 2.0 14.0 3.0 1.0 45.0156-204 10.0 0.77 22.0 0.20 0.36 0.88 2.0 13.0 3.0 1.0 42.0204-218 9.8 0.75 21.0 0.18 0.32 0.70 1.0 12.0 4.0 2.0 42.0218-234 9.7 0.67 19.0 0.17 0.28 0.66 1.0 12.0 5.0 2.0 40.0234-264 9.7 0.60 17.0 0.17 0.26 0.59 - 12.0 4.0 2.0 37.0

Fig. 1. Sampling points in Gudha farm, Panipat, Haryana

Soil bulk density was measured by coremethod using 5 cm long and 5 cm internaldiameter metal cores by placing the core in themiddle of each soil layer (Black and Hartge, 1986)after harvest of wheat in 2017. Soil moisture wasdetermined by gravimetric method and volumetricwater content was calculated by multiplyinggravimetric water content with bulk density ofeach layer (Baruah and Barthakur, 1999). Soilporosity was also calculated by formula asmentioned by Baruah and Barthakur (1999). Thesoil pHs was determined in aqueous soil paste ofthe soil and water by using digital pH meter(USSL, 1954). For determination of electrical

conductivity of saturation extract (ECe), aqueousextract of saturated soil paste was readily removedfrom the soil paste with pressure or vacuum bypump. The reading of saturation extract wasdetected by dipping digital conductivity cell intoit (USSL, 1954). Sodium and potassiumconcentration were determined in soil saturationextract by flame photometer (USSL, 1954;Bhargava, 2003). Calcium and Magnesiumconcentration were estimated by EDTA-Versanate) method (Schwartzenbach et al., 1946).Carbonate and bicarbonate in saturation extractof soil were determined by titrating the sampleagainst standard acid. Chloride in saturation


extract of soil was determined by titrating theextract against silver nitrate solution usingpotassium chromate as indicator (USSL, 1954).Sulphate in saturation extract of soil was estimatedturbidimetric method (Chesnin and Yien, 1951).Sodium adsorption ratio (SARe) of soil saturationextract was calculated by following equation

where [ ] represents the concentration of cationin cmol(p+)L-1

note halving sum of [Ca2+] and [Mg2+] beforetaking square root


Physical properties of soil

Bulk density (BD) of soil ranged from 1.59 to 1.64Mg m-3, lowest was observed at 0-20 cm soil depthunder Eucalyptus (Table 2). Soil under Eucalyptusshowed lowest BD at surface soil which might bedue to higher leaf litter and bark accumulated atsurface soil thereby increased SOC at surface soil(Datta et al., 2015). BD increased with depth,highest (1.80 Mg m-3, at 20-40 cm) was observedunder fallow land which might be due tocompaction of soil. Soils under Eucalyptus alsoshowed higher gravimetric (0.22 and 0.22 g waterg-1 soil) and volumetric water (0.35 and 0.36 gcm-3) at both the soil layers than the other landuses (Table 2). Higher porosity (40%) was alsoobserved at surface soil under Eucalyptus land use.Higher porosity in soils under Eucalyptus resultedin higher gravimetric as well as volumetric watercontent at surface soil. Kisku et al. (2017) also

reported lower BD under in soil under plantationtrees compared to agrarian system.

Physico-chemical properties of soil

Soil pH1:2 and EC1:2

Land use types significantly influenced pH1:2 andEC1:2 irrespective of soil depth. Soil pH1:2 and EC1:2

significantly increased with depth in rice-wheatsystem of farmer’s field (Table 3). Soil pH1:2 rangedfrom 9.12 to 10.4, highest and lowest wereobserved at 140-160 and 0-20 cm soil depth,respectively. Soil pHs of saturation paste variedbetween 8.54 to 9.64, highest (9.64) and lowest(8.54) pHs were observed at 160-180 and 0-20 cmsoil depth, respectively. Highest EC1:2 (2.74 dSm-1) and ECe (3.05 dS m-1) were observed at 120-140 and 0-20 cm soil depth, respectively. UnderEucalyptus system, pH1:2 ranged from 8.74 to 9.58,lowest (8.74) and highest (9.58) were associatedwith 0-20 and 40-60 cm soil depth (Table 4). Herewith depth increment, pH1:2 and pHs increasedupto 60 cm and then decreased at lower depths.Lower pH1:2 were observed at lower depthscompared with middle layers pH1:2. Low pHs

(8.17) was observed at surface soil of 0-20 cm soildepth, ECe also showed similar trend with EC1:2.EC1:2 and ECe ranged from 0.99 to 1.58 and 2.34to 3.57 dS m-1. Soil pH1:2 and pHs ranged from8.49 to 9.27 and 8.14 to 8.74, respectively in fallowland (Table 5). Surface soil in fallow (0-20 cm)showed lowest pH1:2 and pHs (8.49, 8.14);, EC1:2

and ECe (0.77 and 2.0 dS m-1). Among the landuses, rice-wheat cropping system inside theexperimental farm showed lower pH1:2 and pHs

irrespective of soil depth (Table 6). Surface soilrice-wheat showed lowest soil pH1:2 (8.48) and pHs

Table 2. Soil physical properties under different land uses

Land uses/ Bulk density Gravimetric water Volumetric water Porositysoil depth (Mg m-3) (g water g-1 soil) (g cm-3) (%)(cm) 0-20 20-40 0-20 20-40 0-20 20-40 0-20 20-40

Eucalyptus 1.59b 1.73b 0.22a 0.21a 0.35a 0.36a 39.9 34.5R-W FF 1.64a 1.75b 0.10b 0.17ab 0.16c 0.30ab 38.2 34.1Fallow 1.62ab 1.80a 0.13b 0.14b 0.21c 0.25b 38.7 32.0R-W E 1.64a 1.74b 0.17ab 0.16ab 0.28b 0.27b 38.0 34.3

[Values followed by a similar lowercase letters within a column are not significantly different at p ≤ 0.05 (Duncan Multiple RangeTest); R-WFF: rice-wheat cropping system in farmers field outside the farm, R-W E: rice-wheat cropping system inside theexperimental farm]

182 Datta et al.

(8.08) and with increment in soil depth both soilpH1:2 and pHs increased significantly and reachedat highest at 180-200 cm soil depth pH1:2 (9.16 and8.61, respectively). Whereas, EC1:2 ranged from0.68 to 1.56 dS m-1, highest and lowest wereobserved at 160-180 and 80-100 cm soil depth,respectively. Soils are more affected by alkalinityrather than salinity in all the land uses. Similarlytype of soil reaction reported in salt-affected soilsof Mahendragarh district in Haryana (Basak etal., 2016).

Cations and anions of aqueous soil saturation extract

Sodium was the dominant among the analysedcations of soil saturation extract in all the land

uses irrespective of soil depth (Table 3). In rice-wheat system of farmers’ field, Na+ was lowest(28.2 meq L-1) at surface soil (0-20 cm) andconsequently increase along soil depth around 60me L-1). Rest of the extractable cations (K+

, Ca2+

and Mg2+) nearly remained at par. Carbonateconcentration increase with depth and highest andlowest (5.34 and 0.87 me L-1) was observed at 160-180 cm soil depth. Further, bicarbonateconcentration increased significantly with depthand highest (23.15 me L-1) was observed at 80-100 cm soil depth. Chloride concentration rangedfrom 11.75 to 19.05 me L-1, highest and lowestwere observed at 120-140 and 60-80 cm soil depth,respectively. Sulfate concentration was lowest at

Table 3. Soil chemical properties after harvesting of wheat under R-W cropping system outside the experimental farm in April, 2017

Depth pH1:2 pHs EC1:2 ECe Na+ K+ Ca2+ Mg2+ CO32- HCO3

- Cl- SO42- SARe

cm dS m-1 me L-1 mmol1/2

L-1/2

0-20 9.12c 8.54d 1.05d 3.05f 28.20c 0.08 3.75a 4.05c 0.87c 9.10a 14.15b 6.02b 14.52d20-40 9.91b 9.04c 1.85c 4.46e 47.10b 0.05 3.25a 4.75b 2.23b 8.75a 17.30a 14.55a 23.60c40-60 9.99b 9.25b 2.05bc 5.04d 43.68b 0.09 3.00a 3.75c 2.33b 13.75b 12.74b 15.06a 25.76c60-80 10.12a 9.37ab 2.33b 5.33c 50.77ab 0.08 3.75a 3.50 2.91b 15.50b 11.75b 18.07a 29.41c80-100 10.28a 9.60a 2.18b 5.76b 65.10a 0.07 3.25a 4.00c 3.34b 23.15a 13.95b 16.63a 35.24ab100-120 10.35a 9.58a 2.51ab 6.40a 69.08a 0.04 3.00a 3.25c 3.02b 20.90a 14.30b 17.40a 39.18a120-140 10.38a 9.62a 2.74a 6.41a 66.31a 0.04 3.50a 5.50a 2.96b 21.85a 19.05a 17.06a 32.29b140-160 10.40a 9.46a 2.36b 5.91b 60.33a 0.06 2.50ab 4.41bc 3.59b 19.30a 14.80b 17.04a 32.77b160-180 10.38a 9.64a 2.27b 5.03d 60.00a 0.03 3.23a 2.00d 5.34a 21.85a 13.50b 18.70a 38.34a180-200 10.38a 9.50a 1.83c 4.43e 61.25a 0.04 2.95b 2.50d 3.39b 18.50a 14.50b 19.55a 40.79a

[Means followed by a similar lowercase letters within a column are not significantly different at p ≤ 0.05 (Duncan Multiple RangeTest)]

Table 4. Soil chemical properties under Eucalyptus tereticornis system inside the experimental farm, April, 2017


- Cl- SO42- SARe


L-1/2

0-20 8.74c 8.17b 0.99b 2.70b 21.60c 0.07 1.38 2.30 0.94 8.44b 6.45b 10.10b 15.89c20-40 9.37ab 8.72a 1.29ab 3.28a 31.50b 0.29 1.25 1.70 0.99 13.26a 7.50ab 12.66b 27.21ab40-60 9.58a 8.84a 1.32ab 3.47a 38.95a 0.25 1.48 2.25 1.21 12.85a 9.54a 10.78b 31.56a60-80 9.50a 8.76a 1.58a 3.57a 41.05a 0.09 2.05 1.45 1.51 15.10a 10.70a 12.76b 33.28a80-100 9.45a 8.82a 1.12b 2.79b 35.50ab 0.12 1.13 1.62 1.19 14.12a 9.00a 13.10b 34.78a100-120 9.43a 8.74a 1.22b 2.34b 38.70a 0.12 1.75 2.38 1.54 13.45a 5.00b 14.68b 26.86ab120-140 9.36ab 8.62a 1.11b 2.69b 40.05a 0.20 1.25 2.75 1.33 12.30a 5.94b 17.33ab 28.50ab140-160 9.0b 8.38 1.10b 3.42a 33.20ab 0.08 1.50 2.88 1.93 11.31a 5.00b 13.15b 22.18b160-180 9.15b 8.47ab 1.32ab 3.29a 38.25a 0.09 0.88 2.23 1.98 6.74b 6.02b 20.31a 30.66a180-200 9.05b 8.52ab 1.31ab 2.74b 34.90ab 0.09 1.00 2.77 1.97 7.19b 5.55b 19.54a 25.32ab



surface (6.02 meq L-1) and increased along soildepth. With depth increment, SARe increasedsignificantly and highest (40.8) was observed at180-200 cm soil depth. Lowest SARe (14.52) wasobserved at 0-20 cm soil depth. This findingclaimed an increment of alkalinity along depth.Basak et al. (2017) showed similarly increment inSARe along soil depth (0-120 cm) in salt-affectedsoil.

Irrespective of soil depth Na+ concentrationin soil saturation extract ranged from 21.6 to 41.05me L-1 and lowest was observed at surface layer(21.6 meq L-1) (Table 4). Others cations (K+, Ca2+

and Mg2+) and anion CO32- were at par.

Concentration of HCO3- varied from 6.74 to 15.1

me L-1. At 0-20 cm soil depth, Cl- concentrationwas 6.45 me L-1 and increased upto 60-80 cm andthen decreased at lower soil depths. Sulfateconcentration increased with depth and highest(20.31 me L-1) was observed at 160-180 cm depth.Lowest SARe (15.9) was observed at 0-20 cm soildepth in soil under Eucalyptus. SAR increasedwith depth upto 100 cm soil depth and thendecreased at lower depths. Highest SAR (34.8) wasobserved at 80-100 cm depth. Under fallow landNa+ concentration ranged from 21.05 to 30.97 meL-1, highest (30.97 me L-1) and lowest (21.05 meL-1) were associated with 100-120 and 0-20 cm soildepth (Table 5). Concentration of Mg2+ (1.45-2.88me L-1) was dominant over Ca2+ (0.88-2.05 meL-1) irrespective of soil depth. Surface soil showed

a lower value of CO32- (0.67 me L-1) and HCO3

-

(5.8 me L-1). HCO3- concentration increased along

depth upto 120-140 cm of soil depth (12.3 meL-1). Irrespective of soil depth sulfateconcentration ranged from 7.47 to 11.11 me L-1.SARe varied from 16.95 to 28.9, and lowest valueof soil SARe observed at surface soil (16.95).Cations and anions concentration of thesaturation extracts of soils under rice-wheatcropping system inside the experimental farm ispresented in Table 6. Na+ concentration rangedfrom 18.26 to 49.8 me L-1; highest and lowest wereobserved at 180-200 and 60-80 cm soil depth. Soilsat lower depths showed higher Na+ concentrationcompared to upper soil depths. Whereas, othercations (K+, Ca2+ and Mg2+) and CO3

2- were lowerin range. Contrarily, HCO3

- (5.5 to 13.65 me L-1),Cl- (8.70 to 16.54 me L-1) and SO4

2- (6.8 to 10.54me L-1) were greater range. Soil SARe was greaterat deep layer (31.5 to 36.5; 120 to 200 cm)compared to 80-120 cm of soil depth (12.87 to15.57) (Table 6).

Correlation study

Soil pHs showed a positive and significantcoefficient of determination with SARe (R2 =0.50,p<0.05) (Fig. 2) which might be due to pedogenicproperties (Chhabra, 2004; Pal et al., 2003). SoilpHs and CO3

2- concentration of saturation extractwas also significantly and positively related witheach other (R2=0.57, p< 0.05) (Fig. 3). Soluble

Table 5. Soil chemical properties under fallow inside the experimental farm, April, 2017


- Cl- SO42- SARe


L-1/2

0-20 8.49b 8.14b 0.77b 2.00b 21.05b 0.07 1.38ab 1.67b 0.67b 5.80c 7.85c 8.98bc 16.95c

20-40 8.98ab 8.42ab 0.89ab 2.15b 27.15ab 0.29 1.25ab 1.63b 0.96b 6.07c 8.69b 11.11a 24.59b

40-60 9.16a 8.56a 0.85ab 2.03b 30.45a 0.25 0.94b 1.71b 1.20a 5.93c 11.17a 7.47c 28.90a

60-80 9.29a 8.70a 1.02a 2.15b 28.90a 0.09 2.05a 1.45b 1.33a 7.20b 10.84a 10.41ab 24.99b

80-100 9.26a 8.63a 1.09a 2.49a 27.15ab 0.12 1.13ab 1.63b 1.38a 7.19b 8.87b 8.64bc 26.92ab

100-120 9.19a 8.53a 1.01a 2.74a 30.97a 0.12 1.75ab 2.38a 1.46a 8.00ab 11.27a 9.79b 21.97b

120-140 9.16a 8.67a 1.07a 2.64a 29.25a 0.20 1.25ab 2.25a 1.53a 8.40ab 7.92c 10.53ab 22.11b

140-160 9.14a 8.74a 0.95a 2.77a 28.15a 0.08 1.50ab 2.88a 1.55a 9.63a 9.96ab 9.23b 19.48bc

160-180 9.16a 8.59a 1.00a 2.64a 28.20a 0.09 0.88b 2.25a 1.45a 8.93ab 10.98a 8.33bc 22.89b

180-200 9.12a 8.60a 0.99a 2.66a 26.50ab 0.09 1.00b 2.02a 1.39a 8.18ab 10.94a 9.24b 24.51b


184 Datta et al.

Table 6. Soil chemical properties after harvesting of wheat under R-W cropping system inside the experimental farm in April, 2017


- Cl- SO42- SARe


L-1/2

0-20 8.48d 8.08c 1.04ab 2.81d 24.02d 0.27c 1.25ab 2.75ab 0.15c 6.97b 12.34c 6.87b 16.99b20-40 8.50d 8.13bc 0.92b 3.02c 23.91d 0.72b 0.75b 2.50ab 0.20c 5.50b 15.64b 6.87b 18.76b40-60 8.54d 8.16bc 0.82b 3.13c 25.54d 1.57a 1.25ab 2.50ab 0.34c 6.50b 16.54b 9.87ab 18.65b60-80 8.60cd 8.22bc 0.79b 3.14c 18.26e 0.94ab 0.50c 2.25ab 0.45c 7.20b 8.70d 6.80b 15.57b80-100 8.67cd 8.29b 0.68c 2.33d 19.30e 0.06d 0.75b 3.75a 0.54c 6.36b 9.87d 6.98b 12.87b100-120 8.73cd 8.30b 0.73bc 2.25d 18.59e 1.09ab 0.75b 3.00a 0.65c 6.61b 12.30c 7.41b 13.57b120-140 8.80c 8.32b 1.22ab 3.74b 34.24c 0.36c 0.50c 1.75b 0.87b 6.87b 11.00cd 8.65b 32.28a140-160 9.00b 8.37b 1.32ab 3.78b 46.52ab 0.52bc 1.25ab 2.00b 1.91a 13.40a 19.34a 10.54a 36.49a160-180 9.14a 8.55a 1.56a 4.54a 40.33b 0.25c 1.50a 1.00b 0.98b 12.36a 16.00b 7.89b 36.07a180-200 9.16a 8.61a 1.45a 4.52a 49.78a 0.22c 1.50a 3.50a 0.80b 13.65a 16.00b 6.98b 31.49a


Fig. 2. Relationship between soil pHs and SAR

Fig. 3. Relationship between soil pHs and CO32-

Fig. 4. Relationship between soil saturation extractable pHs andNa+

sodium showed a positive and significant relationwith pH1:2 (R2 =0.69, p≤ 0.05) (Fig. 4). Similar typeof relation also indicated by Basak et al. (2015)between pH and SAReq (equilibrium solution)solution at various salinity levels in different salt-affected soils. ECe also showed positive andsignificant coefficient of determination withsodium (R2 =0.65, p< 0.05) (Fig. 5). Ca2+ andMg2+ were the dominant cations after Na+ in thesesoils. There is significant decrease in soil pH fromthe 1982 which was possible only because ofgypsum application technology. Sodiumconcentration in saturation extract wassignificantly reduced and thereby decreased SARe

drastically (Chhabra, 1996).


Conclusions

Reclamation with gypsum followed by cultivationand perturbation has immense influence on soilphysical and chemical properties. Soil underEucalyptus plantation showed lower bulk density,higher gravimetric and volumetric water contentand porosity. Intervention with gypsumtechnology and cultivation decreased soil pH andsoil sodicity (sodium adsorption ratio). Soils atdeep layers still showed alkalinity as amendment(gypsum in this case) was applied at surface soil.Soil profile study needs to be done under differentland uses in Gudha farm to know the changes inother soil pedogenic properties.

Acknowledgements

The current study is a part of research program“NRMACSSRISIL201400100859: Effect of landuses on salt distribution and properties of saltaffected soils” during 2014-2017. The authorsthank to the Head, Division of Soil and CropManagement and Director, Central Soil SalinityResearch Institute, Karnal, Haryana, India, forfinancing this work. Thanks to Mr. Kartar Singh,Laboratory Technician for assistance in lab work.

References

Baruah TC, Barthakur HP (1999) A Text Book of Soil Analysis.Vikas Publishing Houses Pvt, Ltd., New Delhi.

Basak N, Chaudhari SK and Sharma DK (2015) Influenceof water quality on exchange phase-solution phase

behavior of texturally different salt-affected soils. Journalof the Indian Society of Soil Science 63(4): 365-372. DOI:10.5958/0974-0228.2015.00048.1

Basak N, Gobinath R, Rai, AK, Sundha P, Yadav RK,Narjary B, Gajender, Kumar S and Sharma DK (2017)Deficit saline water irrigation and mulch affect root zonesalinity and micronutrient availability in salt-affectedsoil. Paper in National Seminar on “Nutrients andPollutants in Soil-Plant-Animal-Human Continuum forSustaining Soil, Food and Nutritional Security – WayForward” June 9-10, 2017, Lake Hall, Bidhan ChandraKrishi Viswavidyalaya , Kalyani.

Basak N, Sethi M, Datta A, Yadav AK, ChinchmalatpureAR, Khurana ML and Barman A (2016) Distributionand characteristics of salt-affected soils ofMahendragarh District in Haryana. Journal of SoilSalinity and Water Quality 8(2): 153-16.

Bhargava GP (2003) Training manual for undertaking studieson genesis of sodic/ alkali soils, Karnal, p 111.

Blake GR and Hartge KH (1986) Bulk density. In: Klute A(ed) Methods of Soil Analysis: Part 1—Physical andMineralogical Methods. SSSA Book Ser. 5.1. ASA andSSSA, Madison: Wisconsin; pp 363-375.


Chhabra R (1996) Soil Salinity and Water Quality. Oxford &IBH Publications, New Delhi. p 284.

Chhabra R (2004) Classification of salt-affected soils. AridLand Res. Manage. 19(1): 61-79. DOI: 10.1080/15324980590887344.

Datta A, Basak N, Chaudhari SK and Sharma DK (2015)Soil properties and organic carbon distribution underdifferent land uses in reclaimed sodic soils of North-West India. Geoderma Reg. 4: 134–146.

FAO (1995) Global network on integrated soil managementfor sustainable use of salt affected soils. FAO Land andPlant Nutrition Managment Service, Rome, Italy.

González, AP, de Abreu CA, Tarquis AM and Medina-Roldán E (2014) Impacts of land use changes on soilproperties and processes. The Scientific World J. ArticleID 831975. (http://dx.doi.org/10.1155/2014/831975)

Kisku TK, Datta A, Basak N, Mandi S, Hembram S andRoy R (2017) Evaluation of saturated hydraulicconductivity from soil properties in an Inceptisol usingdifferent land cover and depths. Journal of Applied andNatural Science 9 (3): 1482 -1488.

Metternicht GI and Zinck JA (2003) Remote sensing of soilsalinity: Potentials and constraints. Remote Sensing ofEnvironment 85: 1–20.

Minhas PS and Gupta RK (1992) Quality of Irrigation Water:Assessment and Management. ICAR, New Delhi, India,pp 123–124.

Fig. 5 Relationship between soil saturation extractable ECe andNa+

186 Datta et al.

Pal DK, Srivastava P, and Durge SL and Bhattacharyya T(2003) Role of microtopography in the formation ofsodic soils in the semi-arid part of the Indo-GangeticPlains, India. Catena 51: 3–31.

Schwartzenbach G, Biedermann W and Bangerter F (1946)Komplexone VI. Meueeinfache titrimethodenzurbestimmung der wesserharte. Helvetica Chimica Acta. 29:811-818.

Sharma DK, Thimmppa K, Chinchmalatpure AR, Mandal,AK, Yadav RK, Chaudhari SK, Kumar S and Sikka AK(2015) Assessment of Production and Monetary Losses fromSalt-affected Soils in India. Technical Bulletin: ICAR-CSSRI/Karnal/2015/05. ICAR-Central Soil SalinityResearch Institute, Karnal, India.

Singh S (1984) Studies on rain water conservation for theestablishment of an agroforestry system on sodic soil.Ph.D. Thesis, Kurukshetra University, Kurukshetra,Haryana, India.

Smith P, House JI, Bustamante M, Sobocká J, Harper R,Pan G, West PC, Clark JM, Adhya T, Rumpel C,Paustian K, Kuikman P, Cotrufo MF, Elliott JA,McDowell R, Griffiths RI, Asakawa S, Bondeau A,Jain AK, Meersmans J and Pugh TAM (2016) Globalchange pressures on soils from land use andmanagement. Glob. Change Biol. 22: 1008–1028.doi:10.1111/gcb.13068

Tanji KK (1990) The nature and extent of agricultural salinityproblems. In: Tanji, KK (ed) Agricultural SalinityAssessment and Management Engineering Practice No. 71.American Society of Civil Engineers, New York, pp 1-17.

USSL (1954) In: Richards LA (ed) Diagnosis and Improvementof Saline and Alkali Soils. USDA Handbook, Washington,DC, pp 60.

Received in April, 2017; Accepted in June, 2017

Relative Efficiency of Amendments for Reclamation ofSodic Vertisols and their Effects on Crop Production

UR Khandkar1, SC Tiwari1, RK Sharma1, SK Verma2, RL Meena3

and MJ Kaledhonkar3

AICRP on Management of Salt Affected Soils and Use of Saline Water in Agriculture1College of Agriculture, Indore, Madhya Pradesh

2Depatment of Soil Science & Agricultural ChemistryRajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior, Madhya Pradesh

3ICAR-Central Soil Salinity Research Institute, Karnal, Haryana*Corresponding author E-mail: [email protected]

Abstract

Reclamation of sodic Vertisols for crop production is of prime importance in view of the ever-increasing demandof food and other commodities. Among the amendments gypsum is the cheapest and most convenient sourceused for reclamation of sodic soils but now availability of mined gypsum is very limited. Distillery spent wash(DSW) may be used as an alternate to gypsum as it contains huge amount of calcium and magnesium and highorganic carbon. The present investigation was undertaken to compare the effect of DSW, gypsum, vermi-compost and FYM in sodic Vertisols under rice-wheat cropping system. The plant height, effective tillers,length of penicle/ ear head, and grain and straw yield of paddy and wheat increased significantly over controlwith the application of spent wash @ 0.5 million L ha-1. The application of spent wash @ 0.5 million L ha-1

increased the grain yield of paddy by 43.8 and 39.7 and wheat by 44.7 and 85.2 percent over control during2007-08 and 2008-09, respectively. The uptake of Ca, Mg and K was increased while Na uptake was reduced inrice and wheat because of DSW application. The ESP of the soil was reduced from initial 38.8 to 17.1 after twoyears of DSW application. Organic carbon, available nitrogen and potassium status was also improved withthe application of 0.5 million L ha-1 spent wash.

Key words: Sodic Vertisols, Amendments, Distillery spent wash, Reclamation, Paddy and wheat yield

Introduction

In India, salt-affected soils occur in an area ofabout 6.73 million ha (Mandal et al., 2010). Outof which 24.2 thousand ha is found in MadhyaPradesh (Sharma, 1996). The reclamation andutilization of sodic soils are of prime importancein view of ever increasing population pressure onavailable resources. Among the amendments,gypsum is the cheapest and most convenientsource for reclamation of sodic soils, but now-a-days the availability of mined gypsum is limitinghence, there is a need to find out an alternativesource as an amendment for reclamation of sodicsoils. The distillery spent wash (a distilleryeffluent) is an organic material which is highlyacidic in reaction and contains Ca, Mg, K and Sin sufficient amount and may be a betterproposition for reclamation of sodic soils. Safe

disposal of the DSW is a challenge for thedistilleries. Its disposal in water bodies may posethreat to aquatic life. Presence of the high Ca andMg and having acidic reaction provides anopportunity for application of the DSW as anamendment in sodic soils. Sindhu et al. (2007)reported that the high concentration of Ca andMg in spent wash may have potential in reclaimingthe sodic soils. In view of above facts, the presentinvestigation was under taken to study the relativeefficiency of DSW, vermi-compost and FYM inreclamation of sodic Vertisols and their effects oncrop production.


A field experiment was conducted during kharifand rabi seasons of 2007-08 and 2008-09 at SalinityResearch Staion, Barwaha, District Khargone


188 Khandkar et al.

(MP). The experimental soil belonged to finesmectitic hyperthermic Typic Heplusterts-sodicphase, having pHs 8.40 and ECe 1.4 dS m-1. TheCEC and ESP of soil were 38.8 cmol(p+) kg-1 and38.80, respectively. The characteristics of DSWprocured from M/s Associated Alcohol andBreweries, Village Dodi, Tehsil, Barwaha, DistrictKhargone, (MP), vermicompost and FYM aregiven in the Table 1.

The treatments comprised of control, FYM(5 Mg ha-1), vermi compost (5 Mg ha-1), gypsum(75% of GR), gypsum (75% of GR) + FYM (5Mg ha-1), gypsum (75% of GR) + vermi compost(5 Mg ha-1), spent wash (0.25, 0.5 and 1.0 millionL ha-1) were applied in randomized block designwith three replications. The treatments wereapplied 30 days prior to transplanting of paddyseedlings, once in a year under paddy-wheatcropping sequence for reclamation of sodic soils.The FYM, vermi compost and gypsum weremixed in 15 cm soil depth. Twenty-five days oldseedlings of paddy (cv. Kranti) raised separatelyon sodic Vertisols, were transplanted. The wheatcrop (cv.GW-173) was sown during rabi season inthe same plots. Recommended doses of nutrientswere given as per the recommendations for sodicsoils. The plant materials (grain and straw)collected at harvest of respective crops and ovendried at 55ºC, grinded in Wiley mill and digestedin di-acid mixture for analysis of Ca, Mg, Na andK. Total K and Na were determined by flamephotometer. Ca and Mg were analyzed byversenate titration method. The agronomicalparameters were computed on plant samples atharvest of both the crops. Soil samples werecollected at the harvest of wheat crop. The soilsamples were analyzed for organic carbon(Walkley and Black, 1934), available N (Subbaihand Asija, 1956), available P (Olsen et al.1954),

available K (Neutral normal ammonium acetate),pHs, ECe and ESP (Richards, 1954).


Effect of amendments on crop growth and yieldattributes

Application of amendments in the soilsignificantly enhanced the growth and yield ofpaddy over control (Table 2). The plant height,number of tillers, length of panicle and grain andstraw yield of paddy varied significantly withdifferent amendments. The plant height, numberof tillers, length of panicle, grain and straw yieldof paddy increased significantly with theapplication of gypsum @ of 75% GR over control.Whereas, addition of gypsum application @ 75%GR was not found superior over spent wash @5.0 lakh L ha-1 during both the years. Theapplication of gypsum in combination withFYM/ vermi-compost @ 5 Mg ha-1 also increasedthe values of all the parameters but it wasstatistically at par with application of gypsum @of 75% GR. Application of 5.0 lakh L ha-1 spentwash increased the plant height, number of tillersand length of panicle by 18.1 & 15.2, 65.7 & 61.5and 26.7 & 28.6% over control during 2007-08and 2008-09 respectively. Further increase in thespent wash application showed non-significanteffect on plant growth. The improvement ingrowth parameters of rice might be due to theameliorating effect which led to increased supplyof nutrients and enhanced metabolic activity. Thehighest grain yield (5.78 and 5.02 Mg ha-1) andstraw (6.55 and 5.92 Mg ha-1) was recorded in 10.0lakh L ha-1 spent wash level but it was statisticallyat par with 5.0 lakh L ha-1. The application of 5.0lakh Lha-1 spent wash enhanced the grain yieldby 43.7 and 42.2 and straw yield by 39.7 and 44.3per cent, over control during 2007-08 and 2008-

Table 1. Composition of distillery spent wash (DSW), vermi-compost and FYM used as an amendment

pH* ECe BOD COD Composition**(dS m-1) (mg L-1) (mg L-1) Ca Mg K S N Na

DSW 4.98 9.42 4110 20660 1522 880 8675 1150 990 380Vermi-compost 8.5 3.8 - - 0.78 0.38 1.10 0.55FYM 8.1 1.8 - - 0.45 0.15 0.63 0.20

*pH -1:4 Vermicompost/FYM: water ratio, ** in DSW (mg L-1), in Vermi-compost and FYM (%)

Amendments for reclamation of sodic vertisols 189

Table 2. Growth characters and yield of paddy under different amendments

Treatments Plant height Effective Length of Yield (Mg ha-1)(cm) tillers/ hill panicle (cm) Grain Straw

Year 2007-08Control 75.1 7.00 18.46 4.00 4.50FYM (5 Mg ha-1) 77.0 7.73 19.06 4.55 5.10Vermi Compost (5 Mg ha-1) 77.8 7.93 19.80 4.67 5.23Gypsum (75% GR) 80.2 9.13 20.66 4.93 5.63Gypsum (75% GR)+FYM (5 Mg ha-1) 82.6 9.60 20.93 5.13 5.83Gypsum (75% GR)+VC (5 Mg ha-1) 83.4 9.86 21.20 5.42 5.92SW (0. 25 million L ha-1) 83.6 10.00 21.60 5.43 6.05SW (0.5 million L ha-1) 88.7 11.60 23.40 5.75 6.40SW (1.0 million L ha-1) 92.3 11.80 23.53 5.78 6.55LSD (p≤0.05) 4.0 0.69 1.23 0.31 0.33


09 respectively. The beneficial effect of spent washon soil and yield of rice have been reported byPathak et al. (1999) and Bhaskar et al. (2003).

The plant height, number of effective tillersper plant and length of ear head and yield of wheatalso varied significantly with the application ofdifferent amendments (Table 3). Application ofgypsum @ 75% GR significantly increased theplant height, number of effective tillers per plant,length of ear head and grain and straw yield ofwheat over control in both the years. However, itwas statistically not superior to addition of spentwash @ 0.5 million L ha-1. Application of 0.5million L ha-1 spent wash increased the plantheight by 25.4 and 38.0%, number of effectivetillers per plant by 57.0 and 45.5% and length ofear head by 37.1 and 42.0% over control during2007-08 and 2008-09, respectively. Furtherincrease in spent wash application showed nosignificant effect. Improvement in growthcharacters of wheat because of the application ofspent wash was also reported by Sukanya and Meli(2004). The highest grain (4.35 and 4.17 Mg ha-1)

and straw (4.97 and 4.47 Mg ha-1) was noticed in1.0 million L ha-1 spent wash which was at parwith 0.5 million L ha-1 spent wash level.Application of 0.5 million L ha-1 spent washincreased the grain yield by 44.8 and 61.7 percentand straw yield by 85.2 and 89.9 percent, overcontrol during 2007-08 and 2008-09, respectively.The increment in yield of wheat with theapplication of spent wash was also reported byPathak et al. (1999), Bhaskar et al. (2003) andSukanya and Meli (2004).

Effect on nutrients uptake

Uptake of Ca, Mg and K by grain and straw ofboth the crops increased significantly with theapplication of different amendments as comparedto control (Tables 4 and 5). The uptake of Ca, Mgand K by paddy was increased significantly withthe application of gypsum @ 75% GR over controlduring both the years, whereas, it was statisticallyat par with the addition of gypsum in combinationwith FYM @ 5 Mg ha-1. The addition of spentwash @ 0.5 million L ha-1 was significantlysuperior to gypsum addition @ 75% GR. The

190 Khandkar et al.

Table 3. Growth characters and yield of wheat as affected by amendments

Treatments Plant height Effective tillers Length of Yield (Mg ha-1)(cm) per plant ear head (cm) Grain Straw


Year 2008-09Control 47.3 5.27 5.07 2.17 2.29FYM (0.5 Mg ha-1) 48.7 5.40 5.20 2.27 2.44Vermi Compost (0.5 Mg ha-1) 50.0 5.60 5.40 2.33 2.54Gypsum (75% GR) 56.2 6.40 5.53 3.00 3.35Gypsum (75% GR)+FYM (5Mg ha-1) 57.6 6.73 5.80 3.40 3.49Gypsum (75% GR)+VC (5 Mg ha-1) 59.3 6.80 6.00 3.47 3.55SW (0. 25 million L ha-1) 62.0 6.87 6.60 3.52 3.85SW (0.5 million L ha-1) 65.3 7.67 7.20 4.02 4.35SW (1.0 million L ha-1) 66.0 7.93 7.33 4.17 4.47LSD (p≤0.05) 3.23 0.71 0.49 0.48 0.40

Table 4. Nutrient uptake (kg ha-1) by paddy as affected by amendments

Treatments Grain StrawCa Mg Na K Ca Mg Na K

2007-08Control 12.6 5.5 30.3 18.1 9.8 7.8 32.4 44.5FYM (5 Mg ha-1) 15.6 7.9 29.6 21.5 12.2 9.8 32.3 53.6Vermi Compost (5 Mg ha-1) 17.7 8.4 28.8 23.3 14.6 11.5 31.1 56.5Gypsum (75% GR) 22.3 11.9 27.2 27.3 18.6 14.6 28.1 68.7Gypsum (75% GR)+FYM (5 Mg ha-1) 23.8 14.0 26.7 29.7 20.5 16.2 26.7 74.6Gypsum (75% GR)+VC (5 Mg ha-1) 27.4 15.9 26.0 32.5 22.4 17.6 25.6 79.3SW (0. 25 million L ha-1) 30.5 17.1 25.7 35.5 22.9 18.9 24.2 81.8SW (0.5 million L ha-1) 38.3 21.5 23.0 42.1 28.9 23.8 21.1 90.9SW (1.0 million L ha-1) 40.1 21.5 20.8 43.5 31.4 24.8 19.8 96.5LSD (p≤0.05) 6.5 3.5 3.6 2.8 3.9 4.1 4.1 6.2

2008-09Control 10.6 5.1 22.5 14.6 7.6 5.3 27.0 33.7FYM (5 t ha-1) 12.3 6.5 21.7 16.0 8.2 6.8 26.7 36.8Vermi Compost (5 t ha-1) 13.8 7.3 21.5 17.3 9.9 8.2 26.3 38.9Gypsum (75% GR) 16.6 10.2 20.9 21.6 13.2 10.3 26.0 49.3Gypsum (75% GR)+FYM (5 Mg ha-1) 19.7 11.1 20.5 24.2 14.9 11.6 25.8 54.5Gypsum (75% GR)+VC (5 Mg ha-1) 21.2 11.6 20.0 25.8 15.8 12.8 25.6 56.9SW (0. 25 million L ha-1) 23.4 13.2 19.6 28.0 18.2 14.7 24.0 60.9SW (0.5 million L ha-1) 30.7 17.5 19.1 33.6 22.8 18.2 23.6 71.4SW (1.0 million L ha-1) 32.8 19.4 18.2 36.1 25.3 20.9 22.5 76.9LSD (p≤0.05) 4.5 2.2 NS 2.7 2.9 2.2 NS 6.6


Table 5. Nutrient uptake (kg ha-1) by wheat as affected by amendments

Treatments Grain StrawCa Mg Na K Ca Mg Na K

2007-08Control 8.3 5.1 17.5 14.1 7.0 4.7 29.1 27.7FYM (5 Mg ha-1) 8.9 5.5 16.4 15.8 7.9 5.9 27.0 29.8Vermi Compost (5 Mg ha-1) 10.3 7.0 15.9 17.9 9.3 6.9 26.4 32.4Gypsum (75% GR) 13.3 10.4 14.7 22.1 12.7 9.6 25.5 38.7Gypsum (75% GR)+FYM (5 Mg ha-1) 14.6 11.7 14.5 23.8 14.6 10.7 24.8 41.3Gypsum (75% GR)+VC (5 Mg ha-1) 15.6 12.6 14.1 25.3 15.8 12.3 24.3 44.5SW (0. 25 million L ha-1) 18.7 13.7 14.0 27.2 17.7 13.0 23.6 48.7SW (0.5 million L ha-1) 23.9 17.6 11.9 32.1 24.9 16.5 19.4 56.9SW (1.0 million L ha-1) 25.2 19.1 11.3 33.6 25.8 16.8 18.8 60.2LSD (p≤0.05) 3.2 1.7 2.1 3.3 2.9 2.4 3.5 2.7

2008-09Control 6.5 3.5 16.1 9.1 5.9 2.8 26.5 16.6FYM (5 Mg ha-1) 7.4 4.3 15.2 10.2 6.8 3.4 25.6 18.4Vermi Compost (5 Mg ha-1) 8.2 5.1 14.7 11.7 8.2 4.4 25.2 20.1Gypsum (75% GR) 14.4 9.0 14.3 17.4 12.5 8.1 25.0 28.8Gypsum (75% GR)+FYM (5 Mg ha-1) 17.5 10.7 14.1 21.8 13.9 9.1 24.5 31.4Gypsum (75% GR)+VC (5 Mg ha-1) 19.4 11.6 14.0 23.3 14.9 10.4 24.2 33.9SW (0. 25 million L ha-1) 20.3 13.2 13.7 25.4 18.2 11.3 23.6 37.7SW (0.5 million L ha-1) 26.5 16.9 13.4 33.5 22.6 14.8 22.9 45.2SW (1.0 million L ha-1) 29.1 18.9 12.5 36.4 24.7 16.7 21.9 48.6LSD (p≤0.05) 2.5 2.5 NS 3.1 2.1 1.8 NS 4.6

uptake of Na by grain and straw was found todecrease with application of differentamendments as compared to control. The lowestuptake of Na by grain (20.8 and 8.2 kg ha-1) andstraw (19.8 and 22.5 kg ha-1) was recorded with1.0 million L ha-1 spent wash during 2007-08 and2008-09, respectively. Na uptake was decreasedby 24.1 and 34.9 percent in grain and 15.1 and12.6 percent straw with 5.0 lakh L ha-1 spent washapplication over control during 2007-08 and 2008-09, respectively. Improvement in uptake of Ca andMg and K by grain and straw of paddy with theapplication of spent wash might be due to thehigher content of these nutrients in spent wash aswell as the ameliorating effect of spent wash. Daset al. (2010) also reported significant increase inCa, Mg and K uptake by paddy with increasinglevels of spent wash application. Similar trend wasalso observed for uptake of different nutrient inwheat crop for different treatments (Table 5).Enhancement in uptake of Ca and Mg and K bygrain and straw of wheat with the addition ofspent wash could be due to ameliorating effect ofspent wash and it also contained higher amount

of these nutrients. Findings were in agreementwith those reported by Swami (2012).

Effect on soil properties

Addition of different amendments to the soilsignificantly increased organic carbon, availableN and K contents over control, while decreasedthe soil ECe and ESP after harvest of wheat crop(Table 6).

Addition of gypsum in combination withVermi-compost significantly improved the organiccarbon content of soil over control during boththe years. The highest organic carbon content(0.72 and 0.77%) was recorded with 1.0 million Lha-1 spent wash application but it did not differsignificantly with 0.5 million L ha-1 spent wash(0.73%). Significant improvement in organiccarbon content of soil could be ascribed to theaddition of organic matter through spent washapplication. Similar effect was also observed byMurugaragavan (2002). The highest available N(224 and 207 kg ha-1) and K (460 and 447 kg ha-1)contents in the soil were recorded with the

192 Khandkar et al.

Table 6. Effect of amendments on soil properties after the harvest of wheat

Treatments OC Available Nutrients (kg ha-1) pHs ECe ESP(%) N P K (dS m-1)

2007-08Control 0.40 174.0 7.7 314 8.3 1.36 36.0FYM (5 Mg ha-1) 0.44 177.3 8.0 322 8.1 1.30 35.5Vermi Compost (5 Mg ha-1) 0.45 180.1 8.5 328 8.1 1.25 34.4Gypsum (75% GR) 0.44 183.8 9.1 341 8.1 1.22 23.0Gypsum (75% GR)+FYM (5 Mg ha-1) 0.46 184.8 9.6 348 8.0 1.20 22.0Gypsum (75% GR)+VC (5 Mg ha-1) 0.52 187.6 10.1 356 8.0 1.18 21.3SW (0. 25 million L ha-1) 0.59 197.8 10.1 412 8.0 1.16 19.4SW (0.5 million L ha-1) 0.69 217.4 11.2 438 8.0 1.15 17.8SW (1.0 million L ha-1) 0.72 224.0 11.6 460 8.0 1.15 17.2LSD (p≤0.05) 0.09 8.23 NS 34 NS 0.11 1.39

2008-09Control 0.37 178.0 8.1 328 8.13 1.29 35.4FYM (5 Mg ha-1) 0.46 186.7 9.0 335 8.10 1.28 34.6Vermi Compost (5 t ha-1) 0.47 188.3 9.2 339 8.10 1.26 34.2Gypsum (75% GR) 0.46 185.7 9.3 353 8.10 1.24 24.5Gypsum (75% GR)+FYM (5 Mg ha-1) 0.52 189.7 9.9 361 8.10 1.22 23.5Gypsum (75% GR)+VC (5 Mg ha-1) 0.54 192.3 9.9 373 8.10 1.22 21.9SW (0. 25 million L ha-1) 0.62 194.0 10.0 383 8.10 1.20 19.7SW (0.5 million L ha-1) 0.73 202.7 11.7 421 8.10 1.20 17.1SW (1.0 million L ha-1) 0.77 207.3 11.7 447 8.10 1.18 17.0LSD (p≤0.05) 0.05 6.2 NS 35 NS 0.05 1.6

application of 10 lakh L ha-1 spent wash during2007-08 and 2008-09, respectively. Applicationof amendments did not affect the available P statusof soil after harvest of wheat during both the years.Application of amendments significantlydecreased the ECe and ESP of soil after harvestof wheat. The lowest ECe (1.15 and 1.18 dS m-1)and ESP (17.2 and 17.0) were noticed when 1.0million L ha-1 spent wash was applied which wasfollowed by addition of spent wash @ 0.5 millionL ha-1 during 2007-08 and 2008-09, respectively.Sukanya and Meli (2004) and Kalaiselvi andMahimairaja (2010) reported increment in Nstatus of the soil. Increment in the available Kstatus of the soil due to spent wash applicationwas also observed by Pathak et al. (1999) andSindhu et al. (2007). Mark reduction in ESP ofsodic soil may be due to the fact that theexchangeable calcium present in spent wash mighthave replaced sodium ion from the exchange sitesin the soil which eventually reduced the ESP.Similar results were also reported by Saliha (2003),Mahendra (2007) and Sindhu et al. (2007).

Conclusions

Application of 0.5 million L ha-1 distillery spentwash significantly increased the growthparameters, grain and straw yield of paddy andwheat and uptake of Ca, Mg and K under sodicVertisol as compared to control as well as gypsum@ 75% GR. Apart from increasing the organiccarbon and available N, K it also reduced the ESPbelow the level suitable for cultivation of rice andwheat. Therefore, it can be concluded that spentwash may be utilized successfully for reclamationon sodic Vertisols as an alternative to gypsum.

References

Bhaskar M, Kayalvizi C and Subhash Chandra Bose M(2003) Eco-friendly utilization of distillery effluent inAgriculture- A review. Agricultural Review 24: 16-30.

Das M, Chakraborty H, Singandhupe RB, Muduli SD andKumar A (2010) Utilization of distillery waste waterfor improving production in under productive Paddygrown area in India. Journal of Scientific and IndustrialResearch 69: 560-563.

Kalaiselvi P and Mahimairaja S (2010) Effect of spent washapplication on nitrogen dynamics in soil. International


Journal of Environmental Sciences and Development 1: 184-189.

Mahendra AC (2007) Studies on reclamation of sodic soilsthrough distillery spent wash. M.Sc. Thesis, Deptt. ofSoil Science and Agricultural Chemistry, University ofAgricultural Sciences, Dharwad (Karnataka).

Mandal AK, Sharma RC, Singh Gurubachan and Dagar JC(2010) Computerized Database on Salt Affected Soils in India.Tech. Bull. CSSRI, Karnal 2/2010. Central Soil SalinityResearch Institute, Karnal. 28 p.

Murugaragavan R (2002) Distillery spent wash on cropproduction in Dryland soils. M.Sc. (EnvironmentalSciences) Thesis TNAU, Coimbatore. India.

Olsen SR, Cole CV, Watanabe FS and Dean LA (1954)Estimation of available phosphorus in soils by extractingwith sodium bicarbonate. USDA Circulation 939.

Pathak H, Joshi HC, Chaudhary A, Chaudhary R, Kalra Nand Dwivedi MK (1999) Soil amendments with distilleryeffluent for Wheat and Rice cultivation. Water, Air andSoil Pollution 113: 133-140.

Richards LA (ed) (1954) Diagnosis and Improvement of Salineand Alkali Soils. Hand Book No. 60 USDA, WashingtonDC

Saliha BB (2003) Eco-friendly utilization of distillery spentwash for improving agricultural productivity in Drylandand high pH soils of Theni district. Ph.D. Thesis, Deptt.

of Soil Science and Agricultural Chemistry, TNAU,AC&RI, Madurai, India.

Sharma RC (1996) Comments on The Report on “Status ofLand Degradation in India”. Dept. Soil and Waterconservation, Govt. of India, New Delhi.

Sindhu SK, Sharma Amit and Ikram Saiqa (2007) Analysisand recommendation of agricultural use of distilleryspent wash in Rampur district. E- Journal of Chemistry4: 390-396.

Subbiah BV and Asija GL (1956) A rapid procedure for theestimation of available nitrogen in soil. Current Science25: 259-260.

Sukanya TS and Meli SS (2004) Response of Wheat to gradeddilution of liquid distillery effluent on plant nutrientcontents, nutrient up-take, crop yield and residual soilfertility. Karnataka Journal of Agriculture Sciences 17: 417-420.

Swami N (2012) Performance of distillery and sugar industrywaste on reclamation and crop production of wheat insodic Vertisols. M.Sc.(Ag) Thesis, Dept. of Soil Scienceand Agricultural Chemistry, RVSKVV, College ofAgriculture, Indore.

Walkley A and Black IA (1934) An examination of thedigestion method for determining soil organic matter aproposed modification of the chromic acid titrationmethod. Soil Science 37: 29-38.

Received April, 2017; Accepted July 2017

Response of Isabgol (Plantago ovata) to Bioregulators andVarying Water Salinity Levels Under Drip Irrigation

Deepak Gupta*, IJ Gulati, NS Yadav and AK Singh

AICRP on Management of Salt Affected Soils and Use of Saline Water in AgricultureS.K. Rajasthan Agricultural University, Bikaner, Rajasthan, India


Abstract

An experiment was conducted to assess the effects of bioregulators applied as a foliar spray for mitigating theadverse effects of saline water on growth and yield of Isabgol (Plantago ovata) under drip irrigation. Grain yieldof Isabgol remained unchanged as the levels of salinity of irrigation water increased from 0.25 dS m-1 (bestavailable water-control) to 4 dS m-1. However, at 8 dS m-1, significant reduction of 20.5 and 22.4 per cent ingrain yield was recorded as compared to control (787 kg ha-1) and 4 dS m-1 (807 kg ha-1). Grain yield increasedby 21.5, 7.8 and 12.1 per cent over control, ascorbic acid and benzyl adenine, respectively because of foliarspray of K2SO4 (200 mg L-1). Combined effect of treatments was found significant in case of chlorophyll contentand membrane stability index only. Among different bio-regulators, K2SO4 was found most effective particularlywith increased salinity of irrigation water.

Key words:Bioregulators, Drip irrigation, Foliar spray, Isabgol, Plantago ovata, Potassium sulphate, Water salinity

Introduction

Increase in the agricultural production has becomeessential to cope up with the food requirement ofexpanding world population (Chen et al., 2011)but, due to decrease in availability of fresh waterfor agricultural production (Cai and Rosegrant,2003), saline water for irrigation is inevitable(Dagar and Minhas, 2016). Salt stress causes waterdeficit as a result of osmotic effects on metabolicactivities of plants (Ashraf and Fooled, 2007) andthis water deficit results in oxidative stress becauseof the formation of reactive oxygen species(Krasensky and Jonak, 2012)

It is well known that judicious use of salineground water is possible through micro-irrigationsystem. Several studies have been conducted fordevelopment of irrigation systems for salinitymanagement with drip irrigation (DI) using salinewater (Simsek et al., 2004; Dagdelen et al., 2008).In case of drip, relatively small amounts ofirrigation water are applied at frequent intervaland movement of salts in root zone take place atlow leaching fraction, pushing the salts toperiphery of wetting zone. As a result, plants may

experience low salinity stress compared to surfaceirrigation, if irrigation water remains same.

In order to overcome salinity problem, severalstudies have been accomplished for selectingcultivars tolerant to abiotic constraints (De Malachand Pasternak, 1993; Claudivan et al., 2005; OuledAhmad et al., 2007). Of the various strategiescurrently under exploitation, improvement insalinity tolerance of crops through exogenousapplication of different types of chemicalsincluding plant growth regulators, osmo-protectants and inorganic nutrients seems to bean efficient and economical approach (Ashraf etal., 2008). The use of such substances has resultedin a substantial increase in both growth and yieldof many crops grown under saline conditions(Ashraf et al., 2008; Kaya et al., 2010).Bioregulators play a vital role in regulation ofphysiological process related to growth anddevelopment of crops like uptake and transport,stomatal closure (Gunes et al., 2005), membranestability, photosynthesis and growth (Khan et al.,2003). Ion uptake and compartmentalization arecrucial for growth under saline conditions (Adamset al., 1992). Potassium plays an important role in


Response of Isabgol to water salinity levels under drip irrigation 195

survival of crop plants under salt stress conditions.Potassium is essential for many physiologicalprocesses such as photosynthesis, translocation ofphotosynthates into sink organs, maintenance ofturgor, activation of enzymes and reducing excessuptake of sodium (Mengel and Kirby, 2001). Theproblem of excessive sodium in root/shoot systemof plant could be avoided, if potassium is providedthrough foliar application to the plants.

Many salt-tolerant crops have been assessedusing saline irrigation including crops of medicinalvalue (Tomar and Minhas, 2002, 2004 a, b; Dagar,2014; Dagar et al., 2008, 2012, 2013, 2016; Dagarand Minhas, 2016). In these studies, Isabgol(Plantago ovata) has been found among mostpotential crops, particularly for dry regions (Tomaret al., 2010). Though, development of methodsand strategies to ameliorates deleterious effects ofsalt stress on plants have received considerableattention (Shivran, 2015), but the effect of foliarexogenous applications of bioregulators with dripirrigation on growth and yield of Isabgol undersalt stress conditions has yet not been wellattempted. Therefore, this experiment focuses onthe effect of different bioregulators on plantgrowth and yield of Isabgol under drip irrigationwith saline water.


Present research work was carried out atAgricultural Research Station, SwamiKeshwanand Rajasthan Agricultural University,Bikaner during rabi 2012-13 and 2013-14. The soiltexture of the experimental field for 0-90 cm depthwas sandy (sand 89.1%, silt 2.84% and clay 5.68%)with low to medium fertility status. The organiccarbon (%), available N, P2O5 and K2O content(kg ha-1) were 0.067, 93, 12.4 and 140, respectively.The pH1:2, EC1:2 and bulk density of 0-90 cm soilwas 8.33, 0.17 dS m-1 and 1.54 g cm-3, respectively.Hydraulic conductivity was measured to be 8.67cm hr-1. The treatments consisted of three levelsof irrigation water salinity (ECiw) viz. BAW (Bestavailable water having ECiw 0.25 dS m-1), 4 and 8dS m-1 and four foliar spray treatments viz.,control, ascorbic acid (100 mg L-1), potassiumsulphate (200 mg L-1) and benzyladenine (200 mgL-1). These treatment combinations replicated six

times, were laid out in split plot design, with levelsof irrigation water salinity (ECiw) in main plotsand foliar sprays in sub-plots. Saline waters ofdesired salinity were prepared artificially inseparate tanks. For this, five salts namely, NaCl,NaHCO3, Na2SO4, CaCl2 and MgSO4 were usedto obtain EC of 4 and 8 dS m-1 by maintainingSAR of at par with naturally occurring salinewaters. The saline waters were prepared bydissolving required amount of NaCl, NaHCO3,Na2SO4, CaCl2 and MgSO4 in the BAW. Thecontrol plots were irrigated using BAW (ECiw 0.25dS m-1) during the experiment period of two years.Isabgol variety RI-89 was sown and foliarapplications were done twice at 45 and 60 daysafter sowing. Drip with lateral spacing 60 cm andemitter spacing of 30 cm was used in theexperiment. The yield attributes (plant height,number of tillers per plant and numbers of earsper plant), seed yield, biological yield, chlorophyllcontent and membrane stability were recorded anddata were statistically analyzed for estimation ofanalysis of variance (ANOVA).


Growth and yield

Seed yield of Isabgol was not affected withincreased salinity of irrigation water from 0.25dS m-1 (BAW) to 4 dS m-1 (Table 1). However, at 8dS m-1, 20.5 and 22.4 per cent reduction in grainyield was recorded as compared to BAW (787 kgha-1) and 4 dS m-1 (807 kg ha-1). Biological yieldwas not affected significantly up to ECiw of 4 dSm-1 during both the years (Table 1). Furtherincrease in ECiw significantly decreased thebiological yield. Various growth and yieldattributes viz. plant height, number of tillers perplant and number of ears per plant also exhibiteddecreasing trend with increasing levels ofirrigation water salinity. The probable reason fordecrease in growth, yield attributes and yield isthat uptake of toxic ions by plants disturb theirmetabolic activities and concentration of toxicions like Na+ and Cl- increases inside the tissuesconsequently water potential decreases thatreduces growth and productivity of plants (Akhtaret al., 2013; Kausar and Gull, 2014b). Theincreased concentration of toxic ions decreases

196 Gupta et al.

the absorption of essential nutrients like calcium,magnesium, phosphorus, potassium and iron(Han et al., 2014) and as a result plants suffer fromnutritional imbalance (Ashraf et al., 2013).

Among different foliar spray treatments,K2SO4 and its two sprays at 45 and 60 days aftersowing brought about significant improvement inseed yield over rest of the treatments during boththe years. On the pooled basis, K2SO4 and its twosprays at 45 and 60 days after sowing recorded asignificant increase of 21.5, 7.8 and 12.1 per centover control, ascorbic acid and benzyl adenine,respectively. Similarly, foliar application of thethree bioregulators resulted in significant increasein biological yield on pooled basis. Foliarapplication with K2SO4 brought significantimprovement of biological yield of 20.9, 7.5 and10.9 percent over control, ascorbic acid and benzyl

adenine, respectively. Foliar application of K2SO4

caused significant improvement in plant height,number of tillers per plant and number of earsper plant as compared the other bioregulators andcontrol (Table 2). The growth and yield attributesfor ascorbic acid and benzyl adenine werestatistically at par.

In present investigation, foliar application ofK2SO4 alleviated the toxicity of Na+ by decreasingthe chances of its accumulation in plant parts. Theresults of present investigation are in agreementwith the findings of many workers in differentplant species (Sultana et al., 2001; Cha-um et al.,2011) who found that nutrients were absorbed bythe leaves when applied onto the shoot and restrictthe inhibition due to toxic effects of Na+ and Cl-

or minimizes the salinity induced deficiency.These minerals increased photosynthetic and

Table 1. Effect of salinity of irrigation water and foliar application of bioregulators on Isabgol yield

Treatments Seed yield (kg ha-1) Biological yield (kg ha-1)2012-13 2013-14 Pooled 2012-13 2013-14 Pooled

ECiw (dS m-1) levels0.25* 851 723 787 2614 2222 24184.0 864 750 807 2632 2197 24158.0 700 552 626 2112 1665 1889LSD (p≤0.05) 18 40 21 56 131 68

Foliar sprayControl 765 572 669 2343 1727 2035Ascorbic acid (100 mg L-1) 816 692 754 2485 2065 2275K2SO4 (200 mg L-1) 845 781 813 2563 2329 2446Benzyl adenine (200 mg L-1) 794 656 725 2419 1990 2205LSD (p≤0.05) 21 47 26 65 127 70

*Best available water (BAW)

Table 2. Effect of salinity of irrigation water and foliar application of bioregulators on isabgol growth parameters

Treatments Plant Height (cm) No. of tillers plant-1 No. of ears plant-1

2012-13 2013-14 Pooled 2012-13 2013-14 Pooled 2012-13 2013-14 Pooled

EC iw (dS m-1) levels0.25* 26.4 21.2 23.8 12.2 10.3 11.37 6.57 5.13 5.854.0 25.5 19.7 22.6 10.8 9.1 9.94 6.05 5.24 5.658.0 20.0 12.7 16.3 8.7 6.6 7.64 5.35 4.88 5.12LSD (p≤0.05) 0.8 0.6 0.4 0.4 0.4 0.24 0.14 0.20 0.09

Foliar sprayControl 23.0 17.1 20.0 9.67 8.00 8.84 5.68 4.77 5.23Ascorbic acid (100 mg L-1) 23.6 17.6 20.6 10.43 8.70 9.57 5.94 5.09 5.52K2SO4 (200 mg L-1) 25.1 18.6 21.8 11.41 9.20 10.31 6.28 5.32 5.80Benzyl adenine (200 mg L-1) 24.3 18.1 21.2 10.74 8.80 9.77 6.07 5.14 5.61LSD (p≤0.05) 0.9 0.7 0.6 0.47 0.50 0.36 0.16 0.20 0.12



enzymatic activities and an effective translocationof assimilate to reproductive parts resulting inhigher yield (Sarkar and Malik, 2001). Moreover,the induction of antioxidant response andprotective role of membrane by bioregulatorscaused increase in the tolerance of plant to damage(Turen and Aydin, 2005).

Chlorophyll content and membrane stability index

Increasing levels of ECiw significantly decreasedthe chlorophyll content of leaves during both theyears and on pooled basis as well (Table 3). Foliarsprays of K2SO4 excelled all the other treatmentsin this respect and recorded significantly higherchlorophyll content in comparison to rest of thetreatments during both the years. Membranestability index was decreased significantly duringboth the years and also on pooled basis with everyincrease in the levels of ECiw. The highest valuefor membrane stability index was recorded withfoliar sprays of K2SO4 and differed significantlyfrom rest of the other treatments. Combined effectof treatments was found significant in case ofchlorophyll content and membrane stability indexonly. It is pertinent to note that foliar spray ofK2SO4 with BAW increased the chlorophyllcontent by a margin of only 3.2, 0.5 and 3.2 percent over control, ascorbic acid and benzyladenine, respectively, whereas respective increaseof 13.2, 8.9 and 2.2 per cent in chlorophyll contentat 4 dS m-1 and 34.5, 4.7 and 9.5 at 8 dS m-1 provedthe role of K2SO4 with increasing salinity of

irrigation water. In case of membrane stability,K2SO4 exhibited its positive role with increasingsalinity of irrigation water, which is evident fromthe fact that foliar spray of K2SO4 with BAWincreased the membrane stability by a margin ofonly 5.2, 1.2 and 4.4 percent over control, ascorbicacid and benzyl adenine, respectively, whereasrespective increase in membrane stability was ofthe order of 8.4, 3.9 and 6.5 percent at 4 dS m-1

and 30.3, 10.1 and 13.8 at 8 dS m-1 salinity ofirrigation water.

These results are similar with those ofDownton et al. (1985) and Yildirim et al. (2008),who stated that chlorophyll content significantlydecreased in the leaves with increase in salinitylevels. Salt induced reduction in chlorophyllcontent and thereby photosynthesis could beattributed to high Na+ and Cl- (Gunes et al., 2005),disturbance in the accumulation of nutrients,reduction in water potential and increase inosmotic potential, inhibition of photochemicalprocesses (Steduto et al., 2000) and the increasedproduction of ROS in the chloroplast (Meneguzzoet al., 1999).

Combined effect of treatments on chlorophyllcontent and membrane stability index on pooledbasis

Combined effect of treatments on chlorophyllcontent and membrane stability index on pooledbasis are found to be increased (Table 4).

Table 3. Effect of salinity of irrigation water and foliar application of bioregulators on chlorophyll content and membrane stabilityof Isabgol

Treatments Chlorophyll content (mg g-1) Membrane stability2012-13 2013-14 Pooled 2012-13 2013-14 Pooled

ECiw (dS m-1) levels0.25* 0.969 0.917 0.943 55.70 56.15 55.934.0 0.911 0.877 0.894 47.20 50.69 48.958.0 0.768 0.788 0.778 34.80 36.14 35.47LSD (p≤0.05) 0.061 0.018 0.030 1.20 1.03 0.78

Foliar spray/ soakingControl 0.811 0.788 0.800 43.30 44.99 44.15Ascorbic acid (100 mg L-1) 0.879 0.886 0.883 46.50 48.31 47.41K2SO4 (200 mg L-1) 0.941 0.905 0.923 48.60 50.44 49.52Benzyl adenine (200 mg L-1) 0.899 0.863 0.881 45.20 46.89 46.05LSD (p≤0.05) 0.071 0.021 0.040 1.30 1.29 0.90


198 Gupta et al.

The alleviation of salt stress effects onchlorophyll content may be due to improvedantioxidant activity which resulted in betterdistribution of nutrients in leaves and decreasedcontent of Na+ and Cl-, particularly in foliarapplication of K2SO4 treatment. Similar type ofconclusions was also drawn by Gunes et al. (2005).Salinity impaired membrane stability increasingelectrolyte leakage. However, application ofbioregulators especially K2SO4 partly maintainedmembrane stability. Present study clearly indicatedthat bioregulators treatments facilitated themaintenance of membrane functions under saltstress conditions (Gulati et al., 2016).

Conclusions

The critical level of salinity in irrigation water wasfound to be 4 ds m-1, beyond which retardationoccurs at any growth and yield parameters. Itcould considerably be extended with the use offoliar spray of K2SO4 which will provide incentiveto farmer for growing plants utilizing saline waterirrigation so far considered unsuitable forcultivation, through foliar application of essentialminerals.

References

Adams P, Vernon DM, Thomas JC, Bohnert HJ, Jensen RG(1992) Distinct cellular and organismic responses to saltstress. Plant Cell Physiology 33: 1215-1223.

Akhtar J, Ahmad R, Ashraf MY, Tanveer A, Waraich EA,and Oraby H (2013) Influence of exogenous applicationof salicylic acid on salt stressed mung bean (Vignaradiata): growth and nitrogen metabolism. PakistanJournal of Botany 45: 119-125.

Ashraf M, Athar HR, Harris PJC and Kwon TR (2008) Someprospective strategies for improving crop salt tolerance.Advances in Agronomy 97: 45–110

Ashraf MY, Rafique N, Ashraf M, Azhar N, and Marchand,M (2013) Effect of supplemental potassium (K+) ongrowth, physiological and biochemical attributes ofwheat grown under saline conditions. Journal of PlantNutrition 36: 443-458.

Cai XM and Rosegrant MW (2003) World waterproductivity: current situation and future options. In:Kijne JW, Barker R, Molden D (eds.) Water Productivityin Agriculture: Limits and Opportunities for Improvement.Oxford: CAB Publishing and Colombo: InternationalWater Management Institute, pp 163–178.

Cha-um S, Pokasombat Y and Kirdmanee C (2011)Remediation of salt-affected soil by gypsum andfarmyard manure “ Importance for the production ofJasmine rice. Australian Journal of Crop Science 5: 458-465

Chen YQ, Li XB and Wang J (2011) Changes and effectingfactors of grain production in China. Chinese GeographicalScience 21(6): 676–684.

Claudivan, FL, Jose C, Marco AO and Hugo AR(2005) Changes in growth and in solute concentrationin sorghum leaves and roots during salt stress recovery.Environmental and Experimental Botany 54: 69-76.

Dagar JC (2014) Greening salty and waterlogged landsthrough agroforestry systems for livelihood security andbetter environment. In: Dagar JC, Singh AK,Arunachalam A (eds) Agroforestry Systems in India:Livelihood Security & Ecosystem Services, Advances inAgroforestry vol 10, Springer Doldrecht, pp 273-332

Dagar JC and Minhas PS (2016) Saline irrigation forproductive agroforestry systems. In: Dagar JC andMinhas PS (eds) Agroforestry for Management ofWaterlogged Saline Soils and Poor-quality Waters. Advancesin Agroforestry, vol 13. Springer, Dordrecht, pp 145-161.

Table 4. Combined effect of treatments on chlorophyll content and membrane stability index on pooled basis

Treatments Control Ascorbic Acid K2SO4 Benzyl adenine

Chlorophyll content (mg g-1)0.25* 0.929 0.954 0.959 0.9294 dS m-1 0.836 0.869 0.946 0.9268 dS m-1 0.633 0.825 0.864 0.789LSD (p≤0.05) 0.063

Membrane stability (%)0.25 54.57 56.77 57.43 54.964 dS m-1 47.22 49.27 51.18 48.078 dS m-1 30.62 36.25 39.90 35.07LSD (p≤0.05) 1.57



Dagar JC, Sharma PC, Sharma DK and Singh AK (eds)(2016) Innovative Saline Agriculture. Springer, Dordrecht,pp 519

Dagar JC, Tomar OS, Minhas PS and Kumar M (2013)Lemongrass (Cymbopogon f lexuosus) productivity asaffected by salinity of irrigation water, planting methodand fertilizer doses on degraded calcareous soil in a semi-arid region of northwest India. Indian J Agric Sci 83(7):734–738

Dagar JC, Tomar OS, Minhas PS, Singh G and Jeet-Ram(2008) Dryland Biosaline Agriculture -Hisar Experience,Techanical Bulletin 6. CSSRI, Karnal, India, p 28

Dagar JC, Yadav RK and Sharif Ahamad (2012) Euphorbiaantisyphilitica: A potential petro-crop for degradedcalcareous soils and saline water irrigation in dry regionsof India. Journal of Soil Salinity & Water Quality 4(2): 86-91.

Dagdelen N, Basal Y, Gurbuz T and Akcay S (2008) Differentdrip irrigation regimes affect cotton yield, water useefficiency and fibber quality in western Turkey.Agricultural Water Management 96:111-120.

DeMalach Y and Pasternak D (1993) Agriculture in a desertsaline environment—a case study. In: Marani-Bettolo,GB (ed) Agriculture and the Quality of Life—New GlobalTrends. Proceeding of an International Conference heldat The Ponitificia Academia Scientiarum, Ex Aedibvsacadimicis in Civitate Vaticana, Rome - Italy, pp 97-126.

Downton WJS, Grant WJR and Robinson SP (1985)Photosynthetic and stomatal responses of spinach leavesto salt stress. Plant Physiology 77: 85-88.

Gulati IJ, Yadav NS, Singh AK and Gupta D (2016)Mitigating adverse effect of saline water by exogenousapplication of bioregulators in wheat grown under dripirrigation. Journal of Soil Salinity and Water Quality 8(2):180-187.

Gunes A, Inal A, Alpaslan M, Cicek N, Guneri E, Eraslan Fand Guzelordu T (2005) Effects of exogenously appliedsalicylic acid on the induction of multiple stress toleranceand mineral nutrition in maize (Zea mays L.). Archives ofAgronomy and Soil Science 51: 687-95.

Han L, Gao Y and Li D (2014) Ion Uptake in Tall Fescue asAffected by Carbonate, Chloride, and Sulfate Salinity.PLOS ONE, 9(3), 91908. http://dx.doi.org/10.1371 /journal.pone.0091908.

Jamil A, Riaz S, Ashraf M and Foolad MR (2011) Geneexpression profiling of plants under salt stress. CriticalReviews in Plant Sciences 30: 435-458

Kausar A and Gull M (2014) Nutrients uptake and growthanalysis of four sorghum (Sorghum bicolor L.) genotypesexposed to salt stress. Pensee Journal 76(4): 102-110.

Kaya C, Tuna AL and Okant AM (2010) Effect of foliarapplied kinetin and indole acetic acid on maize plants

grown under saline conditions. Turkish Journal ofAgriculture and Forestry 34: 529-538

Khan W, Prithiviraj B and Smith DL (2003) Photosyntheticresponse of corn and soybean to foliar application ofsalicylates. Journal of Plant Physiology 160: 485-492.

Meneguzzo S, Navarri-Izzo F and Izzo R (1999)Antioxidative responses of shoot and root of wheat toincreasing NaCl concentration. Journal of PlantPhysiology 155: 274-80.

Mengel K and Kirkby EA (2001) Principles of Plant Nutrition.Kluwer Academic Publishers, Norwell. pp. 305-313.

Sarkar RK and Malik GC (2001) Effect of foliar spray ofpotassium nitrate and calcium nitrate on grasspea(Lathyrus sativus L.) grown in rice fallows. Lathyruslathyrism Newsletter 2.

Shivran, AC (2015) Effect of seed rate and sowing methodson productivity of Isabgol (Plantago ovata Forsk) undersalinity affected semiarid regions of Rajasthan. Journalof Soil Salinity and Water Quality 7(2): 144-147.

Simsek M, Kacira M and Tonkaz T (2004) The effects ofdifferent drip irrigation regimes on watermelon (Citrulluslanatus) yield and yield components under semi-aridclimatic conditions. Journal of Agricultural Research 55:1149-1157.

Steduto P, Albrizio R, Giorio P and Sorrentino G (2000)Gas exchange esponse and stomatal limitations tocarbon assimilation of sunflower under salinity.Environmental and Experimental Botany 44: 243-55.

Sultana N, Ikeda T and Kashem MA (2001) Effect of foliarspray of nutrient solutions on photosynthesis, dry matteraccumulation and yield in sea water-stressed rice.Environmental and Experimental Botany 46: 129-140.

Tomar OS, Dagar JC and Minhas PS (2010) Evaluation ofsowing methods, irrigation schedules, chemical fertilizerdoses and varieties of Plantago ovata Forsk. to rehabilitatedegraded calcareous lands irrigated with saline water indry regions of north western India. Arid Land Research& Management 24: 133-151.

Tomar OS and Minhas PS (2002) Performance of someornamental winter annual flowering species under salineirrigation. Indian Journal of Horticulture 59(2): 201–206.

Tomar OS and Minhas PS (2004a) Relative performance ofaromatic grasses under saline irrigation. Indian Journalof Agronomy 49(3): 207–208.

Tomar OS and Minhas PS (2004b) Performance of medicinalplant species under saline irrigation. Indian Journal ofAgronomy 49 (3): 209–211.

Yildrim E, Turan M and Guvenc I (2008) Effect of foliarsalicylic acid applications on growth, chlorophyll andmineral content of cucumber (Cucumis sativus L.) grownunder salt stress. Journal of Plant Nutrition 31: 593-612.

Received in April, 2017; Accepted in July, 2017

Effect of Different Levels of Fertilizers and Biogas Slurry onYield and Chemical Composition of Wheat Grown under

Sodic Vertisols

Megha Vishwakarma, UR Khandkar* and SC Tiwari

AICRP on Management of Salt Affected Soils and Use of Saline Water in AgricultureRVSKVV, College of Agriculture, Indore, Madhya Pradesh, India


Abstract

An experiment was conducted to study the effect of recommended doses of fertilizer and biogas slurry on yieldand chemical composition of wheat grown under sodic vertisols. The treatment 75% RDF + 1250 kg biogasslurry (BGS) per ha was found beneficial for increasing the growth, yield attributing characters and yield ofwheat. The concentration of N, P and K in grain and straw of wheat also increased with the application of thistreatment and this was at par with 100% RDF+1250 kg BGS per ha. This also improved the available N, P andK content in soil and there was decline in the ESP and exchangeable sodium content of post-harvest soil.

Key words: Biogas slurry, Recommended doses of fertilizer, Sodic vertisols, wheat yield

Introduction

India is endowed with 6.73 million ha salt-affectedsoils (Mandal et al., 2010) out of which 2.42 lakhha of area is found in Madhya Pradesh. Sodic soilsare known to be low in organic matter and hencepoor in available nitrogen content. Chemicalfertilizers have become indispensable foragriculture but, presently these are much expensiveand, in certain cases not available in time. In salt-affected soils, the crop requires 25% morechemical fertilizers than the normal soils. Theintegrated use of organic and chemical fertilizerscan reduce dependence on expensive chemicalinputs. To sustain high crop yields withoutdeterioration of soil fertility, it is important toworkout optimal combination of fertilizer andmanures in the crop.

Biogas slurry (BGS) is by-product of biogasproduction generated from cow dung. Biogasslurry is a good source of plant nutrients and canimprove soil properties (Garg et al., 2005). It canimprove the physical and biological quality of soilthrough organic matter to the soil. It also improvesWHC, CEC, and lesser soil erosion and providesnutrients to plants and soil micro-flora includingN fixing and phosphorus solubilizing organisms.

Keeping this in view the present pot experimentwas planned to find out the effect of differentcombinations of fertilizers and biogas slurry onyield and chemical composition of wheat grownunder sodic Vertisols.


A pot experiment was conducted during rabiseasons of 2015-16 in the net house of SaltAffected Soils Project, College of Agriculture,Indore. The bulk surface soil (0-15 cm) wascollected from Salinity Research Farm, Barwaha,district Khargone, Madhya Pradesh. The soil wasair dried, crushed with wooden roller and lot wasthoroughly mixed before filling of pots.

The experimental soil (Typic Haplustert- sodicphase) had following characteristics: textureclayey; pHs 8.42; ECe 1.26 dS m-1; organic carbon0.36%; and available N, P and K 190, 10.3 and335 kg ha-1, respectively. The exchangeable Ca,Mg and Na were 16.01, 5.60 and 17.17 (c mol(P+) kg-1), respectively. The CEC and ESP of soilwere 39.6 (c mol (P+) kg-1) and 43.23, respectively.The biogas slurry was obtained from Dairy BiogasPlant, College of Agriculture, Indore. The biogasslurry thus obtained was dried in an oven at 55oC


Effects of fertilizer and biogas slurry on wheat 201

and subjected to the chemical analysis. Thephysico-chemical properties of biogas slurry aregiven in Table 1.

The treatment comprised of T0-Control(original soil), T1-100% recommended dose offertilizer (RDF) i.e.150 N, 80 P2O5 and 40 K2O kgha-1, T2-100% RDF + 750 kg BGS ha-1, T3-75%RDF+ 750 kg BGS ha-1, T4-50% RDF + 750 kgBGS ha-1, T5-100% RDF + 1000 kg BGS ha-1,T6-75% RDF+ 1000 kg BGS ha-1, T7-50% RDF+ 1000 kg BGS ha-1, T8-100% RDF + 1250 kgBGS ha-1, T9-75% RDF+ 1250 kg BGS ha-1, T10-50% RDF+ 1250 kg BGS ha-1 were tried inCompletely Randomized Design with 3replications.

China clay pots of approximate 30 kg capacitywere used. These were filled with 15 kg ofprocessed soil. The full doses of biogas slurry(BGS) was applied to upper 15 cm soil as per thetreatments and moisten the soil for chemicalreaction and kept the pots for 15 days. After 15days, the half of the nitrogen of respective RDFwas applied at sowing and remaining half of theN was applied in two equal splits at 22 and 45days after sowing. The full dose of P and K ofrespective RDF was given as basal at the time ofsowing of wheat. The nitrogen, phosphorus andpotassium were given through urea, single superphosphate and muriate of potash, respectively.

Seeds of wheat (var. HI 1077) were shown inpots and irrigated with deionized water. Thinningwas done after 8 days of sowing and 5 plants werekept in each pot. The plants were harvested atmaturity and grain and straw yield was recorded.

Plant samples (grain and straw) were ovendried at 60oC. Total nitrogen in plant samples wasdetermined by micro-Kjeldahl method as outlinedby Jackson (1973). Phosphorus and potassiumwere determined in wet digested samples byVanado- molybdo phosphoric acid yellow colourmethod (Chapman and Pratt, 1961) and flame

photometer method, respectively. Soil sampleswere collected from all the pots at harvest. Soilsamples were air-dried and processed. The pHsand ECe of soil were determined in saturated pasteand saturated extract, respectively. Theexchangeable Ca, Mg, Na and ESP weredetermined by the method of Richards (1954). Theorganic carbon was estimated by Walkley andBlack (1934) method. The available N (Subbiahand Asija, 1956), P (Olsen et al., 1954) andavailable K were determined by neutral normalammonium acetate method (Handway and Heidal1952).


Growth and yield attributing characters of wheat

The growth and yield attributing characters suchas plant height, number of tillers plant-1, length ofear head and number of spikelet per ear head inwheat varied significantly with the application ofdifferent treatments (Table 2). Application oftreatment T8 significantly increased the plantheight, number of tillers plant-1, length of ear headand number of spikelet per ear head in wheat butit did not differ significantly with T9. Theincrement in plant height, number of tillers plant-

1, length of ear head and number of spikelet perear head due to application of T8 and T9 was 21.1,84.6, 100.3 and 84.7% and 18.2, 80.6, 95.9 and79.5%, respectively over control. The increase ingrowth and yield attributing characters probablycould be attributed by the ability of biogas slurryto supply the required plant nutrients and improvesoil structure and water holding capacity, therebypromoting plant growth and yield attributes. Theresults corroborated with findings of Bharde et al.(2003), Nasir et al. (2010) and Li et al. (2014).

Grain and straw yield of wheat

The application of RDF along with BGSsignificantly improved the grain and straw yieldof wheat over control (Table 2). Highest grain

Table 1. Characteristics of biogas slurry (BGS) used in experiment

Moisture pH ECe Total N Total P Total K Total Ca Total Mg(%) (1:5) (dS m-1) (%) (%) (%) (%)

88 6.98 0.93 1.60 1.55 1.00 1.60 0.50

202 Vishwakarma et al.

Table 2. Growth, yield attributes, grain and straw yield of wheat as affected by different treatments

Treatments Plant height Number of Length of ear Number of Grain yield Straw yield(cm) tillers plant-1 head (cm) spikelet per (g pot-1) (g pot-1)

ear head

T0 64.07 3.25 3.21 10.98 24.46 26.24T1 68.98 4.13 4.21 13.09 33.91 34.04T2 72.98 5.08 5.11 16.15 41.92 42.76T3 70.69 4.98 4.90 15.54 38.19 39.26T4 68.61 4.22 4.21 14.34 35.64 35.64T5 73.38 5.22 5.20 16.27 42.13 44.42T6 71.76 4.78 4.97 15.63 39.89 40.55T7 70.45 4.16 4.36 14.51 36.55 36.55T8 77.62 6.00 6.43 20.29 47.61 51.75T9 75.75 5.87 6.29 19.72 45.70 49.79 T10 72.11 5.06 5.04 15.72 41.58 42.42LSD (p≤0.05) 2.29 0.58 0.79 1.52 3.45 3.48

T0-Control, T1-100% RDF (150 N, 80 P2O5 and 40 K2O kg ha-1), T2-100% RDF + 750 kg BGS ha-1, T3-75% RDF+ 750 kg BGSha-1, T4-50% RDF + 750 kg BGS ha-1, T5-100% RDF + 1000 kg BGS ha-1, T6-75% RDF+ 1000 kg BGS ha-1, T7-50% RDF + 1000kg BGS ha-1, T8-100% RDF + 1250 kg BGS ha-1, T9-75% RDF+ 1250 kg BGS ha-1, T10-50% RDF+ 1250 kg BGS ha-1

Table 3. Effect of different treatments on nitrogen, phosphorus and potassium content (%) in grain and straw of wheat at harvest

Treatments Grain StrawN P K N P K

T0 2.34 0.10 0.28 1.21 0.09 2.10T1 2.42 0.15 0.34 1.28 0.14 2.17T2 2.55 0.22 0.43 1.40 0.19 2.29T3 2.51 0.20 0.41 1.36 0.17 2.26T4 2.43 0.15 0.35 1.29 0.15 2.19T5 2.57 0.23 0.46 1.41 0.20 2.30T6 2.54 0.21 0.42 1.38 0.18 2.28T7 2.46 0.16 0.36 1.31 0.15 2.21T8 2.67 0.31 0.54 1.50 0.26 2.40T9 2.63 0.29 0.52 1.46 0.24 2.38 T10 2.52 0.23 0.42 1.39 0.18 2.27LSD (p≤0.05) 0.07 0.05 0.05 0.07 0.03 0.06

Treatments as depicted in Table 2

(47.61 g pot-1) and straw yield (52.62 g pot-1) wasrecorded in treatment T8 which increased by 94.6and 97.2 per cent, respectively over control. But itwas statistically at par with T9. The per centincrease in grain and straw yield of wheat due toapplication of T9 was 86.8% and 89.7%,respectively over control. Tiwari et al. (2000) alsoreported that WSN (Wheat Straw Nodes) + BGSimproved the rate of mineralization of nutrientsresulting in higher grain yield of wheat.

Nutrient concentration in grain and straw

The data pertaining to nutrient content in grainand straw of wheat (Table 3) indicated that

application of treatment T8 significantly enhancedthe nitrogen content in grain and straw of wheatby 14.1 and 23.9%, respectively over control whichwas statistically at par with T9. The increase in Ncontent in grain and straw of wheat due toapplication of T9 was 12.3 and 20.6 per cent,respectively over control. Significant increase inN content may be ascribed to more availability ofN through mineralization of BGS applied withRDF. Similar results were also reported by Tiwariet al. (2000) and Ahmed et al. (2014).

The increase in phosphorus content in grainand straw of wheat was 210 and 188.8% and 190

Effects of fertilizer and biogas slurry on wheat 203

and 166.6% due to application of treatments T8and T9, respectively. This was due to higher Pavailability from biogas slurry due to its welldecomposed state and faster rate of Pmineralization in biogas slurry treated soil. Braret al. (1999), Nasir et al. (2010) and Ahmed et al.(2014) also reported similar results. Similarly, theincrement in potassium content in grain and strawof wheat due to application of T8 and T9 was92.8 & 14.2 and 85.7 & 13.3 per cent, respectivelyover control. The increment in potassium contentin grain and straw might be due to reclaimingeffect of biogas slurry and improvement innutritional status of soil. The result is in agreementof the study carried out by Dwivedi and Thakur(2000), Tiwari et al. (2000) and Nasir et al. (2010).

Soil chemical properties

The addition of different treatments did not affectthe pHs and ECe of soil significantly (Table 4).However, the application of different treatmentssignificantly increased the organic carbon contentof soil after harvest of wheat over control. Thehighest organic carbon content was observed withthe application of T8, it was statistically at parwith T9. Debebe (2013) also reportedimprovement in organic matter content, bulkdensity and porosity of soil after the biogas slurryapplication. The combined use of fertilizers alongwith BGS was more effective for improvingavailable N, P and K in soil. The addition of T8and T9 increased the available nitrogen in soil by

8.8 and 7.8%, respectively over control. Maximumavailable P was recorded in T8 it was at par withT9. Application of T8 and T9 increased theavailable P by 35.4 and 34.4 per cent, respectivelyover control. The highest available K was observedin T8 followed by T9.

The addition of RDF along with BGS broughtabout the improvement in physicochemicalproperties of soil might be due to themineralization of native as well as applied nutrientwhich brought about a considerable increase innutrient status of soil. These findings are inagreement with More (1994).

Application of T8 and T9 increased theexchangeable Ca and Mg by 9.4 & 21.8 and 9.0 &20.5 per cent, respectively over control (Table 5).

Table 4. pHs, ECe, OC, available N, P and K is post-harvest soil

Treatments pHs ECe OC Available nutrients (kg ha-1)dS m-1 % N P K

T0 8.39 1.24 0.30 189.65 10.17 334.36T1 8.38 1.24 0.30 191.11 11.18 340.60T2 8.36 1.27 0.33 199.51 12.87 353.69T3 8.36 1.26 0.32 197.06 12.40 352.08T4 8.37 1.25 0.31 193.47 12.15 346.86T5 8.34 1.28 0.33 201.62 13.04 354.40T6 8.35 1.26 0.33 197.45 12.46 354.63T7 8.35 1.26 0.31 194.72 12.22 348.70T8 8.33 1.28 0.34 206.45 13.78 360.19T9 8.34 1.29 0.34 204.55 13.67 358.24 T10 8.34 1.26 0.32 196.44 12.82 353.55LSD (p≤0.05) NS NS 0.02 1.95 0.59 3.05


Table 5. Exchangeable Ca, Mg, Na (c mol (p+) kg-1) and ESPof post-harvest soil

Treatment Ca Mg Na ESP

T0 15.81 5.31 17.01 42.96T1 16.11 5.50 16.91 42.71T2 17.01 6.23 15.75 39.76T3 16.64 6.00 15.82 39.95T4 16.82 5.73 15.96 40.30T5 17.06 6.34 15.70 39.65T6 17.07 6.11 15.77 39.81T7 16.67 5.85 15.91 40.18T8 17.31 6.47 15.40 38.88T9 17.24 6.40 15.50 39.13 T10 16.94 5.91 15.72 39.70LSD (p≤0.05) 0.18 0.09 0.23 0.58


204 Vishwakarma et al.

The observed changes in exchangeable Ca and Mgwere mainly due to addition of Ca and Mg in soilsolution from BGS after mineralization. The resultcorroborated with More (1994) and Maskey et al.(2004). Increased Ca and Mg in soil solutionresulted in significant lowering of theexchangeable Na and ESP of soil after harvest ofwheat. The reduction in exchangeable Na andESP was 9.4 and 8.8% and 9.4 and 8.8 per cent,respectively due to application T8 and T9. More(1994) reported that the organic matter containingtreatments decreases the ESP of soil.

Conclusions

In the present investigation it has been found thatapplication of biogass slurry with recommendedfertilizer was effective in reducing the ESP andincreasing the exchangeable cations. Increasednutrient availability from BGS can compensate for25% RDF. Therefore, 75% RDF+1250 kg BGSha-1 may be suitable option for growing wheat cropunder sodic Vertisols as it saved 25% of therecommended doses of fertilizer.

References

Ahmad M, Ahmad Z, Jamil A, Nazil F, Latif M and AkhtarM (2014) Integrated use of plant growth promotingrhizobacteria biogas slurry and chemical nitrogen forsustainable production of maize under salt affectedconditions. Pakistan Journal of Botany 46: 375-382.

Bharde Naresh M, Shivay YS and Singh S (2003) Effect ofbiogas slurry and neem- oil treated urea sources on rice-wheat cropping system. Indian Journal of Agronomy48:73-77.

Brar BS and Dhillon NS (1999) Integrated use of farm yardmanure, biogas slurry and inorganic phosphate in Pnutrition of wheat. Journal of the Indian Society of SoilScience 47: 264-267.

Chapman HD and Prett PF (1961) Soil, Water and PlantAnalysis. Univ. California, Riverside, AgricultureDivision Publication, CA, USA.

Debebe Y (2013) Comparative study on the effect of applyingbiogas slurry and inorganic fertilizer on soil properties,growth and yield of white cabbage (Brassica oleracea var.capitata f. alba) at Sebeta Hawas Woreda, South WestShewa zone. M. Sc. (Environmental Sci.) Thesis AddisAbaba University South West Shewa zone.

Dwivedi DK and Thakur SS (2000) Production potential ofwheat (Triticum aestivum) crop as influenced by residual

organics, direct and residual fertility levels under rice(Oryza sativa)-wheat cropping system. Journal ofAgronomy 45: 641-647.

Garg RN, Pathak K, Tomar H and Das DK (2005) Use offlyash and biogas slurry for improving wheat yield andphysical properties of soil. Environmental Monitoring andAssessment 107:1-9.

Handway JJ and Heidal H (1952) Analysis method as usedin lowa state college soil testing laboratory. Bulletin ofthe Iowa State College of Agriculture 57:1-131.

Jackson ML (1973) Soil Chemical Analysis. Prentice Hall, IndiaPvt. Ltd., New Delhi.

Li Y, Sheng K, Peng S, Meng Z and Dong Z (2014) Effectsof Biogas Slurry on Wheat Yield and the Physical andChemical Properties of Soil. Chinese Agriculture ScienceBulletin pp 181-186

Maskey SL, Bhattarai S and Karki KB (2004) Long-termeffect of different sources of organic manures on Wheat-Soyabean rotation. SAARC Journal of Agriculture 2: 243-256.

Mandal AK, Sharma RC, Singh G And Dagar JC (2010)Computarized Database on Salt Affected Soils in India.Technical Bulletin, Central Soil Salinity Research InstituteKarnal.

More SD (1994) Effect of farm wastes and organic manureon soil properties, nutrient availability and yield of rice-wheat grown on sodic Vertisols. Journal of the IndianSociety of Soil Science 42: 253-256

Nasir A, Usman K M, Munir A, Anwar S, Arslan CH andAjhar AM (2015) Comparative study of mechanicallydried biogas slurry and commercial fertilizer. Journal ofResearch in Engineering and Technololy 1:81-88.

Olsen SR, Cole CV, Watanabe FS and Dean LA (1954)Estimation of available phosphorus by extraction withsodium carbonate. U.S. Dept. Agriculture Circulation

Tiwari VN, Tiwari KN and Upadhyay RM (2000) Effect ofcrop residues and biogas slurry incorporation in wheaton yield and soil fertility. Journal of the Indian Society ofSoil Science 48: 515-520.

Richards LA (1954) Diagnosis and Improvement of Saline andAlkaline Soils. U.S. Dept. Agriculture Handbook No.60,Washington, D.C.

Subbiah BV and Asija HL (1956) A rapid procedure for theestimation of the available nitrogen in soils. CurrentScience 25: 259-60.

Walkley A and Black CA (1934) An examination of theDegtjareff method for determination of soil organicmatter and a proposed modification of the chromic acidtitration method. Soil Science 37: 29-39.

Received in May, 2017; Accepted in August, 2017

Effect of Fertigation on Nitrogen Use Efficiency andProductivity of Tomato Utilizing Saline Water through

Drip Irrigation

Narender Kumar*, RK Jhorar, Sanjay Kumar, Rajpaul Yadav, Ram Prakashand Amandeep Singh

CCS Haryana Agricultural University, Hisar-125004, Haryana, India*Corresponding author E-mail: [email protected]

Abstract

Proper management of water and fertilizers is of paramount importance for crop production and efficientmanagement of marginal quality waters. The present study was conducted to examine the effect of differentnitrogen fertigation level on tomato crop utilizing saline (ECiw ≈ 2.5 dS m-1) water through drip irrigation. Allthe nutrients and 1/3rd of nitrogen were applied before transplanting the tomato. Remaining dose of nitrogenwas divided equally in 11 doses and applied at weekly interval through drip. Soil moisture and salinity in thesoil profile of different treatments were recorded at fortnight interval. Irrigation with saline water led to rapidaccumulation of salts in the soil at the horizontal distance of 20 cm compared to good-quality water. Thetomato yield under good-quality water irrigation with N-fertigation of 100 kg ha-1 and 125 kg ha-1 was statisticallyat par but significantly higher than that at N-fertigation of 75 kg ha-1. Water use efficiency (WUE) increased by37.9 and 48.3 %, when N- fertigation level increased from 75 to 100 kg ha-1 for irrigation with good and salinewater, respectively. Nitrogen use efficiency (NUE) increased when N-fertigation level increased from 75 to 100kg ha-1 and thereafter, it declined at 125 kg ha-1. The increased N-fertigation level did not significantly improvethe tomato yield and WUE but reduced the NUE.

Key words: Drip irrigation, Fertigation, Nutrient-use-efficiency, Saline water, Tomato, Water-useefficiency

Introduction

Irrigation is essential for crop production in aridand semi-arid regions. However, it is being felt thatthe irrigated agriculture is facing the problem ofwater scarcity. Not enough water of good-qualityis available to irrigate whole of cropped area ofthe country. Therefore, it is imperative to usemarginal quality water for irrigation. Likeirrigation, nutrient supply is also important forcomplete yield potential of different crops. Dripirrigation, due to its capability to apply small andfrequent amounts of fertilizers dissolved inirrigation water (fertigation), also promises toapply fertilizers with high fertilizer-use-efficiency.In fertigation, nutrient-useefficiency could be ashigh as 90% compared to 40-60% in conventionalmethod mainly due to decreased leaching ofnutrients under drip irrigation (Solaimalai et al.,2005). It is also considered as suitable option toutilize marginal quality water for crop productiondue to movement of salt away from effective root

zone. Irrigation with poor-quality groundwater,if feasible, can reduce the demand of fresh waterfor irrigation, reduce volume of drainage effluents,and may help to check rise of saline groundwatertable thereby reducing the risk of secondary soilsalinization in affected areas.

Tomato is an important, remunerative andnutritive vegetable grown in India. Tomato isconsidered moderately sensitive to salt stress, sinceit can tolerate an ECe (EC of the saturated soilextract) of about 2.5 dS m-1 and fruit yield decreaseby 10% with each unit of ECe increasing abovethe threshold value (Maas, 1986). In order tofacilitate the safe use of saline water for tomatothrough drip irrigation, the effect of quality ofirrigation water on crop production need to beunderstood. Moreover, it is also important toidentify suitable fertigation strategy for tomatocrop irrigated with saline irrigation. The abilityof drip irrigation to apply water as and when


206 Kumar et al.

required, supply the plant nutrients on demandoffer an opportunity for the use of saline waterfor crop production. It also has great scope forefficient resource management. The present studywas planned to study the response of differentlevels of nitrogen application on tomato crop andto work out suitable nitrogen fertigation dose fortomato crop by using saline water under dripirrigation.


Experiment with two water quality (G, good waterof EC 0.4 dS m-1 and M, saline water of EC 2.5dS m-1) and three nitrogen fertigation level (N1 =75 % RDN (Recommended dose of nitrogen), N2=100 % RDN and N3= 125 % RDN) was carriedout in micro-plots (2 m x 2 m) at Soil ScienceResearch Farm of CCS HAU, Hisar duringFebruary, 2015 to May, 2015. The recommendeddose of nitrogen, phosphorous and potash was100, 50 and 5 kg ha-1, respectively. FYM (8 kg perplot), 100% of P, K and 1/3rd of N were appliedbefore transplanting the tomato. Remaining doseof nitrogen was divided equally in 11 doses andapplied after one month of transplanting at weeklyinterval. Hoeing practice was done in the micro-plots for proper mixing of FYM and the chemicalfertilizer in the soil. Soil of the experimental sitewas having 75.3, 12.3 and 12.4 per cent of thesand, silt and clay, respectively. Bulk density ofthe soil was 1.42 g cm-3, whereas, the organiccarbon and nitrogen present in the soil were 0.25%and 107 kg ha-1. The initial pH of the soil profile(0-15, 15-30, 30-45 and 45-60 cm) irrigated withgood-quality water was 8.02, 7.98, 8.13 and 8.13,respectively, whereas, these values under salinewater were 8.12, 8.08, 8.25 and 8.29. The initialEC1:2 (dS m-1) of the soil profile (0-15, 15-30, 30-45 and 45-60 cm) irrigated with good quality waterwas 0.32, 0.37, 0.40 and 0.41, respectively,whereas, these values under saline water were0.45, 0.48, 0.49 and 0.52 dS m-1. Aftertransplanting the plants in micro-plots, irrigationwas imposed at alternate day based on theprevious two days pan evaporation, cropcoefficient, plant spacing and area shaded by crop.The volume of irrigation water to be applied perplant during an irrigation event was calculated asunder (adopted from Schwab et al.,1993):

Where, V- amount of water applied (ml plant-1),Ep – sum of evaporation of last two days (mm),Kc- crop coefficient, Kp- pan coefficient (0.85),PP- plant to plant spacing (cm), RR- row to rowspacing (cm), Ea- irrigation efficiency (90%), andP- % of area shaded by crop (minimum value wastaken as 15%)

Electrical conductivity and soil moisturecontent were determined in soil profile at 15 daysinterval after transplanting of the crop. Soilsamples from each treatment were collected from0-15, 15-30, 30-45 and 45-60 cm depth at a radialdistance of 10 and 20 cm from the plant. By usingSurfer software, spatial and temporal movementcurves of moisture content and salinity wereprepared. Plant height and crop yield parameterswere measured at different growth period fortomato crop. Tomatoes were picked and weighedfrom each plots during different picking. Cropyield was recorded according to harvesting datein different treatments of nitrogen fertigation.Water use efficiency (WUE) represents therelation between yield and irrigation water. WUEof different treatments was calculated in term offruit yield per hectare to the amount of waterapplied. Nitrogen use efficiency (NUE) representsthe relation between yield and amount of nitrogenapplied. NUE of different treatments wascalculated in term of fruit yield per hectare to theamount of nitrogen applied by the followingformula:


During the cropping season, 948.40 liters ofirrigation water (24 cm) was applied to each micro-plot. Spatial and temporal movement curves ofmoisture content and salinity are shown in Figures1, 2, 3 and 4 at 30, 60 and 90 days aftertransplanting (DAT). As expected the averagemoisture content at the horizontal distance of 10cm was more than at the horizontal distance of20 cm. However, the difference in moisturecontent at the horizontal distance of 10 and 20cm narrowed down with the advancement of the

Effect of nitrogen fertigation on tomato 207

75% of Recommended doseof nitrogen



30 DAT*

Fig. 1. Spatial and temporal movement of moisture content with different doses of fertigation with good-quality water (* daysafter transplanting)

60 DAT

90 DAT

208 Kumar et al.

growing season (Fig. 1 and 2). The moisturecontent at the corresponding depths was alwaysmore at 10 cm distance than that at 20 cm distance.This is due to smaller travel distance for water frompoint of application to the corresponding depthsat 20 cm distance. But the average moisturecontent for 60 cm soil depth at 10 cm horizontaldistance decreased while it increased at 20 cm withthe growing season. The decrease in soil moistureat a distance of 10 cm, despite regular irrigation,indicates active water uptake by the crop in thevicinity of the plant.

Moisture content at 10 cm distance was alwaysmore under saline water irrigation treatments thanunder good quality water irrigation treatments forthe corresponding depths (Figs. 1 and 2). Themoisture content in the 60 cm soil profile was alsohigher under irrigation with saline water ascompared to irrigation with good quality water.Higher moisture content under irrigation withsaline water may be due to possible decrease inET of the crop due to the increased osmoticpotential in the soil profile when irrigated withsaline water as compared to when irrigated withgood quality water. Average moisture contentduring the growing season was only slightlyaffected by the fertigation levels of nitrogen withslight decrease in moisture content with increasinglevels of nitrogen application. Effect of nitrogenfertigation level on average moisture content wasnegligible for irrigation with saline water.

Depth wise EC1:2 of soil at different periodsduring the growing season for good and salineirrigation water are shown in Fig. 3 and 4,respectively. In good quality irrigation, averageEC1:2 at the horizontal distance of 10 cm showeda decreasing trend with the growing season,demonstrating the capability of drip irrigation topush the salts away from the point of applicationtowards the outer periphery of the wetted zone.Soil salinity at the horizontal distance of 20 cmshowed an increasing trend for both good andsaline irrigation treatment, indicating thereby themovement of salts outwards from the point ofwater application. The observed average EC1:2 ofthe soil profile for irrigation with saline water weremore than that of good quality water. Two reasonsmay be attributed to higher EC1:2 of soil whichreceived saline water irrigation: i) these plots were

already being irrigated with saline water for on-going long term experiments, hence, the initialsalinity was higher in these plots, ii) relativelyhigher salt load of saline water used duringexperimentation. The final difference in averagesoil salinity at the horizontal distance of 10 and20 cm was less in saline water than the goodquality water. It can also be observed from Figures3 and 4 that, irrigation with marginal water qualityled to more rapid accumulation of salts in the soilat the horizontal distance of 20 cm distance thanthat observed for irrigation with good qualitywater. Effect of nitrogen fertigation levels on soilsalinity was non-significant.

In general, the height of tomato plant irrigatedwith good-quality water was more than thatirrigated with saline water at the correspondinglevels of N (Table 1). As expected, observed plantheight at 90 DAT was higher for higher level ofunder both water quality. Highest and lowest plantheight was observed for treatments GN3 and MN1,respectively. Higher N levels were more effectivein increasing plant height for irrigation with goodquality water as compared to irrigation with salinewater. Similarly, average fruit weight was higherunder good quality water irrigation in therespective treatment of N-fertigation. Amongdifferent treatment of fertigation in good qualitywater, maximum fruit weight was observed in GN2

treatment and in saline water, it was observed inMN2 treatment.

In good-quality water irrigation, highest cropyield (61.53 Mg ha-1) was obtained in GN3 andlowest yield (43.25 Mg ha-1) was found in GN1

(Table 1). In saline water (ECiw 2.5 dS m-1)irrigation, highest crop yield (50.54 Mg ha-1) wasobtained in MN3 and lowest yield (34.68 Mg ha-1)was obtained in MN1. Nutrient supply is knownto affect the crop yield. Yield of tomato alsoincreased with increasing levels of N-fertigation.At the corresponding levels of N-fertigation,higher tomato yield was obtained under good-quality water irrigation treatment as compared tothe saline water. However, the tomato yield undergood-quality water irrigation with N-fertigationof 100 kg ha-1 and 125 kg ha-1 was statistically atpar but significantly higher than that at N-fertigation of 75 kg ha-1. Likewise, the tomato yieldunder saline water irrigation with N-fertigation


Fig. 2. Spatial and temporal movement of moisture content with different doses of fertigation with saline water (* days aftertransplanting)




30 DAT*

60 DAT

90 DAT

210 Kumar et al.

Fig. 3. Spatial and temporal movement of salt content with different doses of fertigation under good- quality water (* days aftertransplanting)




30 DAT

60 DAT

90 DAT


Fig. 4. Spatial and temporal movement of salt content with different doses of fertigation under saline water (* days after transplanting)




30 DAT

60 DAT

90 DAT

212 Kumar et al.

of 100 kg ha-1 and 125 kg ha-1 was statistically atpar but significantly higher than that at N-fertigation of 75 kg ha-1. These findings are inagreement with earlier reports showing decreasein yield of tomato with increasing salinity ofirrigation water (Kadam and Patel, 2001, Sanchezet al., 2005).

Estimated value of water-use-efficiency(WUE) and nitrogen-use-efficiency (NUE) is givenin Table 1. Maximum WUE (26.0 kg m-3) wasobserved in GN3 treatment and minimum WUE(14.3 kg m-3) in MN1 treatment. Significantimprovement in WUE was observed with N-fertigation level increased from 75 to 100% ofRDN. WUE increased by 37.9 and 48.3% for 75to 100% of RDN for irrigation with good andsaline water, respectively. Therefore, efficient waterapplication method coupled with proper nutrientsupply is essential to realize a higher level ofWUE. At a given level of N-fertigation, WUE washigher for irrigation with good quality water ascompared to saline water.

Similar to WUE, at a given level of N-fertigation, nitrogen use efficiency (NUE) washigher for irrigation with good quality water ascompared to irrigation with saline water (Table1). The maximum NUE (594.9 kg of tomato perkg of Nitrogen) was obtained in GN2 andminimum NUE (404.3 kg of tomato per kg ofNitrogen) was obtained in MN3 treatment. NUEincreased when N-fertigation level increased from75 to 100% of RDN and thereafter it decreasedas N-fertigation level increased from 100 to 125%of RDN. Therefore, maximum NUE, for bothgood and saline water was obtained at N-fertigation level corresponding to RDN. Increased

N-fertigation level supply beyond RDN did notsignificantly improved the tomato yield and WUEbut reduced the efficiency of NUE.

Conclusion

Higher profile moisture content was observed forirrigation with saline water as compared toirrigation with good-quality water. Averagemoisture content during the growing season wasonly slightly affected by the fertigation levels ofnitrogen with slight decrease in moisture contentwith increasing levels of nitrogen application. Dripirrigation pushed the salts away from the point ofapplication and electrical conductivity (EC1:2) ofsoil at the horizontal distance of 10 cm was lessthan that at the horizontal distance of 20 cm. Theincreased N-fertigation level supply beyond RDNdid not significantly improved the tomato yieldand WUE but reduced the efficiency of NUE.

ReferencesKadam JR and Patel KB (2001) Effect of saline water through

drip irrigation system on yield and quality of tomato.Journal of Maharashtra Agricultural University 26 (1): 8-9.

Mass EV (1986) Salt tolerance of plant. Applied AgriculturalResearch 1: 12-26.

Sanchez A, Romero Aranda R and Cuartero J (2005) Plantwater uptake and water use efficiency of greenhousetomato cultivars irrigated with saline water. AgriculturalWater Management 78: 54-66.

Schwab GO, Fangmeir DD, Elliot, WJ and Frevert, KR(1993) Soil and Water Conservation Engineering. 4th ed.John Wiley & Sons Inc., New York.

Solaimalai A, Baskar M, Sadasakthf A and Subburamu K(2005) Fertigation in high value crops - A review.Agriculture Review 26: 1-13.

Received May, 2017; Accepted August, 2017

Table 1: Plant height, crop yield, water-use-efficiency (WUE) and nitrogen-use-efficiency (NUE) of tomato in different treatments

Treatment Average plant height (cm) Yield WUE NUE (kg of tomato30 DAT 60 DAT 90 DAT (Mg ha-1) (kg m-3) per kg of Nitrogen)

GN1 28.2 55.4 85.8 43.25 18.2 576.7GN2 27.8 54.8 89.6 59.49 25.1 594.9GN3 28.4 55.9 92.1 61.53 26.0 492.2MN1 25.7 51.7 83.5 34.68 14.3 462.4MN2 24.8 53.8 84.2 50.18 21.2 501.8MN3 25.9 56.8 87.7 50.54 21.3 404.3LSD (p ≤ 0.05) 2.25 2.80 3.94 7.62 2.7 81.8

GN1- good water (ECiw 0.4 dS m-1) + 75% RDN (recommended dose of nitrogen, GN2-good water + 100% RDN, GN3- good water +125% RDN, MN1- saline water (EC iw 2.5 dS m-1) + 75% RDN, MN2- saline water + 100% RDN, MN3 - saline water + 125% RDN

Effect of Laser Land Leveling on Crop Yield and WaterProduction Efficiency of Paddy (Oryza sativa) in Tungabhadra

Project Command

RH Rajkumar1*, J Vishwanatha1, SR Anand1, AV Karegoudar1,AT Dandekar2 and MJ Kaledhonkar3

1*AICRP on Management of Salt Affected Soils and Use of Saline Water in Agriculture,Agricultural Research Station, Gangavathi-583 227, Karnataka, India

2College of Agricultural Engineering, Raichur-584 104, Karnataka, India3ICAR-Cental Soil Salinity and Research Institute, Zarifa Farm, Kachhwa Road, Karnal-132 001, Haryana, India


Abstract

A study was conducted to know the effect of the laser land leveling on crop yield and water production efficiencyof paddy imposing four treatments viz., T1- puddled transplanting (PTR) in traditionally leveled land (control),T2 - direct seeded rice (DSR) in traditionally leveled land, T3 - PTR in laser leveled land, and T4 - DSR in laserleveled land. The quantum of irrigation water applied at each time for all the treatments was measured with cutthroat flume water measuring instrument. Highest plant height was recorded in PTR in laser leveled landwhich was on par with DSR in laser leveled land treatment. Among DSR and PTR treatments, number ofpanicles per m2 was more in case of laser land leveled treatments. Panicle length was higher in PTR with laserleveled treatment and was at par with DSR in laser leveled treatment and number of mature grains were foundmore in case of DSR in laser leveled land which was at par with PTR in laser leveled land. Highest paddy yieldwas recorded in PTR in laser leveled land treatment (5833 kg ha-1) which was statistically at par with DSR inlaser leveled land treatment (5682 kg ha-1). Water production efficiency was recorded higher in case of DSR inlaser leveled land treatment (0.58 kg m-3) and least in case of PTR in traditional leveled land (0.4 kg m-3). Thetotal irrigation water applied was 10.9% less in case of PTR in laser leveled land as compared to control i.e.,puddled transplanting in traditional leveled land. However, the total irrigation water applied was 23.2 and18.1% less in case of DSR in laser leveled land and DSR in traditional leveled land treatment, respectively ascompared to control treatment. The net returns and B:C ratio were found more in case of direct seeded rice inlaser leveled land treatment (` 80,972 per ha and 3.11) and least in case of PTR in traditional leveled land(` 62,618 per ha and 2.44).

Key words: Laser levelling, Yield, Direct seeded rice, Puddled transplanting, Water production efficiency, Benefitcost ratio

Introduction

Water is one of the most important inputs for cropproduction. Declining water table and degradingsoil health are the major concerns for the currentgrowth rate and sustainability of IndianAgriculture. Thus, proper emphasis is being givenon the management of irrigation water usage foradequate growth of agriculture. Keeping in view,the need for judicious use of our natural resources,concerted efforts are being made to enlighten thefarmers for efficient use of irrigation water at farmlevel (Kaur et al., 2012). Generally, in wheat andrice crops, farmers believe that their fields are

leveled and needed no further leveling. But thedigital elevation survey sheet of a field shows thatmost of the fields are not adequately leveled andfurther precision land leveling is required. Theenhancement of water use efficiency and farmproductivity at field level is one of the best optionsto readdress the problem of declining water level.

Rice is the important crop of TungabhadraProject (TBP) command area, though only 8.6%(29,032 ha) of the TBP command has beenearmarked for paddy cultivation. Recently it hasbeen increased to more than 70% (2,55,366 ha)(Anonymous, 2013) and in all these cases, rice is


214 Rajkumar et al.

traditionally grown by transplanting underpuddled fields. For this puddling operation,farmers in this area are going for intensive tillageunder continuous ponded water nearly 10 cmthroughout the season, which serves to breakdown soil aggregates, reduced macro-porosity,dispersed clay fraction, and farming dense zoneof compaction at depth. In this method, thefarmers are using excessive irrigation water andfertilizers with unscientific method, which isleading to wastage of precious natural resourcei.e. water and land becoming degraded bywaterlogging and salinity. It has been estimatedthat 96,125 ha land has been affected by salinityand waterlogging in TBP command. In thiscommand area, around 20-30% of the total waterrequired for the rice cultivation is being used bythe farmers to nursery raising, puddling andtransplanting.

The water availability during Kharif and lateRabi is a biggest problem in tail end region. Thedirect seeded rice (DSR) will facilitate betterestablishment of second crop in Rabi for tail endfarmers. There are few reports evaluatingmulching for rice, where 20-90% input watersavings and weed suppression occurred withplastic and straw mulches in combination withDSR compared with continuously floodedtransplanting rice (Lin et al., 2003). Presently, thefarmers of this region use traditional methods (viz.tractor operated bucket leveler) of land levelingwhich are good enough to meet only the partialrequirement of land leveling. It still leaves thescope of improvement in land leveling in the field.

Laser land leveling is one such importanttechnology for using water efficiently as it reducesirrigation time and enhances productivity not onlyof water but also of other non-water farm inputs.It does not only minimize the cost of leveling butalso ensures the desired degree of precision. Itenables efficient utilization of scarce waterresources through elimination of unnecessarydepression and elevated contours (Naresh et al.,2011). It has been noted that poor farm designand uneven fields are responsible for 30% waterlosses (Asif et al., 2003). Precision land leveling(PLL) facilitates application efficiency througheven distribution of water and increases water-

use efficiency that results in uniform seedgermination, better crop growth and higher cropyield (Jat et al., 2006). Under these circumstances,PLL can help the farmers to utilize the scarce landand water resource more effectively and efficientlytowards increased crop production (Abdullaev etal., 2007). It was estimated that around 25 to 30%of irrigation water could be saved through thistechnique without having any adverse effect onthe crop yield (Bhatt and Sharma, 2009). Keepingthis in view, this study was undertaken with theobjective to access the effect of laser land levelingon water use and productivity under differentmethods of cultivation of paddy crop (Puddledtransplanting, PTR and Direct seeded rice, DSR)by comparing it with the traditionally leveling andtheir economic feasibility.


The field experiment was conducted during Kharif2014-15 and 2015-16 at Agricultural ResearchStation, Gangavathi, Karnataka; situated in thenorth-eastern dry zone of the state with latitudeof 15°15′41′′ N and longitude of 76°31′40′′ E andat an altitude of 419 m above mean sea level. Thesoil of the site was medium deep black soil whichwas determined by international pipette method(clay, silt and sand 47.6, 29.5 and 22.9%,respectively). The infiltration rate of theexperimental site was 14 mm h-1 and determinedby double ring infiltrometer (Manjunatha et al.,2002). Average annual rainfall of the station is537.7 mm. During Kharif 2014-15 and 2015-16the rainfall during the growing season of paddywas 228.3 and 240.8 mm, respectively. The ECeof the soil of the experimental site was determinedusing conductivity bridge in 1:2.5 soil waterextract. It ranged between 1.25 to 1.45 dS m-1 andpH less than 8.3. The mean bulk density and soilporosity ranged between 1.44 to 1.56 gm cc-1 and42.2 to 47.5%, respectively and was measured bycollecting a known volume of soil using a metalring pressed into the soil (intact core), anddetermined the weight after drying (McKenzie etal., 2004). The soil porosity ranged from 42.2% to47.5% which was determined by % solid space(bulk density /particle density × 100) and %porosity was then calculated by 100 - (% solidspace). Four treatments were imposed viz. T1 -

Effect of laser land leveling on crop yield and water production efficiency 215

puddled transplanting (PTR) in traditional leveledland (control), T2 - direct seeded rice (DSR) intraditional leveled land, T3 - puddled transplantingin laser leveled land, and T4 - direct seeded rice inlaser leveled land in four plots with an area of0.971, 0.323, 0.0849 and 0.315 ha, respectively.For the laser leveling treatment (T3 and T4), theavailable laser leveler at Gangavati Station wasused for leveling the plots and for direct seededrice treatments (T2 and T4), with available multi-crop seed drill was used for sowing. For DSRmethod 0.225 m was kept as row to row distanceand for PTR method traditional practice wasfollowed. Before implementation of theexperiments, the slopes of the four plots wasmeasured which were approximately 0.2 to 0.25%and lands were well prepared. The quantum ofirrigation water applied at each time for all thefour treatments was measured with cut throatflume water measuring instrument. The dischargeavailable at outlet was measured every time. Thetime of irrigation application for differenttreatment was noted during each irrigation. Theapplied irrigation depth was calculated frommeasured discharge applied to known area forrecorded time by the following equation:

QT=AD

Where Q = Discharge (m3 s-1); T = Time (s); A =Area (ha), and D = Depth (m).

The amount of water (m3) applied to eachtreatment was determined by multiplying thedischarge at field outlet with the time ofapplication. The total amount of water appliedwas computed for the entire crop season for allthe four treatments. Water use efficiency (WUE)was computed by the formula: WUE (kg m-3) =Yield (kg ha-1) / Total water applied (mm).

Growth and yield observations were recorded atharvest.


Growth and yield parameters

The pooled data over two years (2014-15 and 2015-16) indicated that highest plant height wasrecorded in puddled transplanting in laser leveledland which was at par with direct seeded rice inlaser leveled land treatment. Among DSR andPTR treatments, numbers of panicles per m2 werefound more in case of laser land leveled treatments(Table 1). Among four treatments, more paniclelength was found PTR with laser leveled treatmentand was at par with DSR in laser leveled treatmentand number of good mature grains were foundhigher in case of direct seeded rice in laser leveledland treatment and which was at par with PTR inlaser leveled land (Table 2). Highest paddy yieldwas recorded in puddled transplanting in laserleveled land treatment (5833 kg ha-1) which wasat par with direct seeded rice in laser leveled landtreatment (5682 kg ha-1) (Table 3). The aboveresults are in line with the findings of Naresh etal. (2014).

Water use and water production efficiency

Tables 4 and 5 show the amount of irrigationapplied, rainfall, effective rainfall and totalirrigation applied for different methods. Theirrigation applied and total irrigation applied washigher in case of puddled transplanting intraditional leveled land (1272.2 mm) followed bypuddled transplanting in laser leveled land (1133.2mm), direct seeded rice in traditional leveled land(1041.7 mm) and least in case of direct seededrice in laser leveled land (977.2 mm). The totalirrigation water applied was 10.9% less in case of

Table 1. Effect of laser leveling and DSR on plant height and number of panicles of paddy

Sl. Treatments Plant height (cm) No. of panicles per m2

No. 2014-15 2015-16 Pooled 2014-15 2015-16 Pooled

1 T1 - PTR in traditionally leveled land (Control) 89.5 88.1 88.8 363 358 3412 T2 - DSR in traditionally leveled land 92.3 90.8 91.5 362 366 3693 T3 - PTR in laser leveled land 97.8 97.4 97.6 388 382 3894 T4 - DSR in laser leveled land 95.6 96.3 95.9 402 395 396

S.Em± 1.10 1.32 1.23 16 18 15LSD (p ≤ 0.05) 3.45 4.16 3.65 45 53 48

216 Rajkumar et al.

Table 2. Effect of laser land leveling on panicle length and number of good grains per panicles under PTR and DSR

Sl. Treatments Panicle length (cm) No of good grains per panicle

No. 2014-15 2015-16 Pooled 2014-15 2015-16 Pooled

1 T1 - Control 17.6 19.7 18.7 146 165 1562 T2 - DSR in traditionally leveled land 19.4 20.3 19.8 158 174 1663 T3 - PTR in laser leveled land 20.4 22.2 21.3 184 187 1884 T4 - DSR in laser leveled land 19.8 21.9 20.8 189 196 190

S.Em± 0.42 0.35 0.28 05 04 5LSD (p ≤ 0.05) 1.45 1.08 0.92 16 13 17

Table 3. Paddy yield as influenced by laser land leveling and DSR

Sl. Treatments Yield (kg ha-1)

No. 2014-15 2015-16 Pooled

1 T1 - PTR in traditional leveled land 4792 5320 50562 T2 - DSR in traditional leveled land 4570 5215 48933 T3 - PTR in laser leveled land 5488 6177 58334 T4 - DSR in laser leveled land 54.04 5960 5682

S.Em± 186 136 128LSD (p ≤ 0.05) 525 475 465

Table 4. Analysis of irrigation water application and rainfall between PTR and DSR in traditional leveled and laser leveled land

Sl. Treatments Irrigation applied (m3 ha-1) Rainfall (RF) during growing season (mm)

No. 2014-15 2015-16 Pooled 2014-15 2015-16 Pooled

1 T1 - PTR in traditional leveled land 1091 1172 1131.5 228.3 240.8 234.62 T2 - DSR in traditional leveled land 892 910 901 228.3 240.8 234.63 T3 - PTR in laser leveled land 967 1018 992.5 228.3 240.8 234.64 T4 - DSR in laser leveled land 793 880 836.5 228.3 240.8 234.6

S.Em± 25 12 18LSD (p ≤ 0.05) 82 26 57

Table 5. Total irrigation water applied for PTR and DSR in traditional leveled and laser leveled land

Sl. Treatments Effective RF (mm) Total irrigation applied (mm)

No. 2014-15 2015-16 Pooled 2014-15 2015-16 Pooled

1 T1 - PTR in traditional leveled land 137 144.5 140.7 1228 1316.5 1272.22 T2 - DSR in traditional leveled land 137 144.5 140.7 1029 1054.5 1041.73 T3 - PTR in laser leveled land 137 144.5 140.7 1104 1162.5 1133.24 T4 - DSR in laser leveled land 137 144.5 140.7 930 1024.5 977.2

puddled transplanting in laser leveled land ascompared to control. However, the total irrigationwater applied was 23.2 and 18.1% less in case ofdirect seeded rice in laser leveled land and directseeded rice in traditional leveled land treatment,respectively as compared to control treatment(Table 6). Water production efficiency wasrecorded higher in case of direct seeded rice in

laser leveled land treatment (0.58 kg m-3) and leastin case of puddled transplanting in traditionalleveled land (0.4 kg m-3) (Table 7).

Economic feasibility of laser leveling and DSR inTBP command

The cost of cultivation, gross return, net returnsand benefit cost ration are presented in Table 8.

Effect of laser land leveling on crop yield and water production efficiency 217

Table 6. Percent of total less water applied in different treatment than control

Sl. Treatments Total less water applied in Percent of less water applied inNo. different treatment than control different treatment than control

2014-15 2015-16 Pooled 2014-15 2015-16 Pooled

1 T1 - PTR in traditional leveled land (control) _ _ _ _ _ _2 T2 - DSR in traditional leveled land 199 262 230.5 16.2 19.9 18.13 T3 - PTR in laser leveled land 124 154 139 10.1 11.7 10.94 T4 - DSR in laser leveled land 298 292 295 24.3 22.2 23.2

Table 7. Water production efficiency as influenced by laser land leveling and DSR

Sl. Treatments WPE (kg m-3)No. 2014-15 2015-16 Pooled

1 T1 - PTR in traditional leveled land 0.39 0.40 0.402 T2 - DSR in traditional leveled land 0.44 0.49 0.473 T3 - PTR in laser leveled land 0.50 0.53 0.514 T4 - DSR in laser leveled land 0.58 0.58 0.58

S.Em± 0.02 0.01 0.022LSD (p ≤ 0.05) 0.65 0.04 0.07

Table 8. Economic feasibility of laser leveling technology in PTR and DSR method

Sl. Treatments Cost of Gross return Net returns B:CNo. cultivation (` ha-1) (` ha-1) ratio

(` ha-1)

1 T1 - PTR in normal leveled land 43558 106176 62618 2.442 T2 - DSR in normal leveled land 35850 102743 66893 2.873 T3 - PTR in laser leveled land 46058 122483 76425 2.664 T4 - DSR in laser leveled land 38350 119322 80972 3.11

S.Em± - - 1232 0.01LSD (p ≤ 0.05) - - 3567 0.32

The cost of cultivation and gross returns weremore in PTR with laser leveled land and least incase of DSR in traditional leveled land,respectively. Among four treatments the netreturns (` 80,972 per ha) and B:C ratio (3.11) werefound more in case of direct seeded rice in laserleveled land treatment and least in case of puddledtransplanting in traditional leveled land (` 62,618per ha and 2.44). The above results are in line withthe findings of Naresh et al. (2014).

Conclusions

Highest paddy yield was recorded in puddledtransplanting in laser leveled land treatment (5833kg ha-1) which is on par with direct seeded rice inlaser leveled land treatment (5682 kg ha-1). Waterproduction efficiency was recorded higher in case

of direct seeded rice in laser leveled land treatment(0.58 kg m-3) and least in case of puddledtransplanting in traditional leveled land (0.4 kgm-3). The total irrigation water applied was 10.9%less in case of puddled transplanting in laserleveled land as compared to control (puddledtransplanting in traditional leveled land).However, the total irrigation water applied was23.2 and 18.1% less in case of direct seeded ricein laser leveled land and direct seeded rice intraditional leveled land treatment respectively ascompared to control treatment (puddledtransplanting in traditional leveled land). Amongfour treatments, the net returns (` 80,972 per ha)and B:C ratio (3.11) were found more in case ofdirect seeded rice in laser leveled land treatmentand least in case of puddled transplanting in

218 Rajkumar et al.

traditional leveled land (` 62,618 per ha and 2.44).In conclusion, before going for the DSR methodof sowing in TBP command, the land should beleveled with laser leveling and then paddy can besown with seed drill. This in turn helps in attaininguniform seeding depth and smooth operation ofthe seed drill. With laser leveling around 20-25%water can be saved mainly due to smooth and levelland which in turn helps in reducing of irrigationapplication time. This technology will help thefarmers by reducing the land to becomewaterlogged and ensure in-time availabilityof canal water for the tail enders of commandarea.

Acknowledgements

We express our sincere gratitude to theGovernment of Karnataka for sanctioning of theproject and giving financial support to conductthe experiment and for demonstration of laserleveling technology and DSR methods inHyderabad Karnataka region. This technologywas recently introduced in TBP command areaalso and there was excellent response from thehead reach and tail end farmers of the commandarea.

References

Abdullaev I, Husan MU and Jumaboev K (2007) Watersaving and economic impacts of land leveling: The casestudy of cotton production in Tajikistan. IrrigationDrainage Systems 21: 251-263.

Anonymous (2013) Annual Report. CADA (Command AreaDevelopment Authority) Tungabhadra Project,Munirabad. Karnataka, India, pp22-30.

Asif M, Ahmed M, Gafool A and Aslam Z (2003) Wheatproductivity land and water use efficiency bytraditionally and laser land-leveling techniques. On lineJournal of Biological Sciences 3(2): 141-146.

Bhatt R and Sharma M (2009) Laser Leveller for Precision LandLeveling for Judicious Use of Water in Punjab, Extension

Bulletin, Krishi Vigyan Kendra, Kapurthala, PunjabAgricultural University, Ludhiana , 23p.

Jat ML, Chandna P, Gupta RK, Sharma SK and Gill MA(2006) Laser Land Leveling: A Precursor Technology forResource Conservation, Rice-Wheat Consortium. TechnicalBulletin Series 7. Rice-Wheat Consortium for the Indo-Gangetic Plains, New Delhi. 48p.

Jat ML, Gathala MK, Ladha JK, Saharawat YS and RajGupta (2009) Evaluation of precision land leveling anddouble zero-till systems in the rice-wheat rotation: Wateruse, productivity, profitability and soil physicalproperties. Soil and Tillage Research 105(1): 112-121.

Kaur B, Singh S, Garg BR, Singh JM and Singh-Singh J(2012) Enhancing water productivity through on-farmresource conservation technology in Punjab agriculture.Agricultural. Economic Research Review 25(1): 79- 85.

Lin XQ, Chen HX, Cheng SH and Uphoff N (2003) Effectof plant density and nitrogen fertilizer rates on grainyield and nitrogen uptake of hybrid rice (Oryza sativaL.). Journal of Agricultural Biotechnology and SustainableDevelopment 1(3): 44-53.

Naresh RK, Gupta Raj K, Kumar A, Prakesh S, Tomar SS,Singh A, Rathi RC, Misra AK and Singh Madhvendra(2011). Impact of laser leveler for enhancing waterproductivity in Western Uttar Pradesh. InternationalJournal of Agricultural Engineering 4(2):133-147.

Naresh RK, Singh SP, Misra AK, Tomar SS, Pardeep Kumar,Vineet Kumar and Sanjeev Kumar (2014) Evaluationof the laser leveled land leveling technology on crop yieldand water use productivity in Western Uttar Pradesh.African Journal of Agricultural Research 9(4): 473-478.

Manjunatha MV, Hebbara M, Patil, SG and Minhas PS(2002). Performance of multi-purpose tree species onsaline-waterlogged soils. Journal of the Indian Society ofSoil Science 50(1): 103-106.

McKenzie N, Jacquier D, Isbell R and Brown K (2004)Australian Soils and Landscapes. CSIRO Publishing,Clayton South VIC 3169, Australia, pp 5-6.

Wajid Ali Shahani, Feng Kaiwen and Aslam Memon (2016).Impact of laser leveling ecology on water use efficiencyand crop productivity in the cotton- wheat croppingsystem in Sindh. International Journal of Research 4(2):2394-3629

Received in June, 2017; Accepted in August, 2017

Direct Seeded Rice Followed by Zero Tillage Rapeseed IncreaseSystem Yield and Profitability in Coastal Saline Soils

Sukanta K. Sarangi1*, B Maji1, UK Mandal1, S Mandal1 and PC Sharma2

1ICAR-Central Soil Salinity Research Institute, Regional Research Station, Canning Town-743 329, West Bengal, India2ICAR-Central Soil Salinity Research Institute, Karnal-132001, Haryana, India


Abstract

Field experiment was conducted on coastal saline clay soil to evaluate three rice establishment methods viz. drydirect seeded rice (DSR), unpuddled transplanting (UNPT) and puddled transplanting (PT) followed by threerabi tillage practices for sowing rapeseed viz zero tillage (ZT), conventional tillage (CT) and raised bed sowing(RBS). DSR was sown on last week of May before the onset of monsoon and germination started with monsoonalrain in first to second week of June. Transplanting in the UNPT and PT plots were done during the first weekof July when the seedlings were 40 days old. Rice grain yields were statistically at par in three establishmentmethods (PT: 5.12 Mg ha-1, DSR: 4.74 Mg ha-1 and UNPT: 4.47 Mg ha-1). However, net return (` 36000 ha-1)and benefit cost ratio (2.2) was highest in DSR due to 26- 55% reduction in cost of cultivation. ZT helped in theearly sowing of rapeseed as a result it matured under favorable temperature conditions and produced significantlygreater seed yield (0.86 Mg ha-1) and net return (` 10820 ha-1). The system involving dry direct seeded ricefollowed by zero tilled direct sown rapeseed produced higher system rice equivalent yield (7.35 Mg ha-1), netreturn (` 48800 ha-1) and benefit cost ratio (1.98).

Key words: Direct seeded rice, Rapeseed, Brassica campestris, Economics, Oryza sativa, Puddling, Raised bed,Unpuddled transplanting, Raised bed sowing

Introduction

Rice (Oryza sativa L.) is the predominant cropduring kharif season in the coastal areas of India,however the productivity is low (<2 Mg ha-1) dueto several factors like soil salinity, drought and cropdamage by flooding due to heavy rain followingtransplanting. The events of flooding/submergence are more likely during the early cropgrowth just after transplanting. Prolonged partialflooding with 30 to 60 cm water depth reducesrice productivity because of high mortality,suppressed tillering, reduced panicle size and highsterility. Puddled transplanted rice has also anegative effect on soil structure and on subsequentrabi crop establishment. Gangwar and Singh(2010) observed that the system productivity ofrice-mustard cropping system was 12.45, 12.80,13.17 and 14.37 Mg ha-1 under puddled manualtransplanting, puddled mechanical transplanting,un-puddled mechanical transplanting, and drydirect seeding, respectively. Therefore, puddlingis not a pre-requisite for higher yield, rather it

deteriorates the physical properties of soil,adversely affects the performance of succeedingrabi crops and contributes to methane emissions.The method of dry direct seeding of rice duringkharif season as well as transplanting withoutpuddling has not been tested in a systemperspective under the coastal saline soil conditions.It can save inputs as well as ensure properestablishment of the crop.

During rabi season, most of the land remainsfallow in coastal areas due to scarcity of irrigationwater and salinity, which restricts the choice ofcrops to be grown. However, there is a potentialityof growing of low water requiring short durationrabi season oilseed crops like rapeseed (Brassicacampestris var. yellow sarson) having good marketdemand. Rapeseed is also a salt tolerant crop asthe threshold salinity (the maximum soil salinitythat does not reduce yield below that obtainedunder non-saline conditions) is 9.7 dS m-1. Sincethe winter season is very short in the coastal areas,to establish a good crop, proper tillage practices


220 Sarangi et al.

are essential. Keeping these facts in view thepresent study was conducted to find out suitablecrop establishment and tillage methods for rice-rapeseed cropping system in the low-lying salt-affected coastal land of West Bengal and to studythe effect in a system perspective on soil properties,productivity and profitability.


A field experiment was conducted in the researchfarm of ICAR-Central Soil Salinity ResearchInstitute, Regional Research Station, CanningTown (Latitude 22°15′ N, Longitude 88°40′ E,

altitude 3.0 m from average mean sea level) forthree years. The weather data for the experimentalperiod is given in Fig. 1 & 2. The total annualrainfall for 2013-14, 2014-15 and 2015-16 were2252.2, 1404.5 and 1915.2 mm, respectively. Therainiest month of the year was August (672.3 mm)and September (337.8 mm) for 2013-14 and 2014-15, respectively, whereas, July received the highestrainfall (838.4 mm) for 2015-16. The highest andlowest mean maximum temperature was 34.0 to35.5°C in May and 24.6 to 25.3°C in January,respectively. The highest and lowest meanminimum temperature was 26.7 to 27.4°C in May

Fig. 1. Monthly rainfall (mm) and soil salinity (dS m-1) recorded at ICAR-CSSRI, RRS, Canning Town during the three years ofexperimental period

Fig. 2. Monthly maximum and minimum air temperature (°C) recorded at ICAR-CSSRI, RRS, Canning Town during the threeyears of experimental period

Direct seeded rice and zero tillage rapeseed increase system yield 221

and 12.5 to 13.6°C in January, respectively.Experimental soil is heavy textured, with 43% clay,47% silt and 10% sand. The pH of top soil variedfrom 5.6 to 6.2, with initial bulk density of 1.47 gcm-3 and organic carbon status of 0.45%. Meansoil salinity, measured as electrical conductivityof saturation extract (ECe) was highest in May(14.3 dS m-1) and lowest in September (1.9 dSm-1). Available N, P and K were 152.7, 14.3 and287 kg ha-1 respectively.

Physico-chemical characteristics of theexperimental soil were determined from top soilsamples (0-15 cm) which were sun dried and sievedthrough a 2 mm sieve. Soil texture was determinedby hydrometric method (Bouyoucos, 1962).Twenty grams soil was taken in 100 ml beaker, 40ml distilled water was added, stirred well with aglass rod and after half an hour soil pH wasmeasured by a pH meter. Bulk density of soil wasmeasured in the experimental field by core samplermethod (Miller and Donahue, 1990) by usingmetal core sampler of 4.1 cm length and 5.6 cminternal diameter. The core sampler was insertedto the soil at desired depth by hammering and thentaken out along with soil. Excess soil from bothsides were cut by a sharp knife accurately. Sampleswere then oven dried at 105°C for 48 hours. Ovendried weight of soil (g) divided by the volume ofcore sampler (101.024 cm3) gave the soil bulkdensity (g cm-3). Soil salinity was measured interms of electrical conductivity of saturationextract (ECe) by Systronic Electrical ConductivityMeter (Jackson, 1973). Soil organic carbon,available nitrogen, available phosphorus andavailable potassium were determined by Walkleyand Black (1934), Subbiah and Asija (1956), Olsenet al. (1954) and Hanway and Heidel (1952)methods, respectively.

Three methods of kharif rice establishment viz.dry direct seeded rice (DSR), unpuddledtransplanting (UNPT) and puddled transplanting(PT) were taken in main plot; three tillage practicesviz. zero tillage (ZT); conventional tillage (CT) andmaking raised beds (RBS) for sowing rapeseedduring rabi season were evaluated in sub-plots.Experiment was conducted in split plot designwith nine treatments replicated thrice. DSR forkharif rice was done on last week of May in each

year before the onset of monsoon. On the daymonsoon rain started (mostly in the first to secondweek of June) nursery sowing was done for othertwo treatments. The rice variety ‘Amal-Mana’ apromising variety developed for growing duringkharif season in coastal saline areas (tolerates ECeof 6.0 to 8.0 dS m-1) frequently affected by stagnantfloods (25 to 50 cm) (Sarangi et al., 2016) was usedin the study. Transplanting was done in 20 cm ×15 cm spacing as per treatments. For DSR andUNPT treatments the field was ploughed onlyonce during summer by tractor in the mid of Mayand then sowing/transplanting was done in lines20 cm apart. In PT plots, in addition to summerploughing, two times ploughing was carried outusing power tiller, then puddling was done twiceand levelling was done before transplanting.

Sowing of ZT rapeseed was done in first weekof December immediately after harvest of kharifrice to use the residual soil moisture. CT consistedof ploughing the land after drying of the wet soil,followed by secondary tillage operations by powertiller. In RBS, sowing was done by making raisedbeds (60 cm bottom, 30 top width and 30 cmheight). Sowing under CT and RBS was delayed(first week of January) compared to ZT, as tillagewas done when soil moisture reached tillablecondition. Rapeseed (yellow sarson) variety‘Benoy’ (B 9) was used in the experiment, havingplant height of 90 to 95 cm, maturity duration of90 to 95 days, and average yield of 0.8 to 1.4 Mgha-1 with 46% oil content and suitable for coastalsaline conditions.

Depth of irrigation water (IW) applied (ha-cm) to rapeseed was calculated dividing thevolume of water applied by the area to whichirrigation water was applied. The irrigation waterproductivity (IWp) was computed by dividing theseed yield by the amount of irrigation waterapplied. Seed yield of rapeseed was converted intorice grain equivalent yield (REY) taking intoaccount the prevailing market price (rice = ̀ 11000Mg-1, rapeseed= ` 30500 Mg-1) and using theformula: REY = (seed yield × price of rapeseed)/price of rice grain. Soil organic carbon and bulkdensity were observed at the start of theexperiment in May 2013 and at the end of thirdkharif rice in November 2015. Data were subjected

222 Sarangi et al.

to an analysis of variance (ANOVA) with F-testand significant differences between treatmentswere compared by the use of least significantdifference (LSD) values calculated by the use ofstandard error of means.

Results and Discussions

Effect of kharif rice establishment methods onyield, economics and soil properties

There was non-significant variation of grain andstraw yields of kharif rice with differentestablishment methods (Table 1). However, netreturn and benefit cost ratio were significantlyhigher in DSR over other treatments. DSR didnot require seed bed preparation, puddling in thenursery as well as in the main field andtransplanting, therefore there was saving in costof cultivation. In case of UNPT, though nurserybed was prepared, it was transplanted withoutpuddling, which saved the cost in main fieldpreparation. Cost of cultivation was 26 and 55%more in PT than UNPT and DSR, respectively.

Kamboj et al. (2013) reported that UNPT inrice reduced cost of cultivation and produced 3 to11% higher grain yield over PT rice. With theincreasing cost of labour inputs, the method thatrequires less labour results in more profits. Netreturn was 38 and 56% more in DSR over UNPTand PT respectively. Due to lower cost ofcultivation, the BCR was significantly higher inDSR over UNPT and PT rice. Therefore,economics of kharif rice establishment methodsplay an important role in the decision making offarmers. DSR show clear economic advantagescompared with PT rice with a lower cost of

production (Kumar and Ladha, 2011). Afterharvest of third year kharif rice in November 2015,soil bulk density (BD) increased from initial valueof 1.47 to 1.56 g cm-3 due to the effect of puddling,however, it decreased to 1.29 and 1.40 g cm-3 inDSR and UNPT treatments, respectively. BDincreased significantly by 21 and 11% in PT plotscompared to DSR and UNPT plots, respectively.On the other hand soil organic carbon (SOC)increased from initial value of 0.45% to 0.56% inDSR treatment. SOC was significantly higher inDSR compared to UNPT and PT; also it washigher in UNPT over PT treatment. The soilsalinity in December (Table 1) after harvest ofkharif rice was significantly higher in PT plots (4.3dS m-1) compared to DSR (2.33 dS m-1) and UNPTplots (3.00 dS m-1), therefore due to puddling thesubsequent rabi crops are affected by salinity stress.Transplanting needs puddling, which has negativeeffect on soil physical properties, because there isdestruction of soil aggregates, clogging of macropores, formation of hard pan with consequentincrease in soil bulk density and lowering ininfiltration rate (Mousavi et al., 2009). Increase inBD due to puddling might be due to breakage ofsoil aggregates into finer particles, which remainsuspended in water and thereafter there isflocculation of particles leading to destruction ofmacro pores as well as shrinkage of soil at lowermoisture contents.

Yield components, yield, irrigation water use andeconomics of rapeseed

Rapeseed crop was significantly affected by kharifrice establishment methods (Table 2). DSRresulted in better yield contributing characters like

Table 1. Yield, economics and soil properties as influenced by different kharif rice establishment methods (pooled data of 2013,2014 and 2015)

Rice Grain Straw Cost of Gross Net BCR Soil BD Soil OC Soil ECeestablishment yield yield cultivation return return (g cc-1) (%) (dS m-1)methods (Mg ha-1) (Mg ha-1) (` 103 ha-1)

DSR 4.74 10.21 31 67 36 2.2 1.29 0.56 2.33UNPT 4.47 10.09 38 64 26 1.7 1.40 0.51 3.00PT 5.12 9.29 48 71 23 1.5 1.56 0.41 4.30SEm± 0.31 0.36 0.5 1.6 1.1 0.1 0.01 0.003 0.19LSD (p=0.05) ns ns 2.0 ns 4 0.3 0.05 0.012 0.75

DSR - Dry Direct Seeded Rice, UNPT - Unpuddled Transplanting, PT - Puddled Transplanting, BCR - Benefit Cost Ratio, BD -Bulk Density, OC - Organic Carbon, ECe – Electrical Conductivity of Saturation Extract of soil for the month of December.


Table 2. Yield components, yield, depth of irrigation water applied (IW), irrigation water productivity (IWp) and economics ofrapeseed under different kharif establishment methods and rabi tillage practices (pooled data of 2013-14, 2014-15 and2015-16)

Treatments Pods Seeds 1000 seed Seed yield IW IWp Cost of Gross Net BCRplant-1 pod-1 wt (g) (Mg ha-1) (ha-cm) (kg ha-cm-1) cultivation return return

(` 103 ha-1)

DSR 52 16 2.95 0.79 28.13 28.42 19.84 27.20 7.36 1.38UNPT 54 16 2.79 0.69 32.03 21.63 20.59 24.04 3.45 1.19PT 41 15 2.71 0.55 35.76 15.47 19.60 19.91 0.31 1.03SEm± 2.2 0.2 0.08 0.03 0.28 1.25 0.42 1.03 0.65 0.04LSD (p≤0.05) 8.6 0.9 ns 0.13 1.09 4.91 ns 4.03 2.54 0.14ZT 63 19 2.83 0.86 30.76 28.61 18.76 29.58 10.82 1.57CT 40 14 2.88 0.57 33.43 17.43 20.23 20.28 0.05 1.01RBS 44 15 2.73 0.60 31.73 19.48 21.05 21.29 0.24 1.01SEm± 2.4 0.4 0.11 0.03 0.42 1.14 0.43 0.86 1.03 0.05LSD (p≤0.05) 7.4 1.3 ns 0.08 1.28 3.52 1.32 2.64 3.17 0.15

DSR - Dry direct-seeded rice, UNPT - Unpuddled transplanting, PT - Puddled transplanting, ZT - Zero tillage, CT - Conventionaltillage, RBS = Raised bed sowing, ns - Non-significant.

Table 3. Maximum and minimum air temperature (°C) during rabi crop growing period recorded at Canning Town, West Bengal,India (Latitude 22°15′ N, Longitude 88°40′ E, Altitude 3.0 m from AMSL)

Month 2014 2015 2016 Mean

Max Min Max Min Max Min

Jan 24.1 12.5 24.6 14.0 25.3 13.6 19.0Feb 27.1 15.8 28.5 16.8 29.9 20.0 23.0Mar 32.1 20.5 32.4 20.5 33.2 23.3 27.0Apr 36.7 25.6 33.7 24.2 36.8 26.7 30.6

pods per plant and seeds per pod, however, seedweight were not affected by kharif riceestablishment methods. There was non-significantdifference between UNPT and PT treatments withrespect to yield contributing characters except forpods per plant, which was 31.7% higher in UNPTover PT. More number of pods per plant and seedsper pod was observed due to the effect of DSRand UNPT, which resulted in higher seed yield inthese treatments compared to PT. Irrigation wateruse and productivity was also significantly higherdue to DSR and UNPT. There was saving of 8and 4 ha-cm of irrigation water and increase inwater productivity by 84 and 40% because of DSRand UNPT, respectively, over PT treatment.Though kharif rice establishments did not affectthe cost of cultivation of rapeseed, but the grossreturn, net return and BCR of the cropping systemwas significantly higher for DSR.

The number of pods per plant was 63 andseeds per pod were 19 in ZT sown rapeseed which

was significantly higher over CT and RBS (Table2). Statistically there was non-significant variationin 1000 seed weight due to rabi tillage practices.In rapeseed, CT required higher amount ofirrigation water in comparison to other practices.The irrigation water productivity (IWp) wassignificantly higher in ZT (28.6 kg ha-cm-1) as theseed yield was higher and depth of irrigation waterrequired was lower over CT (17.4 kg ha-cm-1) andRBS (19.5 kg ha-cm-1).

Scarcity of irrigation water is a majorconstraint for rabi season cropping in coastal areas(Sarangi et al., 2014), therefore, tillage practice thatincrease IWp is most likely to be adopted byfarmers. Seed yield of rapeseed was significantlyhigher in ZT by 51 and 43% over CT and RBS,respectively. Similarly, gross return, net return andBCR were higher for ZT rapeseed. Since the ZTrapeseed was sown early, it got carryover soilmoisture, favorable low temperature condition andmatured earlier (March) than CT and RBS

224 Sarangi et al.

methods (April). The mean (2014, 2015 and 2016)air temperature during January, February, Marchand April was 19, 23, 27 and 31°C respectively(Table 3). There was no aphid attack in ZT plots,whereas in other methods there was damage byaphids. The CT and RBS crop maturity wasdelayed and faced higher temperature conditionduring the month of March and April, which maybe the cause of higher aphid infestation. Sowingtime is one of the important cultivation practicesin rapeseed, delaying the sowing time resulted insignificant reductions in seed yield due toinsufficient plant growth, early flowering causedby high temperature and drought (Turhan et al.,2011).

Effect of tillage and establishment on system yieldand economics

There was significant effect of kharif riceestablishment methods on the seed yield ofsubsequent rapeseed crop (Table 4) being highestin DSR (0.79 Mg ha-1), followed by UNPT (0.69Mg ha-1) and PT (0.55 Mg ha-1). However, theeffect of DSR and UNPT was at par on the seedyield of subsequent rapeseed crop. Puddlingresults in formation of hard pan as a result theroot growth and water uptake of rabi season cropis affected, resulting in lower yield.

Rapeseed produced highest seed yield underZT (0.72 to 0.94 Mg ha-1) than CT and RBS. REY

was highest (7.35 Mg ha-1) in DSR-ZT rapeseedsystem. This system (DSR-ZT rapeseed) alsoresulted in lowest cost of cultivation (` 50010ha-1) but highest gross return (` 98810 ha-1), netreturn (` 48800 ha-1) and BCR (1.98). Residualsoil moisture after kharif rice harvest in ZT helpedin better growth, yield attributes and yield ofrapeseed. Therefore, by adopting ZT technologyfor sowing rapeseed after DSR, farmers in coastalsaline region could increase the productivity,reduce cost of cultivation, and thereby increasecropping intensity and profitability. Direct seededrice followed by ZT rapeseed also help in timelysowing, conserve soil moisture and require lessirrigation water, saves tillage cost and time.Tripathi et al. (2013) reported that due to adoptionof zero tillage in rice-wheat system there isreduction of 12.7% operational cost and 16.9%increase in net income.

Conclusion

Adoption of dry direct seeding an alternativemethod of kharif rice crop establishment can helpin saving the cost of cultivation and increasebenefit cost ratio. Zero tillage sowing of rabi croplike rapeseed results in higher yield andprofitability due to early sowing, which providesfavorable temperature regime during its growthperiod. Combination of direct seeded ricefollowed by zero tillage rapeseed increased the

Table 4. Yield and economics of rice-rapeseed cropping system under different kharif establishment methods and rabi tillagepractices (pooled data of 2013-14, 2014-15 and 2015-16)

Treatments Rice yield Rapeseed yield System Cost of Gross Net BCR(Mg ha-1) (Mg ha-1) REY cultivation return return

Seed REY (Mg ha-1) (` 103 ha-1)

DSR-ZT 4.74 0.94 2.61 7.35 50.01 98.81 48.80 1.98DSR-CT 4.74 0.74 2.05 6.79 50.49 92.61 42.12 1.83DSR-RBS 4.74 0.70 1.94 6.68 52.04 91.18 39.14 1.75UNPT-ZT 4.47 0.93 2.58 7.05 56.69 95.25 38.56 1.68UNPT-CT 4.47 0.49 1.36 5.83 59.38 81.66 22.28 1.38UNPT-RBS 4.47 0.64 1.77 6.24 58.72 86.23 27.51 1.47PT-ZT 5.12 0.72 2.00 7.12 66.58 96.35 29.77 1.45PT-CT 5.12 0.47 1.30 6.42 67.82 88.26 20.44 1.30PT-RBS 5.12 0.47 1.30 6.42 69.38 88.12 18.74 1.27SEm± 0.31 0.04 0.12 0.12 0.74 1.48 1.78 0.03LSD (p=0.05) ns 0.14 0.38 0.38 2.29 4.57 5.49 0.10

REY - Rice equivalent yield, DSR - Dry direct seeded rice, UNPT - Unpuddled transplanting, PT - Puddled transplanting, ZT -Zero tillage, CT - Conventional tillage, RBS - Raised bed sowing, BCR - Benefit cost ratio.


irrigation water productivity, thereby efficient useof scarce resource like irrigation water, with highernet return and better soil physical properties.

References

Bouyoucos, GJ (1962) Hydrometer method for makingparticle size analysis of soil. Agronomy Journal 54: 464-465.

Gangwar KS and Singh HR (2010) Effect of rice (Oryza sativa)crop establishment technique on succeeding crops.Indian Journal of Agricultural Sciences 80(1): 24-28.

Hanway JJ and Heidel H (1952) Soil analysis methods asused in Iowa state college soil testing laboratory, Iowa.Agriculture 57: 1-31.

Jackson ML (1973) Soil Chemical Analysis. Prentice Hall ofIndia Pvt. Ltd., New Delhi, p 183.

Kamboj BR, Yadav DB, Yadav A, Goel NK, Gill G, MalikRK, Chauhan BS (2013) Mechanized transplanting ofrice (Oryza sativa L.) in non-puddled and no-tillconditions in the rice-wheat cropping system in Haryana,India. American Journal of Plant Sciences 4: 2409-2413.

Kumar V and Ladha JK (2011) Direct seeding of rice: recentdevelopments and future research needs, Advances inAgronomy 111: 297-413.

Miller RW and Donahue RL (1990) Soils, An Introduction toSoils and Plant Growth.

Sixth Edition, Prentice-Hall Inc., Englewood Cliffs, NewJersey, p 60.

Mousavi SF, Yousefi-Moghadam S, Mostafazadeh-Fard B,Hemmat A and Yazdani MR (2009) Effect of puddlingintensity on physical properties of a silty clay soil underlaboratory and field conditions. Paddy Water Environment7: 45-54.

Olsen SR, Cole CV, Watanabe FS and Dean LA (1954)Estimation of Available Phosphorus in Soils by Extractionwith Sodium Bicarbonate. USDA Circular 939.Government Printing Office, Washington DC, pp 1-9.

Sarangi SK, Maji B, Singh S, Sharma DK, Burman D,Mandal S, Ismail AM and Haefele SM (2014) Cropestablishment and nutrient management for dry season(boro) rice in coastal areas. Agronomy Journal 106(6):2013-2023.

Sarangi SK, Maji B, Singh S, Sharma DK, Burman D,Mandal S, Singh US, Ismail AM and Haefele SM (2016)Using improved variety and management enhances riceproductivity in stagnant flood-affected coastal zones.Field Crops Research 190: 70-81.

Shirani Rad AH, Shahsavari N, Jais HM, Dadrasnia A,Askari A and Saljughi M (2015) Fall cultivar of rapeseed(Brassica napus) for reduction of damage due to lateseason drought. Indian Journal of Agricultural Sciences85(1): 50-4.

Subbiah BV and Asija GL (1956) A rapid procedure for thedetermination of available nitrogen in soils. CurrentScience 25: 259 -260.

Tripathi RS, Raju R and Thimmappa K (2013) Impact ofzero tillage on economics of wheat production inHaryana. Agricultural Economics Research Review 26(1):101-108.

Turhan H, Gul MK, Egesel CO and Kahriman F (2011)Effect of sowing time on grain yield, oil content, andfatty acids in rapeseed (Brassica napus subsp. oleifera).Turkish Journal of Agriculture and Forestry 35: 225-234.

Walkley AJ and Black IA (1934) Estimation of soil organiccarbon by the chromic acid titration method. Soil Science37: 29-38.

Received in June, 2017; Accepted in September, 2017

Potassium and Sulfur Dynamics under Surface DripFertigated Onion Crop

Sanjay T Satpute1* and Man Singh2

1Deptt. of Soil and Water Engineering, PAU, Ludhiana-141 004, Punjab, India2Water Technology Centre, IARI, New Delhi-110 012, India


Abstract

A field experiment was conducted to study the modeling of potassium (K) and sulfur (S) dynamics underdifferent drip fertigation strategies in onion cultivated on sandy clay loam soil. Field data were used to calibrateand validate the solute transport model HYDRUS-2D in sandy clay loam soil. The model was calibrated forsoil hydraulic parameters except the hydraulic conductivity of the soil. These calibrated parameters were usedfor validation of the model. The performance of HYDRUS-2D was evaluated by comparing its simulatedvalues with the observed values of soil moisture and nutrient concentration. The coefficient of determination(R2), root mean square error (RMSE) and mean absolute error (MAE) were used as model performance indicators.The range of R2 between 0.73-0.99 for K and S distribution indicated good correlation between the observedand simulated values. The MAE and RMSE values for K and S distribution ranged from 0.0007 to 0.0083which indicated the accuracy of the model. From these results, it could be concluded that the model performswell for predicting the K and S concentration in the soil in onion crop. The model was also validated fornutrient distribution with the observed values at the end of the crop season and found to be performing well.The HYDRUS-2D model may be used to carry out simulations for different soil types and with different fertigationand irrigation strategies for developing guidelines.

Key words:Model HYDRUS-2D, Fertigation strategy, Potassium and sulfur dynamics, Drip irrigation, Irrigationinterval

Introduction

Due to increased population and water demandsthe share of water resources for agriculturalproduction is decreasing. Therefore, there is anurgent need to achieve “more crop per drop”.Compared with other irrigation methods, micro-irrigation has been considered as the most efficientform of irrigation. It improves the water andnutrient use efficiency and aims at maximizingfarmer’s income and minimizing pollution (Or andCoelho, 1996). The dynamics of the water withinthe soil volume surrounding the emitter isprerequisite to design irrigation systems as wellas to manage water and nutrients (Akbar et al.,1996; Zur, 1996). Only a few computer simulationmodels have the capability to analyze water flowand nutrient transport in multiple spatialdimensions, with the exception of HYDRUS-2D(Somma et al., 1998; Simunek et al., 1999; Cote etal., 2003) and FUSSIM 2 (Heinen, 2001). The

HYDRUS model allows for specification of rootwater and nitrate uptake, and the spatialdistribution of water and nitrate availabilitybetween irrigation cycles. Few studies haveevaluated the interrelationships between rates andspatial distribution of N application, rootdistribution and growth, and total plant uptake(Hopmans and Bristow, 2002). Gardenas et al.(2005) analyzed four different micro-irrigationsystems in combination with five differentfertigation strategies for various soil types, clearlydemonstrating the effects of root distribution andfertigation strategy on the uniformity of water andnutrients around drip lines and their effects onwater drainage and associated nitrate leaching byusing the HYDRUS-2D.

The guidelines for managing micro-irrigationsystems are needed so that the principles ofsustainable agriculture are satisfied. Appropriatedesign of drip fertigation system requires detailed


Potassium and sulfur dynamics in onion 227

understanding of water and nutrient distributionpattern in the root zone, nutrient availability inthe root zone and leaching of nutrient below theroot zone which is a function of emitter discharge,soil hydraulic properties and soil physicalproperties. The soil wetting and solute transportin trickle irrigation was analyzed by usingHYDRUS-2D model (Cote et al., 2003). Manystudies were conducted for water and nitratedistribution under drip fertigation (Ajdary, 2008;Rajput and Patel, 2006) but the informationavailable on potassium and sulfur distributionunder drip fertigation is very limited. The nitrogenis more efficiently used when applied withphosphorus, potassium and sulfur. In keeping viewof the rationale, the present study was undertakento calibrate and validate the HYDRUS-2D for thepotassium and sulfur distribution from the onionfield under inline drip fertigation.


Location and soil of experimental field

The field experiments were conducted at WaterTechnology Centre of Indian AgriculturalResearch Institute, New Delhi, in 2008 and 2009.The soil of the experimental site was sandy clayloam in texture, low in organic matter (0.25%)with neutral pH (7.1). The available N, assimilableP, available K and sulfur were 87.5, 25.0, 175.0and 45.0 kg ha-1, respectively. The field capacityvalues for 0-15, 15-30, 30-45 and 45-60 cm depthswere 20.91, 26.86, 26.33 and 28.33% (by volume)respectively, and permanent wilting point valuesfor the corresponding depths were 6.25, 6.22, 9.86and 9.94 %, respectively. The weather was coolduring the initial stages and warm to hot duringthe later stages. Rainfall during the two cropping

seasons was 176 mm and 28 mm, respectively. Themean daily evaporation ranged from 2.9 to 5.6mm in 2008 and from 3.5 and 6.6 mm in 2009.The actual mean maximum temperature rangedfrom 19.5°C to 36.5°C and 20.5°C to 39.0°C inthe years 2008 and 2009, respectively. Thevariations in mean minimum temperature ingrowing months were 5.5°C to 23.5°C and 7.2°Cto 24.1°C, respectively, for the years underconsideration.

Treatment and layout

Two months old seedlings of onion Pusa Madhaviwere transplanted in rabi season in the secondweek of January during 2008 and 2009 with 15cm spacing between rows and 10 cm betweenplants. The experiment was laid out in a split plotdesign having two main irrigation treatments (I1

and I2) and four fertigation treatments (F1, F2, F3,F4) as shown in Table 1. The irrigation treatmentswere in main plot, whereas, the fertigationtreatments were in subplot treatment. The plot sizefor the each replication was kept at 2.4 m × 5 m.

Irrigation and fertigation scheduling and cropmanagement practices

The growing period was 135 days in both the yearsof the study from transplanting to harvesting.Before transplanting, 25 Mg ha-1 of farm yardmanure (FYM) was applied to the field. Thefertilizers used in the experiment were urea, ortho-phosphoric acid, potassium chloride andmagnesium sulphate as a source of N, P, K and S,respectively. The level of fertilizers used in thestudy was 120 kg N ha-1, 50 kg P ha-1, 70 kg Kha-1 and 50 kg S ha-1 which is the recommendeddose of fertilizers for onion crop and it was divided

Table 1. Detail of treatments

I1F1: 2 days irrigation interval with fertigation during first half of irrigation durationI1F2: 2 days irrigation interval with fertigation during throughout irrigation durationI1F3: 2 days irrigation interval with fertigation during second half of irrigation durationI1F4: 2 days irrigation interval with fertigation during middle half of irrigation durationI2F1: 4 days irrigation interval with fertigation during first half of irrigation durationI2F2: 4 days irrigation interval with fertigation during throughout irrigation durationI2F3: 4 days irrigation interval with fertigation during second half of irrigation durationI2F4: 4 days irrigation interval with fertigation during middle half of irrigation durationI1=Irrigation at 2 days interval; I2= Irrigation at 4 days interval

F1-F4= Fertigation treatments

228 Satpute and Singh

in 12 equal doses. The fertilizers were injected ateight day interval through the inline dripperswhich was started 15 days after transplanting andstopped 30 days prior to the end of crop period.The time of application of fertigation injectionwas different in all four fertigation treatments. Forcrop water requirement, the reference evapo-transpiration (ETo) was estimated using the FAOPenman-Monteith equation employing previousfive year meteorological data. The crop durationof onion (135 days) was divided into four stages,namely, 1st (15 days), 2nd (35 days), 3rd (50 days)and 4th (35 days) with a crop coefficients (Kc) as0.7 for the 1st, 0.90 for the 2nd, 1.05 for the 3rd and0.75 for the 4th growth stages i.e. initial,developmental, bulb formation and bulb maturitystages, respectively, as given by Allen et al. (1998).The crop water requirements then were calculatedby multiplying the ETo values with the onion cropcoefficients at that particular stage. The crop waterrequirement and irrigation requirement werecalculated by using the ETc for both the seasons.Crop water requirement was 395 mm and 391 mmin 2008 and 2009, respectively, whereas, irrigationrequirement was 310 mm and 370 mm in 2008and 2009, respectively. The irrigation requirementin 2008 was less as compared in 2009, because in2008, there were more rainy days with heavyrainfall (176 mm).

Sampling and analysis

Soil samples were collected from different depthsviz. 0-15 cm, 15-30 cm, 30-45 cm, and 45-60 cmand also it was taken at emitter, 15 cm and 22.5cm away from emitter. The soil samples were alsocollected temporally. In two days irrigationinterval treatment, samples were taken at beforefertigation, 4 h after fertigation, 24, 48, 52 and 72h after fertigation and in four days irrigationinterval treatment, the samples were collectedperiodically (before irrigation, 4, 24, 48, 72 and96h after irrigation). The tube auger was used forthe sample collection from the field. The soilsamples were used for determination of availableK in soil by ammonium acetate method and S byturbidimetric method by using CaCl2. The flamephotometer was used for K determination andspectrophotometer was used for S determination.

Nutrient transport modelling

In the present study, HYDRUS-2D was selectedbecause it can simulate the effect of the following:

• Soil hydraulic properties on water andnutrient movement

• Discharge rate on the water and nutrientdistribution

• Time dependent flux boundary on water andnutrient distribution

• Timing of water and nutrient application onthe resultant distribution of nutrientdistribution within the root zone

Description of HYDRUS-2D

HYDRUS-2D is a finite element model, whichsolves the Richard’s equations for variablysaturated water flow and convection-dispersiontype equation for heat and solute transport. Theflow equation includes a sink term to account forwater uptake by plant roots. The model usesconvective-dispersive equation in the liquid phaseand diffusion equation in the gaseous phase tosolve the solute transport problems. It can alsohandle nonlinear non-equilibrium reactionsbetween the solid and liquid phases, linearequilibrium reactions between liquid and gaseousphases, zero-order production and two first orderdegradation reactions: one which is independentof other solutes and other which provides thecoupling between solutes involved in sequentialfirst order decay reactions. Physical non-equilibrium solute transport can also be accountedby assuming a two region, dual porosity typeformulation which partition the liquid phase intomobile and immobile regions. The program maybe used to simulate water and solute movementin unsaturated, partially saturated or fullysaturated porous media. Simulation can be donein non-uniform soils also. It can simulate the flowand transport in the vertical plane, horizontalplane and in a three dimensional region exhibitingradial symmetry about vertical axis. The modelcan deal with prescribed head and flux boundaries,controlled by atmospheric conditions, as well asfree drainage boundary conditions. The governingflow and transport equations are solved


numerically using Galerkin-type linear finiteelement schemes. The current version 2.0 ofHYDRUS also includes a Marquardt-Levenbergparameter optimization algorithm for inverseestimation of soil hydraulic and/or solutetransport and reaction parameters from measuredtransient or steady state flow and/or transportdata. A detail description of model and relatedtheory is presented in the report documentsversion 2.0 of HYDRUS (Simunek et al., 1999).

System geometry

The simulations were done for a soil profile ofdepth Z = 60 cm and radius r = 30 cm, with a dripemitter placed at the surface. The flux radius wastaken equal to the wetted radius withcorresponding emitter in the centre. Surface areafor irrigation without causing ponding wasdetermined from the flux radius and subsequentlyflux per unit area, resulting from emitter wasestimated. Fig. 1 shows the conceptual diagramof simulated area and imposed boundaryconditions. No flux was allowed through thelateral boundaries. Bottom boundary wasconsidered as free drainage boundary. Surfaceboundary was considered as variable fluxboundary (up to the radius of 25 cm) andatmospheric boundary for remaining 5 cm radius.The system was conceptually divided into fourlayers depending upon variability of the soilphysical properties.

Initial and boundary conditions

Initial distribution of the water content in differentsoil layers within the flow domain was kept as

observed in the experimental field. A sample figureshowing the initial water content is shown in Fig. 2.

For the purpose of investigating the influenceof drip emitter discharge, soil hydraulic propertiesand frequency of water input on wetting patterns,a time dependent flux boundary condition at thesurface in a radius of 25 cm from emitter positionwas used. This was done to take into account theirrigation and no irrigation periods and temporalchanges in duration of irrigation in the growingperiod. In the present case, water table was situatedfar below the domain of interest and therefore freedrainage boundary condition at the base of soilprofile was considered. On the sides of the soilprofile, it was assumed that no flux of water tookplace and hence no flux boundary condition waschosen, which in HYDRUS-2D is specified forimpermeable boundaries where the flux is zeroperpendicular to the boundary.

Input parameters

Soil hydraulic properties

The soil properties needed are water retention è(h)and hydraulic conductivity K(h) functions. In thisstudy, van Genuchten (1980) analytical modelavailable in HYDRUS-2D was used for the soilhydraulic properties. The model was calibrated forthe soil hydraulic properties. Saturated hydraulicconductivity of these soils was obtained from fieldexperiment.

Solute transport properties

A range of values of the longitudinal andtransverse dispersivities was selected fromFig. 1. Conceptual diagram of simulated area

Fig. 2. Initial conditions of water content


literature and approximate values were selectedafter calibration process.

Input for root water uptake

Two root water uptake model of Feddes et al.(1978) and S-shaped model are available in theHYDRUS-2D. The root water uptake model,Feddes is selected to simulate the root wateruptake of onion crop. Feddes model assigns plantwater uptake at each point in the root zoneaccording to soil pressure head conditions. P0 isthe pressure head of which the plant begins toextract water. P0pt is the pressure head at whichplants begin to extract water at maximum possiblerate (i.e. potential transpiration rate given in thetime variable boundary condition). For a potentialtranspiration rate of r2H, P2H is the pressure headat which the plant no longer extracts water atmaximum possible rate. For a potentialtranspiration rate of r2L, P2L is the pressure headat which the plant no longer extracts water at themaximum possible rate. Root water uptakes ceasesat P3 which is usually permanent wilting point.Plant parameters for onion crop at early growthstage and at bulb formation stage are given byFeddes (1978). The total volume of rootdistribution is responsible for 100% of plant soilwater extraction as regulated by transpirationdemand of the plant. Because of change of rootingdepth, the root distribution is varied throughoutthe simulation period. Actual root distributionparameters vary with crop, crop growth andsimulation period. Distribution of roots in the rootzone in relative term with onion plant is shown inFig. 3.

Calibration and validation

The model is calibrated using residual watercontent (θr), saturated water content (θs), Alpha(α) and n. The parameters were selected from therun when predicted and observed values are closeenough. The model was calibrated for nutrientdistribution. After calibration, model wasvalidated with the long term observed data toexamine its predictability.

Calibration of the model was done using thevalues ofpotassium and sulfur concentration atvarious points along the line and at differentdepths as mentioned above and selected in the rootzone with respect to the emitter. It was observedat 4, 24, 48, 52, 72 and 96 hours after fertigation.To check the performance of HYDRUS-2D, threeperformance indicators namely, coefficient ofdetermination (R2), Root mean square error(RMSE) and mean absolute error (MAE) wereused (Willmott, 1981). Root mean square error(RMSE) and mean absolute error (MAE) werecalculated using equations as given below. Acoefficient of determination of 1.0 represents aperfect prediction while negative and value zerorepresents a prediction no better than the randomvariation in the observed data, negative valuesindicate increasingly poorer predictions (Nash andSutcliffe, 1970)

…i

…ii

i = 1, 2, 3…………n

where,

Pi = Predicted values,

Oi = Observed values

N = Total number of observations

A criterion adopted by Willmott (1981) wasconsidered in evaluating different developedsimulation models, the evaluation criteriaconsisted of:

i. Lower the mean absolute error, modelpredictions are good with better accuracy

ii. Smaller RMSE value, the better theperformance of modelFig. 3. Relative root distribution of onion



Spatial and temporal distribution of nutrients inthe soil

Spatial distribution of potassium and sulfur hasbeen described using the data collected during thecrop season. The different fertigation strategiesdescribed in methodology were followed duringthe experimentation. From the yield data of theonion, F3 strategy was found to be better thanother strategies. So, F3 fertigation strategy wasselected for describing the nutrient distribution andintensive sampling was done in F3 in 2009 ascompared to 2008. To find out the temporalvariation in the potassium and sulfur distribution,soil samples were taken before fertigation, 4, 24,48, 52 and 72 h after fertigation for I1 and for I2,samples were collected before fertigation, 4, 24,48, 72 and 96 h after fertigation.

Potassium distribution

Available K in the soil during the cropping seasonof onion was estimated using the proceduredescribed earlier in the methodology. The highestyield was observed under F3 fertigation strategytherefore, only F3 was considered for modeling ofK distribution. Higher concentrations of K wereobserved in the upper layers due to fertigationduring second half of fertigation duration. Thisstrategy retained K in the active root zone, makingit easily available for the crop. K concentrationwas higher at the emitter and decreased withincrease in horizontal distance as well as with thedepth.

The HYDRUS-2D model was used to predictthe K movement under F3 treatment. Thecomparison of simulated and observed Kconcentration at various depths and at varioustime intervals has been presented in Figs. 4 and 5.

Fig. 4. Simulated and observed K concentration in I1 (a) at emitter (b) at 15 cm from emitter (c) at 22.5 cm from emitter

Fig. 5. Simulated and observed K concentration in I2 (a) at emitter (b) at 15 cm from emitter (c) at 22.5 cm from emitter


It showed that simulated and observed Kconcentration follow a similar trend. Kconcentration decreased with elapsed time andirrigation. The simulated and observed Kconcentration at the emitter and 24 h afterfertigation were 0.135 mg ml-1 and 0.126 mg ml-1

in the first layer and 0.133 mg ml-1 and 0.123 mgml-1 in the same layer 48 h after fertigation.Simulated and observed K concentration at 15 cmand 22.5 cm from emitter showed a decreasingtrend similar to the water distribution.

Same trend was observed in the differentdepths also. Water helps to move the nutrient todeeper layers as was observed after next irrigation.K concentration at 4 h after next irrigation was0.128 mg ml-1 and 0.121 mg ml-1 as simulated andobserved values, respectively. In a similar analysisdone for I2 irrigation treatment, higherconcentration of K was observed in the lowerlayers. The comparison between simulated andobserved K concentration has been shown in Fig.5 and it follows a similar trend as was observed inI1.

The coefficient of determination R2, meanabsolute error (MAE) and root mean square error(RMSE) were determined to find out the closenessbetween observed and simulated values of Kconcentration and the accuracy of the modelunder I1 and I2 (Tables 2 and 3). The higher (0.73to 0.99) values of R2 indicated that simulated and

observed values of K movement are highlycorrelated and the model is predicting the Kmovement satisfactorily in both I1 and I2. MAEvalues for K concentration varied from as low as0.0005 to as high as 0.0080 in both I1 and I2. TheRMSE values for K concentration varied from aslow as 0.0032 to as high as 0.0083 in both I1 andI2.The lower values of MAE and RMSE indicatedthe higher accuracy of the HYDRUS-2D modelfor simulating the K movement.

Sulfur distribution

The comparison of simulated and observed Sconcentration at various depths and at varioustime intervals is presented in Figs. 6 and 7. It hasshown that simulated and observed Sconcentration follow the same trend as observedin P and K. The simulated and observed Sconcentration at the emitter and 24 h afterfertigation depict 0.0252 mg ml-1 and 0.0272 mgml-1 in the first layer and 0.0238 mg ml-1 and 0.0264mg ml-1 in the same layer after 48 h of thefertigation. The simulated and observed Sconcentration at 15 cm and 22.5 cm from emitteralso showed a similar trend as observed in P andK distribution. The concentration of S founddecreased with increase in horizontal distance.The magnitude of the S movement is more thanK but less than N. The figures showed the decreasein S concentration after the next irrigation event.

Table 2. Potassium distribution: Model performance parameters for I1

Observation point 4 hrs 24 hrs 48 hrs

R2 MAE RMSE R2 MAE RMSE R2 MAE RMSE

0 0.93 0.0037 0.0048 0.92 0.0018 0.0044 0.87 0.0049 0.005915 0.93 0.0028 0.0046 0.73 0.0013 0.0034 0.84 0.0040 0.004622.5 0.88 0.0017 0.0037 0.77 0.0005 0.0032 0.84 0.0015 0.0032

MAE depicts mean absolute error and RMSE, root mean square error

Table 3. Potassium distribution: Model performance parameters for I2

Observation 4 hrs 24 hrs 48 hrs 72 hrs 96 hrs

point R2 MAE RMSE R2 MAE RMSE R2 MAE RMSE R2 MAE RMSE R2 MAE RMSE

0 0.97 0.0079 0.0083 0.99 0.0077 0.0079 0.99 0.0080 0.0082 0.99 0.0075 0.0077 0.99 0.0068 0.007115 0.98 0.0056 0.0060 0.98 0.0050 0.0053 0.98 0.0050 0.0054 0.95 0.0044 0.0050 0.94 0.0037 0.004422.5 0.96 0.0039 0.0043 0.95 0.0050 0.0051 0.96 0.0048 0.0050 0.91 0.0040 0.0045 0.96 0.0035 0.0040



A similar analysis done for I2 indicated a similartrend as was observed under I1 irrigationtreatment. Higher concentration of S wasobserved in deeper layers under I2 than I1.

The model performance parameters viz.coefficient of determination (R2), mean absoluteerror (MAE) and root mean square error (RMSE)were determined to find out the closeness betweenobserved and simulated values of S concentration

and the accuracy of the model under I1 and I2

(Table 4 and 5). The higher (0.77 to 0.99) valuesof R2 in I1 indicated that simulated and observedvalues of S movement matched closely more thanthe I2 where it varied from 0.70 to 0.92. MAEvalues for S concentration varied from 0.0015 to0.0038 and RMSE values varied from 0.0021 to0.0041. The lower values of MAE and RMSEindicated the effectiveness of the HYDRUS-2Dmodel for simulating S movement.

Fig. 6. Simulated and observed S concentration in I1 (a) at emitter (b) at 15 cm from emitter (c) at 22.5 cm from emitter

Fig. 7. Simulated and observed S concentration in I2 (a) at emitter (b) at 15 cm from emitter (c) at 22.5 cm from emitter

Table 4. Sulfur distribution: Model performance parameters for I1

Observation point 4 hrs 24 hrs 48 hrs

R2 MAE RMSE R2 MAE RMSE R2 MAE RMSE

0 0.98 0.0027 0.0027 0.99 0.0021 0.0022 0.99 0.0028 0.0028

15 0.92 0.0026 0.0030 0.81 0.0033 0.0038 0.77 0.0038 0.0042

22.5 0.93 0.0035 0.0036 0.79 0.0033 0.0037 0.94 0.0040 0.0041



To examine the predictability of the model onseasonal basis, simulations were carried out topredict the K and S distribution at the end of thecrop season i.e. 136 days (Figs. 8 and 9). Theobserved and simulated values of K and Sdistribution followed the similar trend. Thenutrient concentration found to be decreasing withincrease in horizontal distance from the emitter.The model performance parameters were alsodetermined. The R2 between simulated andobserved K and S distribution varied from 0.73 to0.99. The MAE varied from 0.0005 to 0.0080 andRMSE varied from 0.0021 to 0.0083. The higher

R2 indicate that the model is predicting K and Sconcentration satisfactorily and low values ofMAE and RMSE indicate that the model waspredicting these values with greater accuracy.

Nutrient uptake by the plant

The onion plant samples collected at the harvestwere analyzed in the laboratory to determine Kand S uptake by the plant. Irrespective of theirrigation interval, the highest plant uptake of K(43.02 kg ha-1) and S (12.19 kg ha-1) was observedin F3 and it retained most of the nutrients in theupper profile making them easily available for the

Table 5. Sulfur distribution: Model performance parameters for I2

Observation 4 hrs 24 hrs 48 hrs 72 hrs 96 hrs

point R2 MAE RMSE R2 MAE RMSE R2 MAE RMSE R2 MAE RMSE R2 MAE RMSE

0 0.82 0.0032 0.0037 0.82 0.0034 0.0038 0.91 0.0024 0.0026 0.79 0.0026 0.0030 0.75 0.0025 0.002915 0.79 0.0030 0.0035 0.76 0.0031 0.0036 0.78 0.0017 0.0024 0.74 0.0015 0.0021 0.70 0.0017 0.002322.5 0.72 0.0032 0.0038 0.76 0.0033 0.0037 0.92 0.0025 0.0028 0.92 0.0025 0.0029 0.89 0.0025 0.0028

Fig. 9. Validation of S distribution (a) at emitter (b) at 15 cm from emitter (c) at 22.5 cm from emitter

Fig. 8. Validation of K distribution (a) at emitter (b) at 15 cm from emitter (c) at 22.5 cm from emitter

Simulated I1F3

Simulated I2F3

Observed I1F3

Observed I2F3

Simulated I1F3

Simulated I2F3

Observed I1F3

Observed I2F3


plant. The combined effects of fertigation andirrigation strategies are shown in Fig. 10 whichreveal that the highest K and S uptake was foundunder I1F3. It was observed that among K and Snutrients, K uptake was more by the onion plant.The similar results were reported byEL-Desuki etal. (2006) and Jha et al. (2000).

The statistical analysis indicated that there wasnon-significant difference between the uptakes ofnutrients under different fertigation strategies. Itcan therefore, be assumed that fertigation strategydid not have any impact on the uptake of thenutrients by plant.

Conclusions

The results presented here described the effect ofdrip fertigation strategies and irrigation intervalon K and S distribution in the soil and their uptakeby plant. Higher concentrations of K and S wereobserved at upper layers under the fertigationduring the second half of irrigation duration.HYDRUS-2D model was used for the predictionof K and S concentration in different fertigationstrategies and the results revealed that observedvalues were satisfactorily predicted. Calibrationand validation results showed that HYDRUS-2Dcan be used for simulation of water and nutrient(K and S) distribution. The R2, MAE and RMSEvalues indicated show better matching betweenobserved and simulated results. The R2valuesranged from 0.73 to 0.99 which indicated thatobserved and predicted values were highlycorrelated. The MAE values for K and S

distribution varied as low as 0.0005 and as highas 0.0080 and RMSE for nutrient distributionranged between 0.0021-0.0083. The lower valuesof MAE and RMSE showed the accuracy andeffectiveness of the HYDRUS-2D model. Fromthe nutrient distribution information and underdifferent treatments, it can be concluded that theHYDRUS-2D model can be used for thesimulation of nutrient distribution under differentfertigation and irrigation scenarios. This will helpto reduce the cost and time of performing theexperiment on each soil type and for everydischarge rate of the emitter.

References

Ajdary K (2008) Simulation of nitrogen distribution in soilwith drip irrigation system. Journal of Applied Sciences8(18): 3157-3165.

Akbar AK, Yitayew M and Warrick AW (1996) Fieldevaluation of water and solute distribution from pointsource. Journal of Irrigation and Drainage Engineering122(4): 221-227.

Allen RG, Pereira LS, Raes D and Smith M (1998) Cropevapotranspiration. Guidelines for computing crop waterrequirements. FAO Irrigation and Drainage Paper No.56, FAO, Rome, Italy, p. 300.

Cote CM, Bristow KL, Charlesworth PB and Cook FJ (2003)Analysis of soil wetting and solute transport in sub-surface trickle irrigation. Irrigation Science 22(3–4): 143–156.

EL-Desuki M, Abdel-Mouty MM and Ali AH (2006)Response of onion plants to additional dose ofpotassium application. Journal of Applied Sciences Research2(9): 592-597.

Fig. 10. Uptake of potassium and sulfur by onion plant under different treatments


Feddes RA, Kowalik PJ and Zaradny H (1978) Simulationof field water use and crop yield. In: SimulationMonographs, Pudoc, Wageningen.

Gardenas AI, Hopmans JW, Hanson BR and Simunek J(2005) Two-dimensional modeling of nitrate leachingfor various fertigation scenarios under micro-irrigation.Agricultural Water Management 74(3): 219-242.

Heinen M (2001) FUSSIM2: Brief description of simulationmodel and application to fertigation scenarios. Agronomy21: 285-296.

Hopmans JW and Bristow KL (2002) Current capabilitiesand future needs of root water and nutrient uptakemodeling. Advances in Agronomy 77:104–175.

Jha AK, Pal N and Singh N (2000) Phosphorus uptake andits utilization by onion varieties at different stages ofgrowth. Indian Journal of Horticulture 57(4): 347-350.

Or D and Coelho FE (1996) Soil water dynamics under dripirrigation: transient flow and uptake models. Transactionof ASAE 39(6): 2017-2025.

Rajput TBS and Patel N (2006) Water and nitrate movementin drip-irrigated onion under fertigation and irrigation

treatments. Agricultural Water Management 79 (3): 293-311

Simunek J, Sejna M and van Genuchten MTh (1999) TheHYDRUS-2D software package for simulating the two-dimensional movement of water, heat and multiplesolute in variably-saturated media. International Groundwater Modeling Centre, Colorado School of MinesGolden, Co 80401.

Somma F, Clausnitzer V and Hopmans JW (1998) Modelingof transient three-dimensional soil water and solutetransport with root growth and water and nutrientuptake. Plant and Soil 202: 281-293.

VanGenuchten MTh (1980) A closed-form equation forpredicting the hydraulic conductivity of unsaturatedsoils.Soil Science Society of America Journal 44: 892–898.

Willmott CJ (1981) On the validation of the models. PhysicalGeography 2: 184-194.

Zur B (1996) Wetted soil volume as design objective in trickleirrigation. Irrigation Science 16: 101-105.


Integrated Farming System in Salt-affected Soils ofTamil Nadu for Sustainable Income Generation

M Selvamurugan1*, M Baskar1, P Balasubramaniam1, P Pandiyarajan1

and MJ Kaledhonkar2

1A.D. Agricultural College and Research Institute, Tamil Nadu Agricultural UniversityThiruchirapalli-620 009, Tamil Nadu, India

2 Central Soil Salinity Research Centre, Karnal-132 001, Haryana, India *Corresponding author E-mail: [email protected]

Abstract

This experiment was conducted to compare the conventional cropping system and integrated farming system(IFS) in terms of income and profitability in salt- affected lands of Tamil Nadu. Both the pure crop and cropwith fisheries and poultry components were included in 0.40 ha each. An overall income of ` 1,17,328 wasobtained from all three components of IFS program and the profit contribution from fisheries and poultrycomponent were 59% and 24% respectively. In comparison with a pure crop in 0.40 ha, higher yield and netreturn were obtained from IFS (0.30 ha for crop and 0.10 ha for poultry and fisheries) and BC ratio was 2.97which was 1.42 higher than the crop alone. Therefore, it is recommended to adopt IFS program to increase theincome and livelihood of all types of farmers cultivating salt-affected land areas of Tamil Nadu.

Key words: Salt-affected soils, Integrated Farming System, Subsistence farming, Net return, Benefit cost ratio

Introduction

The population of India is increasing at the rateof 1.2%, indicating that it will be the mostpopulous nation in the world by 2025. Theincreasing population causes fragmentation ofland and as a consequence the average landholding has reduced from 2.3 ha in 1970–71 to1.2 ha in 2010–11 (Nath et al., 2016). Moreover,the number of marginal farmers with less than 1ha of cultivated land has increased from 51% to67% during that period. Small farm holdersgenerally practice subsistence farming and theyhave poor access to land, water, inputs, credit,technology and markets. These resource-poorfarmers are needed to produce a continuous,reliable and balanced supply of foods, as well ascash for basic needs and recurrent farmexpenditure.

The salt-affected soils form importantecological entity in Tamil Nadu as also in manyother states of India. Economic use of salt-affectedlands for agriculture has special reference to TamilNadu, which has about 4.7 lakh hectares of

salinity/ alkalinity affected land. Moreover, thesalt-affected area is increasing continuously dueto various factors viz., intrusion on sea water,continuous irrigation with saline water etc. Atpresent, it experiences huge recurring losses interms of limited productivity. It is imperative todevelop strategies that enable adequate incomeand employment generation, especially for smalland marginal farmers cultivating salt-affected land.Under this condition, it is necessary to integrateland based enterprises like fishery, poultry,duckery, apiary, field and horticultural crops, etc.within the bio-physical and socio-economicenvironment of the farmers to make farming moreprofitable and dependable (Behera et al., 2004).No single farm enterprise is likely to be able tosustain the small and marginal farmers withoutresorting to integrated farming systems (IFS) forthe generation of adequate income and gainfulemployment year-round (Mahapatra, 1994). TheIFS, aims at increasing income and employmentfrom small-holdings by integrating various farmenterprises and recycling crop residues and by-products within the farm itself (Behera and


238 Selvamurugan et al.

Mahapatra, 1999; Singh et al., 2006). Through IFS,a change in the farming techniques for maximumproduction in the cropping pattern is introduced,which takes care of optimal resource utilization.The farm wastes are better recycled for productivepurposes in IFS. The inter-related, interdependentand interlinking nature of IFS, involves theutilization of primary produce and secondaryproduce of one system as basic input of the othersystem, thus, making them mutually integrated asone whole unit. This incidentally helps to reducethe dependence on procurement of inputs fromopen market, making thereby the IFS a self-supporting entity and sustainable system overtime. Moreover, the farm family gets scope forgainful employment round the year there byensuring good income and higher standard ofliving even from small holdings (Biswas, 2009).With this in view, this trial was conducted.


The experiment on Integrated Farming System(IFS) was initiated at the farm of AgriculturalCollege and Research Institute of Tamil NaduAgricultural University involving cropping(paddy), fishery and poultry as the integratedsystem and cropping (Daincha (Sesbania aculeata)– Rice) alone as the control. For this study, 0.80ha of land was taken up, out of which 0.40 hawas allotted for IFS-0.30 ha for crop component(paddy) and 0.10 ha for poultry and fisheriescomponents. The remaining 0.40 ha was allottedexclusively for cropping alone (control) whereinthe paddy var. White Ponni was cultivated. Thestudy was conducted in the year 2015-16.Observations on the productivity and economicsof individual components and the farming systemas a whole were recorded as per the standardprocedure. The soil of the experiment site was clayloam in texture with pH of 9.10 and EC of 0.78dS m-1. The N, P and K content of the soil was220, 19.2, and 232 kg ha-1, respectively.

Components

I. Crop: In the IFS program under cropcomponent 0.30 ha of area was cultivatedwith paddy var. White Ponni and productionand economics were calculated from yielddata.

II. Fisheries: Fingerlings, totaling 1100 innumbers of Catla, Silver carp, Rohu, Mirgaland Grass carp were released into fish pondwith area of 0.10 ha during third week ofJanuary’ 2015. Locally suited recommendedpractices were employed in rearing offingerlings, and the fishes were harvested aftercompleting 8 months.

III. Poultry: To generate additional income, thirtylayers of ‘Bab Cock’ variety birds were rearedin the poultry shed constructed on the fishpond from 3rd week of February. Poultrydropping was allowed to drop into the fishpond directly which served as the source offood for fish. In the poultry component, eggproductivity and economics were observedand the layer birds were culled aftercompleting age of 70 weeks period.

IV. Bund cropping: In IFS, various vegetables,greens and tree saplings were raised along thebund of fish pond, adopting spot reclamationtechnology to increase the revenue of thefarmers. The production and economics ofvegetables crops viz., moringa, bitter gourdand ripped gourd and the greens wereobserved.

V. Control: In control, 0.40 ha of area wascultivated with paddy var. White Ponni inwhich, normal crop rotations and othercultural practices followed by the farmer werepracticed. The yield and economics wererecorded for comparison with the variouscomponents of IFS.


The expenditure incurred and income generatedfrom various IFS components are presented inTable 1. The total cultivation expenditure for 0.30ha of paddy crop was ` 13,539 and the totalincome generated from the sale of grains and strawwas ̀ 24,785. A net profit of ̀ 11,246 was obtainedfor the cultivation of 0.30 ha of paddy crop. Thefisheries component incurred a total expenditureof ` 10283 and the poultry component incurred atotal expenditure of ` 14,950. Both the fisheriesand poultry component consumed a capitalinvestment of ` 16,500. The cultivation of

Integrated farming system for salt-affected soils 239

vegetables crops viz., moringa, bitter gourd andripped gourd and the greens along the buds offish pond also incurred a total expenditure of` 750.

The total fish production in 0.10 ha of fishpond was 314 kg and total income generated fromthe fishery component was ` 56,520. The totalincome generated from the poultry was ` 33,873through selling of eggs (` 26,210) and culling ofmatured birds (` 5,663). The income generatedfrom the bund crops viz., Moringa (Moringaoleifera), Ripped gourd (Luffa acutangula), Bittergourd (Momordica charantia), Sirukeerai(Amaranthus tricolor), Mulai keerai (Amaranthusblitum) and Pulicha keerai (Hibiscus cannabinus)was ̀ 630, 460, 190, 320, 140 and 410, respectivelywith total income of ` 2150. Through thecomponents of poultry and bund vegetable cropsof IFS, the income was generated daily and alsoit provides gainful employment from unit landarea over stipulated time period (Khanda, 2009).An overall profit of ` 77,752 was obtained fromall three components of IFS program and thefisheries and poultry component yielded anincome of 59% and 24%, respectively.

Table 2 illustrates the net profit from 0.4 haarea was ` 77, 752 in IFS which was ` 67, 498,more as compared to sole cropping i.e. ` 68,745per ha higher than sole cropping. In IFS, BC ratioof 2.97 was obtained which was 1.47 higher thanthe crop alone. Similar results were reported by

Jayanthi et.al. (1994), who reported that theintegration of poultry with 20 birds of Bapkoklayers, fishery 300 fingerlings of polyculture andoyster mushroom with a production capacity of2 kg day-1 with improved rice-based croppingincreased the food productivity and income of thesmall and marginal lowland farmers. Bahera andMahapatra (1998) also reported increase in returnsthrough IFS. Similarly, Sonjoysha et. al. (1998)

Table 1. Cost and profit details of various IFS Components

Component Income Expenditure Profit(`) (`) (`)

Cropping (0.30 ha) 24,785 13,539 11,246Fisheries 56,520 10,283 46,237Poultry 33,873 14,950 18,923Bund cropping 2,150 750 1,400Net profit 117,328 39,522 77,752

Table 2. Comparison of IFS with pure cropping

Components Cost Income Profit B:C(`) (`) (`) ratio

IFS Components (0.4 ha) 39,522 117,328 77,752 2.97Pure cropping (0.4 ha) 18,768 29,022 10, 254 1.55

indicated that for irrigated situation rice-fish-vegetables-fruit crops farming system wasprofitable. Based on the results it can be concludedthat IFS with crop, poultry and fish componentswill increase the income of the farmers of salt-affected land areas of Tamil Nadu many fold ascompared to crop alone component which isgenerally practiced by the farmers.

References

Behera UK and Mahapatra IC (1999) Income andemployment generation of small and marginal farmersthrough integrated farming systems. Indian Journal ofAgronomy 44(3): 431-439.

Bahera UK and Mahapatra IC (1998) Income andemployment generation for small and marginal farmersthrough integrated farming system. Indian Farming 48:16-28.

Behera UK, Jha KP and Mahapatra IC (2004) Integratedmanagement of available resources of the small andmarginal farmers for generation of income andemployment in eastern India. Crop Research 27(1): 83-89.

Biswas BC (2009) IFS to improve input use efficiency,employment and income in Eastern India. In: ProceedingsWinter School on Multi Criteria Decision Making andOptimization Methodology for Sustainable Farming Systems.Division of Agronomy, IARI, New Delhi, pp 60-76.

Jayanthi C, Rangasamy A, Chinnusammy C,Purushothaman S and Planiappan SP (1994) Integratedfarming systems for smallholdings. Indian J. Agron. 39:1-7.

Khanda CM (2009) Integrated Farming System: Anapproach for improving livelihood of small and

240 Selvamurugan et al.

marginal farmers. In: Invited Papers and Abstracts ofthe National Seminar on Managing Rural Livelihood inIndia: Challenges and Opportunities. Orissa University ofAgriculture and Technology, Bhubaneswar, Odisha, pp140-145.

Mahapatra IC (1994) Farming system research – A key tosustainable agriculture. Fertilizer News 39(11): 1325.

Mahapatra IC and Behera UK (2004) Methodologies offarming systems research. In: Panda D, Sasmal S, NayakSK, Singh DP, and Saha S (eds) Recent Advances in Rice-based Farming Systems, 17-19 November 2004, Cuttack,Orissa, Central Rice Research Institute, pp 79-113.

Nath, SK, De HK and Mohapatra BK (2016) Integratedfarming system: is it a panacea for the resource-poorfarm families of rainfed ecosystem? Current Science110(6): 969-971.

Singh KBJS, Singh Y and Singh JP (2006) Development offarming system models for the north-eastern plain zoneof Uttar Pradesh. Indian Farming 56(2): 5-11.

Sonjoysha H, Sinhababu DP, Poonan A and Jha KP (1998)Integrated farming systems models for integrated andrain fed lowland small farm of coastal Orissa. In: Proc.First Int. Agron. Cong., India, pp 415-416.


Evaluation of Groundwater Quality for Irrigation inGulha Block of Kaithal District in Haryana

Vijay Kant Singh1*, Ramprakash1, Rajpaul1 , Sanjay Kumar2,Kuldeep Singh1 and Satyavan1

1Department of Soil Science, CCS Haryana Agricultural University, Hisar-125004, Haryana, India2Department of Soil and Water Engineering, CCS Haryana Agricultural University, Hisar-125004, Haryana, India


Abstract

Evaluation or supervising ground water quality for irrigation purposes is of paramount importance in semi-arid and arid regions, particularly in the developing countries like India. Therefore, the study was carried out toassess the quality of groundwater in Gulha block of Kaithal district in Haryana. From the block, 109 groundwatersamples were collected and analysed for pH, EC, anions (CO3

2-, HCO3-, Cl-, SO4

2- and NO3-) and cations (Ca2+,

Mg2+, Na+ and K+). In addition to this, water quality indices (SAR and RSC) were also computed. The EC andpH of water samples varied from 0.30 to 2.31 dS m-1 and 7.36 to 9.80 with a mean value of 1.24 dS m-1 and 8.19,respectively. The cations followed the order- sodium > magnesium > calcium > potassium. Likewise, anionsfollowed the order- HCO3

–> Cl–> SO42–> CO3

2–> NO3–. Sodium absorption ratio (SAR) and residual sodium

carbonate (RSC) ranged from 2.55 to 14.39 (mmol l-1)1/2 and nil to 5.80 me l-1 with mean value of 6.12 (mmoll-1)1/2 and 2.20 me l-1, respectively. According to All India Coordinated Research Project (AICRP) classification,out of 109 samples 69 were of good quality, 3 marginally saline, 12 marginally alkali, 24 alkali, and 1 highlyalkali. Spatial variability maps of EC, pH, SAR, RSC and water quality of groundwater used for irrigation inthe block were also generated. By and large, the analysis of various parameters indicated that quality ofgroundwater in this block is safe for irrigation purposes.

Key words: Groundwater, Water quality indices, Sodium absorption ratio (SAR), Residual sodium carbonate(RSC), Cations, Anions, Spatial variability

Introduction

In India, the scarcity of water is burning issuewhich is going to escalate further because ofclimate change. The problem is more severe inarid and semi-arid areas of the country owing tothe vagaries of monsoon and paucity of surfacewater. During the past few decades, thecompetition for economic development linkedwith the population boom and urbanization hasled to the substantial changes in land use therebyensue more demand of water for agriculture,household and industrial activities (Nag and Das,2014). The exceptional physical and chemicalcharacteristics determine the use of the water. Theutilizable water supply is not adequate to irrigatethe arable area. Therefore, efforts are required toamplify the chances of water for irrigation inagriculture (Sharma, 2005; Ahamed et al., 2013).The exploitation and contamination withnumerous chemical and biological sources have

led to retreating of worldwide surface watersources thereby increasing tremendous pressureon groundwater resources (Singh et al., 2006; Bhatet al., 2016). The quality of groundwaterencompasses the physical, chemical and biologicalfeatures of groundwater. The suitability ofgroundwater for different uses mainly reckons onits quality, therefore, evaluation of groundwateris a major concern (Packialakshmi et al., 2011;Vishwanath et al., 2016). Since, groundwater is themain source of irrigation in arid and semi-aridregions, farming is restricted due to dearth ofsuitable irrigation water. The quality of irrigationwater profoundly impacts crop production and hasstrong bearing on physical and chemicalproperties.

Because being devoted to agricultural usage,the groundwater quality must be appraised toprotect public health and environment.Accordingly, comprehensive groundwater quality


242 Singh et al.

supervision is an effective tool not only to assessthe suitability of groundwater for irrigation butalso to assure a competent management of waterresources. It is imperative that the naturalresources should be used judiciously not only forthe welfare of current population but also to satisfythe needs and ambition of future generations foroverall sustainable development of the society.Ground water is one of the valuable resources forwhich a planned approach is needed (Jain et al.,2012). The chemical make-up of groundwaterdetermines its suitability for different uses whichrequire various standards. The quality ofgroundwater depends upon distinct natural(precipitation, rock-water interaction, geology,geomorphology etc.) and anthropogenic(agriculture, industry, domestic, land use etc.)activities that eventually make the groundwatervulnerable. Vulnerability is the characteristic ofthe aquifer to receive and carry contaminant fromanthropogenic sources (Vrba and Zoporozec,1994; Adhikary et al., 2014). The quality of waterfor agricultural purposes is ascertained byexamining the effect of water on superiority andyield of the crops in addition to distinctive changesin the soil (FAO, 1985; Zinabu et al., 2010). Theproblems confronted in soil used as a base forevaluation of water quality are those associatedto salinity, water infiltration rate, toxicity and setof other heterogenous problems (Richardson,1954; Zinabu et al., 2010). Therefore, monitoringof groundwater quality is must to prevent thesecondary salinization. Keeping in view the facts,the present study was undertaken to evaluate thequality of groundwater for irrigation purposes inGulha block of district Kaithal, Haryana.


The study area of block Gulha falls in the districtKaithal, Haryana and is surrounded by districtKurukshetra and state of Punjab. The climate ofstudy can be classified as semiarid and hot whichis mainly dry with very hot summer (temperatureabove 40°C in May and June) and cold winter(near about 7°C in January) except duringmonsoon season when moist air of oceanic originpenetrates the district. The soils of the block aresandy to sandy loam in texture. The dominatingcropping system in this region is rice-wheat under

surface irrigation (flooding and basin). Other maincrops grown in the area are sorghum, pearl millet,sugarcane, cotton, etc.

To assess water quality of the study area, 109groundwater samples were collected to cover theentire study area and locations were recordedusing hand held GPS. The location map of thesampling point is presented in Fig. 1.

Fig. 1. Sampling sites of Guhla block in Kaithal district

Sampling was carried out using pre-cleanedplastic bottles, which were rinsed thrice withsample water prior to sample collection. Beforeanalysis of groundwater, the instruments werecalibrated in accordance with the manufacturer’srecommendations. The chemical analysis wasaccomplished as per the standard methodsrelevant to the analysis of groundwater (Table 1).

Electrical Conductivity (EC) was measured byconductivity meter and pH by pH meter. Sodium(Na+) and potassium (K+) were measured by flamephotometer. Calcium and magnesium weredetermined with standard EDTA solutiontitrimetrically. Carbonate and bicarbonate wereestimated by titration with H2SO4, Chloride bytitrating against standard silver nitrate (AgNO3)solution. The colorimetric analysis of sulphate andnitrate was done by spectrophometer. The groundwater samples were analysed for various chemicalparameters, viz., pH, EC, anions (CO3

2-, HCO3-,

Groundwater quality for irrigation in Gulha block in Haryana 243

Cl-, SO42- and NO3

-) and cations (Ca2+, Mg2+, Na+

and K+). Subsequently, SAR and RSC werecalculated for these samples. The water qualityindices viz., SAR (Richards, 1954) and RSC(Eaton, 1950) are calculated as:

a)

b)

Based on EC, SAR and RSC, water sampleswere classified into different categories as per theclassification of All India Coordinated ResearchProject (AICRP) on management of salt affectedsoils and use of saline water in agriculture (Guptaet al., 1994).


The range and mean of different water qualityparameters are given in Table 2.

The pH is important parameter fordetermining acidity, neutrality or alkalinity ofwater. The pH of water samples ranged from 7.36-9.80 with a mean value of 8.19 indicating that thewater is neutral to alkaline in nature. Bhat et al.(2016) reported pH in range of 7.19-9.72 inGohana block of Sonipat district. The lowest valuewas observed in village Chaba and highest inChand Chak. The spatial variability of pH inGuhla block is shown in Fig. 2. Variation inelectrical conductivity reflects the variation of totalsoluble salt concentration and ultimately the

salinity of the groundwater samples. The electricalconductivity of water varied from 0.30-2.31 dSm-1 with mean value of 1.24 dS m-1. According toEC, water is classified as moderate to good quality.The lowest electrical conductivity was recordedin village Azimgarh and highest in ThehMukerian. The spatial variability of EC in Guhlablock is presented in Fig. 3.

The average chemical composition and relatedparameter in different EC classes for Guhla blockare given in Table 3. The distribution of groundwater samples with increasing EC indicated thatthe percent samples in EC classes is in irregulartrend, firstly increased upto 1-2 EC class, andthereafter, showed a sharp decline in percentageof water sample. The maximum number ofsamples (75) was concentrated in EC class of 1-2.Average SAR and RSC of the EC class 0-1 wasthe highest 9.37 (mmol l-1)1/2 and 2.30 me l-1,respectively. Kumar et al. (2013) reported that ECvaried from 0.79-9.38 dS m-1 in Lakhan MajraBlock of Rohtak district. Gagandeep et al. (2017)reported that the mean chemical composition andrelated quality parameters in different EC classesof block Palwal and percent distribution of samplein different EC classes. Percentage of samples indifferent EC classes is different, its highest percent-age (34.1) was found in EC class of 1-2 dS m-1

and its lowest percentage (0.8) was found in ECof class 8-9 dS m-1 and 10-11 dS m-1. In EC rangeof 0-2 dS m-1, there were 40.9 percent sampleswhich is nearly an indication of good quality

Table 1. Methods used for estimation of different hydro-chemical parameters of groundwater in the study area

Parameters Method used as described byRichards (1954)

pH Glass electrodeEC (Electrical Conductivity) Conductivity Bridge methodNa+ (Sodium) Flame Photometric methodK+ (Potassium) Flame Photometric methodCa2+ (Calcium) EDTA titration methodMg2+ (Magnesium) EDTA titration methodCO3

2- (Carbonate) Acid titration methodHCO3

-(Bicarbonate) Acid titration methodCl- (Chloride) Mohr’s titration methodNO3

- (Nitrate) Spectrophotometric methodSO4

2- (Sulphate) Turbidity method using CaCl2

Table 2. Range and mean of different water quality parametersof Guhla block

Sr. No. Quality parameter Range Mean

1 pH 7.36-9.80 8.192 EC (dS m-1) 0.30-2.31 1.243 RSC (me l-1) nil-5.80 2.204 SAR (mmol l-1)1/2 2.55-14.39 6.125 Ca2+ (me l-1) 0.20-2.00 0.926 Mg2+(me l-1) 0.80-4.90 2.697 Na+ (me l-1) 1.80-18.20 8.308 K+ (me l-1) 0.06-0.42 0.159 CO3

2- (me l-1) 0.00-3.20 1.0010 HCO3

- (me l-1) 0.30-8.60 4.7211 Cl- (me l-1) 1.40-10.90 4.1612 SO4

2- (me l-1) 0.04-7.13 1.8413 NO3

- (me l-1) nil-1.94 0.32

244 Singh et al.

Fig. 2. Spatial variability of pH of groundwater in Guhla Block

Fig. 3. Spatial variability of EC of groundwater in Guhla Block


groundwater according to AICRP criteria basedon EC only.

The concentration of cations viz., calcium,magnesium, sodium and potassium in watersamples varied from 0.20-2.00, 0.80-4.90, 1.80-18.20 and 0.06-0.42 me l-1 with average of 0.92,2.69, 8.30 and 0.15 me l-1. The cationicconcentration followed the order- sodium,magnesium, calcium and potassium. Sodium andmagnesium were the dominant cations andaccounted for 68.83 and 22.31% of the totalcations, respectively. The presence of sodium ingroundwater primarily results from the chemicaldecomposition of feldspars, feldspathoid andsome iron, magnesium minerals. The amount ofNa+ ions in the water predicts the sodicity dangerof the water (Singh, 2000). Calcium andpotassium were lesser in importance andconstituted 7.60 and 1.26%, respectively. Thepresence of Ca2+ in groundwater might beattributed to calcium-rich minerals such asamphiboles, pyroxenes and feldspars and the Mg2+

in groundwater might be due to olivine mineraland the ion exchange of minerals in thesurrounding rocks and soils. Averageconcentration of sodium, magnesium and calciumshowed irregular trend with increase in EC whilepotassium showed the steady trend. Theconcentration of anions viz., carbonate,bicarbonates, chloride, sulphate and nitrate variedfrom nil-3.20, 0.30-8.60, 0.04- 7.13 and nil-1.94me l-1 with average values of 1.00, 4.72, 4.16, 1.84and 0.32 me l-1, respectively. Bicarbonate andchloride were the major ions accounting 39.28 and33.97% respectively of the total anions. Sulphate,carbonate and nitrate were secondary inimportance comprising 15.60, 8.42 and 2.74%,respectively. The reasons for carbonate (CO3

2–) andbicarbonate (HCO3

–) concentrations ingroundwater can be ascribed to carbonate

weathering as well as from the dissolution ofcarbonic acid in the aquifers. Kumar et al. (2013)analyzed groundwater quality of Lakhan MajraBlock of Rohtak district and reported that theorder of abundance of cations was Na+> Mg+>Ca+> K+ and those of the anions were Cl–> HCO3

–

> SO42–> CO3

2–.

Sodium adsorption ratio

The sodium absorption ratio (SAR) was recordedin the range of 2.55-14.39 (mmol l-1)1/2 with meanvalue of 6.12 (mmol l-1)1/2.The maximum valuewas observed in village Kasauli and minimum invillage Azimgarh. The Spatial variability of SARof groundwater in Guhla block is presented in Fig.4. Bhat et al. (2016) reported that SAR varied from4.03-24.16 (mmoll-1)1/2 in groundwater of Gohanablock, Haryana. Isaac et al. (2009) ascertained thatthe SAR of soil solution is increased with theincrease in SAR of irrigation water whicheventually increases the exchangeable sodium ofthe soil.

Residual Sodium Carbonate

For agricultural purposes, residual sodiumcarbonate (RSC) is usually used to evaluate thedeleterious effect of carbonate and bicarbonate onthe quality of water. The residual sodiumcarbonate was recorded in the range of nil-5.80me l-1 with the mean value of 2.20 me l-1. Themaximum value was observed in village Kasauliand minimum value was found in village Diwana.Naseem et al. (2010) reported that pH, EC andSAR of the irrigation water are significantlyinfluenced by RSC. The Spatial variability of RSCof groundwater in Guhla block is shown in Fig.5.

According to AICRP on Management of SaltAffected Soils and Use of Saline Water in

Table 3. Average chemical composition of water samples in different EC classes of Guhla block

EC No of Per cent CO32- HCO3

- Cl- SO42- NO3

- Ca2+ Mg2+ Na+ K+ RSC SARclasses samples of me l-1 (mmol(dS m-1) samples l-1)1/2

0-1 29 16.51 0.70 4.89 3.19 1.20 0.32 0.83 2.45 6.94 0.16 2.30 9.371-2 75 77.06 1.01 4.71 4.53 2.06 0.32 0.96 2.81 8.88 0.15 2.20 6.422-3 05 6.42 0.70 2.86 2.82 4.07 0.24 0.79 2.30 7.37 0.16 1.80 5.93

246 Singh et al.

Fig. 5. Spatial variability of RSC of groundwater in Guhla Block

Fig. 4. Spatial variability of SAR of groundwater in Guhla Block


Agriculture classification, out of 109 watersamples 69 were of good quality, 3 marginallysaline, 12 marginally alkali, 24 alkali, and 1 highlyalkali (Table 4).

Eaton FM (1950) Significance of carbonates in irrigationwaters. Soil Science 69: 123–133.

FAO (1985) Soil Survey Investigation for Irrigation. Soil Bulletin42, Agriculture Organization of the United Nation,Rome, Italy.

Gagandeep, Ram Prakash, Kumar Sanjay, Rajpaul, Satyavanand Sharma SK (2017) Ground water quality assessmentfor irrigation in Palwal block of Palwal district, Haryana,India. Journal of Applied and Natural Science 9(1): 34–38.

Gupta RK, Singh NT and Sethi M (1994) Water Quality forIrrigation in India. Technical Bulletin 19, CSSRI, Karnal,India.

Isaac RK, Khura TK and Wurmbrand JR (2009) Surfaceand subsurface water quality appraisal for irrigation.Environmental Monitoring Assessment 159: 465–473.

Jain CK, Bandyopadhyay A and Bhadra A (2012) Assessmentof ground water quality for irrigation purpose, districtNainital, Uttarakhand, India. Journal of Indian WaterResources Society 32(3-4): 8-14.

Kumar S, Sharma SK, Rajpaul, Ramprakash and Satyavan(2013) Mapping groundwater quality for Lakhan Majrablock of Rohtak district (Haryana). Annals of Agri BioResearch 18(2): 186-190.

Nag SK and Das S (2014) Quality assessment of groundwaterwith special emphasis on irrigation and domesticsuitability in Suri I & II Blocks, Birbhum District, WestBengal, India. American Journal of Water Resources 2(4):81-98.

Naseem S, Hamza S and Bashir E (2010) Groundwatergeochemistry of winder agricultural farms, Balochistan,Pakistan and assessment of irrigation water quality.European Water 31: 21-32.

Packialakshmi S, Ambujam NK and Nelliyat P (2011)Groundwater market and its implications on waterresources and agriculture in the southern peri-urbaninterface, Chennai, India. Journal of Environment,Development and Sustainability 13(2): 423–38.

Richards LA (1954) Diagnosis and Improvement of Saline AndAlkali Soils: U.S. Department of Agriculture Handbook60, 160 p.

Sharma BK (2005) Water Pollution, 4th edn. Goel PublishingHouse, Meerut.

Singh J, Shanwal AV and Verma SL (2000) Poor qualityirrigation water and secondary salinization in semi-aridregion of Rajasthan. Annals of Agri. Bio. Research 5(2):127-130.

Singh KP, Malik A, Mohan D, Vinod KS and Sinha S (2006)Evaluation of groundwater quality in northern Indo-Gangetic alluvium region. Environmental Monitoring andAssessment 112: 211-230.

Table 4. Ground water quality classification of Guhla Block

Water quality Class Number Percentageof samples

Good A 69 63.2

Saline B

Marginally Saline B1 3 2.7

Saline B2 0 0

High SAR Saline B3 0 0

Alkali Water C

Marginally Alkali C1 12 11.1

Alkali C2 24 22.1

Highly alkali C3 1 0.9

Total 109

Conclusions

The groundwater analysis of Gulha Blockindicated that various constituents are inpermissible limits; therefore, the groundwater cansafely be used for irrigation purpose. Anions werefound in order of HCO3

-> Cl-> SO42-> CO3

2->NO3

- and cations followed the order Na+> Mg2+>Ca2+> K+. However, at some places, where thewater is of doubtful category, care is to be takento use the water for irrigation. The spatialdistribution maps generated for various physico-chemical parameters using GIS techniques couldbe valuable for policy makers for initiatinggroundwater quality monitoring in the area.

References

Adhikary PP, Dash CJ, Kumar G and Chandrasekharan H(2014) Characterization of groundwater quality forirrigation and drinking purposes using a modifiedgroundwater quality index. Indian Journal of SoilConservation 42(3): 260-267.

Ahamed AJ, Ananthakrishnan S, Loganathan K andManikandan K (2013) Assessment of groundwaterquality for irrigation use in Alathur Block, PerambalurDistrict, Tamilnadu, South India. Applied Water Science3: 763–771.

Bhat MA, Grewal MS, Ramprakash, Rajpaul, Wani SA andDar EA (2016) Assessment of groundwater quality forirrigation purposes using chemical indices. Indian Journalof Ecology 43(2): 574-579.

248 Singh et al.

Vishwanath J, Ravikumar D, Karegoudar AV, Anand SR andRajkumar RH (2016) Characterization of ground waterfor irrigation in Dharwad District of Karnataka. J SoilSalinity & Water Quality 8(2): 202-206

Vrba J and Zoporozec A (1994) Guidebook on MappingGroundwater Vulnerability. IAH InternationalContribution for Hydrogeology, Heise, Hannover, v.16,131p.

Zinabu E, Yazew E and Haile M (2010) Assessment of theimpact of industrial effluents on the quality of irrigationwater and changes on soil characteristics (A Case ofKombolcha Town). Fourteenth International WaterTechnology Conference, IWTC 14 2010, Cairo, Egypt.pp. 711-727.

Received in July, 2017; Accepted in September, 2017

Characterization of Soils and Cropping Pattern of CoastalWest Bengal - A Case Study in Canning II Block

R Srinivasan1*, SK Singh2, T Chattopadhyay3, SK Gangopadhyay3

,

DC Nayak3 and S Mukhopadhyay3

1ICAR- National Bureau of Soil Survey and Land Use Planning, Regional Centre, Hebbal, Bangalore-560024, India2ICAR- National Bureau of Soil Survey and Land Use Planning, Amravati Road, Nagpur-440033, India

3ICAR- National Bureau of Soil Survey and Land Use Planning, Regional Centre, Salt lake, Kolkata-700091, India*Corresponding author E-mail: [email protected]

Abstract

Major soils and land-use of Canning II block, representing coastal region of West Bengal studied. The soilswere deep to very deep, brownish, varied from silt loam to clay. These are very strongly acidic to moderatelyalkaline (pH 3.9 to 8.8) in soil reaction, slight to moderately saline (ECe 0.57 to 14.3 dS m-1), low to high inorganic carbon (OC) content (0.08- 1.45%) and low in cation exchange capacity [6.9 to 19.2 cmol (p+) kg-1] andbase saturation (52 to 93%). Among the exchangeable cations, calcium is found to be dominant in all soils,followed by magnesium, sodium and potassium. Major land use in kharif is paddy followed by boro paddy(summer), and vegetables and oilseeds are grown in rabi and summer season with the help of tube well irrigation.The soils identified and mapped and qualify order Inceptisols. Based on the characteristics, soils were classifiedas Fluventic Endoaquepts, Typic Halaquepts, Typic Endoaquepts and Typic Haplustepts. Soil potentials andproblems were assessed and suitable cropping system and management practices for each soil series are suggested.

Key words: Cropping pattern, Soil series, Landuse, Inceptisols, Soil salinity, Boro paddy

Introduction

Indian has coastline stretching 8,129 km coveringGujarat, Goa, Maharashtra, Karnataka andKerala in the west, and Tamil Nadu, AndhraPradesh, Orissa and West Bengal in the east,besides Lakshadweep, Andaman Nicobar groupof Islands, and Union Territories of Pondicherry,Daman and Diu accounting 10.78 M ha of TGA(Velayutham et al., 1999). The coastal agro-eco-region is distributed over nine coastal states, outof whichWest Bengal, Orissa and Andhra Pradeshcover two agro-ecological sub-regions (AESR).The delta region of the river Ganges, occurs inthe coastal tracts of North and South 24-Parganasdistricts of West Bengal constituting 0.82 millionhectares and 220 km of coastal line (Chakraborty,2013) with wide variability in climatic,topographical and edaphic conditions (Mitran etal., 2014).

Agriculture is the main source of livelihoodfor the people of coastal region. The coastal landsare predominantly mono-cropped paddy with very

low productivity. The coastal soils occur as riverdeltas, connected with mainland, islands rangingfrom a few kilometers to about 50 km from thesea-coast. There is wide variation among thecoastal soils, land use pattern and agro-climaticconditions.

Soil salinity is common problem in the South24-Parganas of West Bengal. Salinity buildup andlack of irrigation water during dry months (rabiand summer), excess water logging in crop lands(in kharif), etc. are common problems which arefurther compounded by frequent natural disasterslike cyclone, seawater intrusion, drought etc. Thesoil salinity starts increasing after the kharif seasonon cessation of monsoon rains and reaches itspeak in the month of May-June, before the onsetof next monsoon rains. The salinity buildup ismostly attributed to the upward capillarymovement of water from brackish groundwatertable located at shallow depth (Bandyopadhyay etal., 2011). Following the evaporation of water, thesalts accumulate in the soil surface and the salinity


250 Srinivasan et al.

of soil increases as the dry spell proceeds.Ingression of saline tidal water from the sea orthe tidal rivers also contributes to the saltaccumulation in soil.

Therefore, sustainable utilization of land-usepotential may be achieved through effectivemanagement of resources, which requires site-specific detailed information on land resources.In this context, a case study was attempted tocharacterize soils and land use in Canning II blockas a representative of coastal system of WestBengal.


A case study was taken up during 2013-14 inCanning II block under division of South 24-Paraganas district of West Bengal which is closeto the Bay of Bengal. The block consists of 9 Gram-panchayats and 62 villages and covers an area of21,493 ha, which is 2.15% of total geographicalarea (TGA) of the district (Fig. 1).

Geologically the area comprises of sub-recentand recent alluvium of the Ganga river system.The coastal alluvium is of the Holocene period.The recent alluvium formations are mainly themixture of sand, silt and clay materials of varyingproportions. The climate of the block is sub-tropical, sub-humid with hot humid summers andcool winters. The pre-monsoon starts in April-Mayand the actual monsoon begins in the month ofJune, which recedes by September. The averageannual rainfall is 1600 mm. The mean maximumand minimum air temperatures are 34.5 °C and18.3 °C, respectively and the mean annualtemperature is 27.0 °C. The soil temperature classis hyperthermic. The soil moisture regime is “aquic”.The area belongs to Agro-eco Sub Region (AESR)18.5, which is hot sub-humid plain with LGP of180-210 days. Major land use is paddy in entirearea during kharif followed boro paddy, vegetablesand oilseed crops during rabi and summer seasonswith the help of tube well irrigation (Table 1).

Fig. 1. Location map of study area

Table 1. Landscape characteristics of study area

Pedons Series Slope (%) Drainage Land use

1 Srinagar 1-3 Moderately well drained Paddy-oilseeds/vegetables2 Gabbuni 0-1 Somewhat poorly drained Paddy-paddy3 Bibirabad 0-1 Poor Paddy-fallow4 Moktarpur 0-1 Somewhat poorly drained Paddy-vegetables5 Deuli 0-1 Poor Paddy-oilseeds/vegetables

Soils and cropping pattern of coastal West Bengal 251

Detailed soil survey was carried out on1:10,000 scale by using base map prepared fromremote sensing satellite data (1RS-P6 LISS IV) inconjunction with village cadastral map and Surveyof India (SOI) topo-sheets for delineation ofphysiographic units. Major landform is level (0-1%) and nearly level (1-3%). Profile observationsand auger samplings were done to cover all thephysiographic units to confirm the soil landform

relationship. In total 68 soil profiles and 139 augerbores were studied to delineate the variation insoil characteristics and current land use (Fig. 2).After final correlation, five soil series with twelvemapping units were established (Fig. 3).

The collected soil samples were air-dried,ground and processed by sieving and labeled. Thesamples were analyzed for their mechanical

Fig. 2. Land use map of the study area

*sri- Srinagar series; sic-silty clay texture; d5-very deep soil depth; S2 –slight saline; A- 0-1% soil slopeFig. 3. Soil map of the study area


fractions and physical and chemical properties asper standard methods (Jackson, 1973; Page et al.,1982). The soils were classified as per guidelinesgiven in Key to Soil Taxonomy (Soil Survey Staff,2010). Land evaluation of the identified soil serieswas carried out through Land CapabilityClassification (AIS & LUS, 1970; Sys et al., 1991).


Cropping pattern

Rice-based cropping systems viz. rice-rice, rice-fallow, rice-oilseed (sesamum, ground nut andsunflower), rice-vegetables (ladies finger/bhindi,tomato, brinjal, bitter gourd and pumpkin) areprevailing in the block in kharif/rabi seasons (Table2). The selection of crops and cropping systemare based on irrigation water facility as well asquality. When canal irrigation is available, farmersare cultivating boro paddy, whereas, vegetables andoilseeds are cultivated by using bore-wellirrigation. The available water from surface andground water sources are not meeting the waterdemand for agriculture during rabi and summercrop seasons. When water deficit situation exists,lands are kept fallow and areas with sufficientgroundwater available for second crop farmersgrow vegetables and oil seeds. Almost similarcropping patterns were also earlier reported bySarangi et al. (2012).

Soil characteristics

Soil morphology

Brief morphological features of the soils arepresented in Table 3. The solum depth is deep

(100-150 cm) to very deep (>150 cm). Munsellcolour notation of soil in hue of 10YR/2.5Y withvalue 6 to 3 and chroma 4 to 1. Srinagar andMoktarpur series had dark greyish brown colourin surface and dark grey brown to brown colourin sub-soils. Gabbuni and Bibirabad series are lightolive brown and very dark grayish brown insurface and very dark gray to olive brown in sub-surface soils. Deuli series is yellowish brown insurface and dark yellowish brown to olive brownin lower horizons. Gabbuni series has sporadicdistribution of mottles in lower layers, colourvaried from yellowish red (5YR 4/6) to dark red(2.5YR 3/6) which may be due to presence ofironic materials (Srinivasan et al., 2015).

Soil texture varied from silt loam to clay. Thetextural variation might be due to variation indepositional cycle by rivers and sea. Based onvariable soil characteristics in all soil series, wedo not find any specific characteristics so as toqualify for a particular diagnostic horizontherefore suggesting presence of ochric epipedons.However, the lower horizons are physically andchemically altered horizons formed due to thestratification of texture, structure and colour,hence qualifying for cambic endopedons. Thestructure of soils is sub-angular blocky type. Thedry consistency is observed only in surface layerwhich is slightly hard and moist; and consistencyis friable, slightly sticky to sticky and slightly plasticto plastic.

Physical characteristics

The detailed physical characteristics of the soilsare presented in Table 3. Granulometric datarevealed that the clay content varied from 5.1 to58.7 %. The irregular distribution of clay is shownin all the series, which may be due to river waterfluctuation in different periods (Gour, 2012). Insubsequent horizons, the clay content graduallyincreased and then decreased. Silt content in allpedons were high (39.1-84.2%) and exhibited anirregular trend with depth. Sand constitution isvery narrow due to coastal soils which are mostlyfine textured and vary widely from place to placedepending on their physiographic locations,climatic conditions and soil parent materials(Bandyopadhyay et al., 2003; Maji et al., 1998).

Table 2. Current land use and area occupied in study area

Current land use classes Area (ha) (%) of TGA

Single crop (kharif paddy) 2189 10.18Double crop (paddy- paddy) 10129 47.13Double crop (paddy-oil seeds) 603 2.81Double crop (paddy-vegetables) 3296 15.34Aquaculture 2594 12.07River 230 1.07Habitation 1091 5.07Homestead garden 1361 6.33Total 21493 100.00

TGA=Total geographic area


Table 3. Morphological and physical characteristics of the soils

Depth Horizon Colour Mottle Sand Silt Clay Texture Structure Consistency(cm) (moist) colour (2.0-0.05) (0.05-0.002) (<0.002) S G T D M W

(mm)

Pedon 1- Srinagar series: Fine, mixed, hyperthermic Fluventic Endoaquepts0-13 Ap 10 YR4/2 - 0.2 71.1 28.7 sicl puddled shfr s/p13-30 Bw1 10 YR 3/1 - 3.1 62.8 34.1 sicl m 2 sbk - fr s/p30-62 Bw2 10 YR 3/1 - 2.2 39.1 58.7 c m 2 sbk - fr s/p62-95 Bw3 10 YR 4/2 - 1.7 50.2 48.1 sic m 2 sbk - fr s/p95-138 Bw4 2.5 Y 4/2 - 31 63.9 5.1 sil f 2 sbk - vfrss/spPedon 2- Gabbuni series: Fine, mixed, hyperthermic, Typic Halaquepts0-12 Ap 2.5 Y 5/4 - 1.9 54.0 44.1 sic puddled shfr s/p12-30 Bwg1 10 YR 3/2 5 YR 4/6 4.2 53.5 42.3 sic m 2 sbk - fr s/p30-63 Bwg2 10 YR 3/2 2.5YR 3/6 8.3 53.9 37.8 sicl m 2 sbk - fr s/p63-87 Bwg3 10 YR 3/1 2.5YR 3/6 5.5 54.4 40.1 sic m 2 sbk - fr s/p87-114 Bwg4 10 YR 3/1 2.5YR 3/6 5.4 50.3 44.3 sic m 2 sbk - fr s/pPedon 3- Bibirabad series: Fine- silty, mixed, hyperthermic Typic Halaquepts0-15 Ap 2.5 Y 3/2 - 1.5 68.8 29.7 sicl puddled shvfr s/p15-33 Bn1 2.5 Y 6/2 - 4.4 69.3 26.3 sil m 2 sbk - frss/sp33-70 Bn2 2.5 Y 5/2 - 13.1 78.1 8.8 sil m 2 sbk - frss/sp70-105 Bn3 2.5 Y 4/4 - 10.5 69.8 19.7 sil m 2 sbk - frss/spPedon 4- Moktarpur series: Fine-silty, mixed, hyperthermic, Typic Endoaquepts0-14 Ap 10 YR4/2 - 0.9 78.6 20.9 sil puddled shfrss/sp14-31 Bw1 10 YR 4/1 - 0.5 76.3 23.2 sil m 2 sbk - frss/sp31-45 Bw2 10 YR 4/1 - 2.2 79.9 17.9 sil m 2 sbk - frss/sp45-74 Bw3 10 YR 3/3 - 6.3 80.5 13.2 sil m 2 sbk - frss/sp74-120 Bw4 10 YR 5/3 - 1.4 84.2 14.4 sil f 2 sbk - frss/spPedon 5- Deuli series: Fine-silty, mixed, hyperthermic Typic Haplustepts0-18 Ap 10 YR 5/4 - 0.7 74.9 24.4 sil puddled shfrss/sp18-48 Bw1 10 YR 5/4 - 0.1 66.2 33.7 sicl m 2 sbk - frss/sp48-82 Bw2 10 YR 4/4 - 0.6 73.5 25.9 sil m 2 sbk - frss/sp82-115 Bw3 10 YR 4/3 - 4.6 82.4 13.0 sil m 2 sbk - frss/sp115-150 Bw4 2.5 Y 4/4 - 2.7 83.7 13.6 sil m 2 sbk - frss/sp

Chemical characteristics

Chemical characteristics of the soils are presentedin Table 4. All the soil series are very stronglyacidic to moderately alkaline (3.9 to 8.8) in soilreaction (pH) with electrical conductivity (ECe)ranging from 1.14 to 14.3 and 0.57 to 9.72 dS m-

1 in surface and sub-soils, respectively. Varying soilreaction (pH) is controversy with saltconcentration (EC) and sodium level (ESP) inSundarban coastal system of West Bengal, whichmay qualify as acid saline soil/saline sodic soil.Salinity level remains least during the monsoonseason due to huge fresh water inflow and rainfallthat washes away the soluble salts, and reachmaximum concentration in summers when highevapotranspiration draws out the soil moisture

through capillary action, leaving the salt depositson the top soil known as salt encrustations (Hazraet al., 2016; Haldar and Debnath, 2014;Bandyopadhyay et al., 2003).

The organic carbon of the soils was found tobe high in surface (0.51- 1.41%) and low in sub-surface (0.08- 0.62%) except in Gabbuni series.The distribution of organic carbon followedirregular pattern with depth. In some pockets ofstudy area, lower part of the profiles containedhigh amount of organic carbon which could bedue to mixing of crop residues and degradedwooden materials within soils (Bandyopadhyayet al., 1998). Cation exchange capacity and basesaturation varied from 6.9 to 19.2 cmol (p+) kg-1

and 52 to 93%, respectively, whereas,


Table 4. Chemical characteristics of soils

Depth Horizon pH(1:2.5) ECe OC Exchangeable cations CEC BS ESP(cm) H2O 1N KCl (dS m-1) (%) Ca Mg Na K Sum of (%)

(1 N NH40Ac, pH 7.0) cations cmol (p+) kg-1

Pedon 1- Srinagar series: Fine, mixed, hyperthermic Fluventic Endoaquepts0-13 Ap 5.4 - 1.14 0.77 4.9 2.3 0.2 0.5 7.9 12.3 64 1.6213-30 Bw1 7.2 - 0.57 0.35 7.9 3.4 0.4 0.5 12.2 14.4 85 2.7730-62 Bw2 7.9 - 0.74 0.39 9.8 6.2 0.5 0.6 17.1 19.2 89 2.6062-95 Bw3 8.0 - 1.25 0.27 8.4 5.8 0.4 0.4 15 17.1 88 2.3395-138 Bw4 8.8 - 1.32 0.08 1.1 0.7 0.2 0.2 2.2 13.0 73 1.53Pedon 2- Gabbuni series: Fine, mixed, hyperthermic, Typic Halaquepts0-12 Ap 4.2 3.9 14.3 1.41 4.8 1.5 2.6 0.5 9.4 16.2 58 16.0412-30 Bwg1 4.3 3.7 5.20 0.70 5.0 1.5 2.4 0.6 9.5 15.8 60 15.1830-63 Bwg2 4.1 3.5 4.68 0.92 4.6 1.4 2.8 0.6 9.4 14.9 63 18.7963-87 Bwg3 3.9 3.3 5.46 0.99 4.7 1.5 1.7 0.6 8.5 16.3 52 10.4287-114 Bwg4 4.1 3.5 5.85 1.45 5.1 1.6 1.8 0.7 9.1 17.3 53 10.40Pedon 3- Bibirabad series: Fine- silty, mixed, hyperthermic Typic Halaquepts0-15 Ap 8.0 7.5 7.81 0.51 7.0 2.6 2.4 0.5 12.5 13.8 90 17.3915-33 Bn1 8.3 7.7 4.84 0.20 6.0 2.4 2.2 0.4 11.0 11.8 93 18.6433-70 Bn2 8.1 7.6 3.16 0.26 5.5 1.3 1.8 0.3 8.9 9.7 92 18.5570-105 Bn3 7.3 6.8 6.00 0.39 6.7 2.0 2.3 0.5 11.5 13.5 85 17.03Pedon 4- Moktarpur series: Fine-silty, mixed, hyperthermic, Typic Endoaquepts0-14 Ap 5.7 - 2.96 1.05 4.4 1.8 0.2 0.1 6.5 10.5 62 1.9014-31 Bwg1 7.7 - 2.62 0.33 5.7 2.8 0.3 0.5 9.3 11.2 83 2.6731-45 Bwg2 8.2 - 4.68 0.24 4.8 1.5 0.2 0.5 7.0 8.0 87 2.5045-74 Bw1 8.2 - 5.47 0.09 4.1 1.8 0.2 0.2 6.3 7.3 86 2.7374-120 Bw2 8.3 - 5.92 0.08 5.0 1.6 0.2 0.2 7.0 8.1 86 2.46Pedon 5- Deuli series: Fine-silty, mixed, hyperthermic Typic Haplustepts0-18 Ap 7.5 - 4.11 0.79 6.5 2.6 0.4 0.3 9.8 11.6 84 3.418-48 Bw1 8.2 - 2.46 0.39 9.7 4.2 0.3 0.4 14.6 15.8 92 1.848-82 Bw2 8.2 - 6.88 0.3 7.1 2.5 0.4 0.3 10.3 11.5 89 3.482-115 Bw3 8.2 - 8.20 0.8 3.8 1.4 0.5 0.2 5.9 7.1 83 7.0115-150 Bw4 8.1 - 9.72 0.62 3.8 1.1 0.4 0.2 5.5 6.9 80 5.7

exchangeable bases were distributed in thefollowing order of Ca2+> Mg2+> Na+> K+ on theexchange complex of soils. Exchangeable cationsare in trace amounts due to high rainfall, althoughcalcium is found slight higher among the cations.Exchangeable sodium percentage (ESP) variedfrom 1.53 to 18.79% and was maximum inGabbuni and Bibirabad series (above 15%). Theabove findings agree with those Srinivasan et al.(2015) and Bandyopadhyay et al. (2003).

Interpretative groupings

The land capability classification was found to beinterpretative grouping of different soil unitsindicating the relative suitability of soils for

cultivation of crops, pastures and agroforestry inaddition to focusing the inherent problems thatneed preventive management measures(Klingebiel and Montgomery, 1966). Based on thecriteria, the soils of Canning II block have beenclassified into three land capability classes and sub-classes for better management of lands (Table 5).

The Gabbuni and Deuli series were placed inthe land capability class IIIws, whereas, Srinagar,Moktarpur Bibirabad were IIs, IIws and IVsw,respectively. By adopting suggested land use in therespective areas, sustained crop production canbe achieved as it helps in better management ofsoil and water besides the reclamation of salt-affected soils.


Conclusions

The present study concludes that characterizationof soils and land use in coastal region is the firststep of land and soil improvement. However, soilis considered as a key for better crop and nutrientmanagement. Major land use in coastal areas ispaddy-based cropping system and soils are verystrongly acidic to slightly alkaline. The electricalconductivity (ECe) is ranging from 0.57 to 14.3dS m-1 which is the indication of prevailing ofslight to severe soil salinity. OC content of the soilswas found to be low to high (0.08- 1.41%) andCEC and base saturation varied from 6.9 to 19.2c mol (p+) kg-1 and 52 to 93%, respectively. Studyindicated that the lands are nearly level (0-1%)with poor drainage and fine textured favorable forpaddy which is more adoptable to aquic soilregime. Based on the soil properties, three landcapability classes were established and suitableland use options have been suggested forincreasing crop yield sustaining crops production.

Table 5. Interpretation of soils in study area

Soil series Land Description Major limitations Suggested land usecapabilityclass withlimitations

Srinagar IIs Good cultivable Soils having Soils have the potential for paddy cultivation in kharif andland for problems of rabi season and when deficient of water oilseed (ground nut,sustainable heavier texture gingelly and mustard) and vegetables (cabbage, bhindi andagriculture and with slight to tomato) can be grown in rabi season with proper soil and

moderate salinity nutrients management practices.Gabbuni IIIws Moderately Soils have poor Soils are suitable for paddy in both seasons with proper

good cultivable drainage and irrigation facility, parts of soils are suitable for cultivationland for moderate salinity of selective salt tolerant pulses and vegetables with bettersustainable soil and nutrient management.agriculture

Bibirabad IVsw Fairly good Soils have high Construction of alternate raised beds and furrows iscultivable land salinity during advocated to improve the drainage condition andfor sustainable summer and poor reclamation with gypsum could control the saline sodicagriculture drainage condition condition. Cultivation of paddy during rainy season and

in rainy season some salt tolerant vegetables and grasses can be grownduring rabi season.

Moktarpur IIws Good cultivable Soils are somewhat Paddy can be grown in both seasons, but when deficient ofland for poorly drained and irrigation water, selective oil seeds, pulses and vegetablessustainable having silt loam can be cultivated during summer. Soils with relatively lessagriculture texture with slight problem, farmers can go for better fertilizer and crop

salinity management to get maximum yield.Deuli IIIws Moderately Soils are coarse Cultivation with precaution to avoid permanent damage;

good cultivable textured and have moderate soil reclamation can be done by applying gypsumland for moderate to strong and leaching with good quality irrigation water. Growingsustainable salinity of paddy in kharif and few selective salt tolerant vegetables,agriculture fruit crops and grasses may be preferred in summer.

References

AIS and LUS (1970) Soil Survey Manual. Department ofAgriculture, Govt. of India, IARI Campus, New Delhi.

Bandyopadhyay BK, Burman D and Mandal S (2011)Improving agricultural productivity in degraded coastalland of India- experiences gained and lessons learned.Journal of Indian Society of Coastal Agricultural Research29: 1-9.

Bandyopadhyay BK, Maji B, Sen HS and Tyagi NK (2003)Coastal Soils of West Bengal- Their Nature, Distribution andCharacteristics. Bull. No.1/2003. Central Soil SalinityResearch Institute, Regional Research Station, CanningTown, West Bengal, India, p62.

Bandyopadhyay BK, Sahu GC and Maji B (1998) Status,nature and composition of organic matter in coastalareas. Journal of the Indian Society of Soil Science 19: 58-67.

Chakraborty SK (2013) Interactions of environmentalvariables determining the biodiversity of coastalmangrove ecosystem of West Bengal, India. The Ecoscan3: 251-265.

Gour J (2012) Changing fluvio-geomorphologicalenvironment in the Matla-Bidyadhari Interfluve- a model


unit of active and mature Indian Sundarbans. Geo-Analyst2: 1-7.

Haldar A and Debnath A (2014) Assessment of climateinduced soil salinity conditions of Gosaba Island, WestBengal and its influence on local livelihood. In: ClimateChange and Biodiversity: Proceedings of IGU RohtakConference (vol 1). Advances in Geographical andEnvironmental Sciences. pp. 27-44.

Hazra S, Bhadra T and Sinha Roy SP (2016) Sustainablewater resource management in the Indian SundarbanDelta. In: Proceeding of International Seminar onChallenges to Ground Water Management: Vision 2050. pp324-334.

Jackson ML (1973) Soil Chemical Analysis. Prentice Hall ofIndia Pvt. Ltd., New Delhi.

Klingebiel AA and Montgomery PH (1966) Land CapabilityClassification. Agri. Book No. 210, Soil ConservationSeries, USDA, Washington D.C.

Maji B, Bandyopadhyay BK, Sarkar D and Chatterji S (1998)Morphological and chemical characterization of soilsof Sagar Island of the Sundarbans, West Bengal. Journalof the Indian Society of Soil Science 46(1): 99-103.

Mitran T, Mani PK, Basak N, Mandal B and MukhopadhyaySK (2014) Soil fertility constraint assessment usingspatial nutrient map at three selected villages of coastalSundarbans. Journal of Soil Salinity and Water Quality6(1): 1-8.

Page AL, Miller RH and Keeney DR (1982) Methods of SoilAnalysis, Part 2, 2nd Edition, Soil Science Society ofAmerica, Madison, USA.

Sarangi SK, Mahanta KK, Mandal S and Maji B (2012)Characterization of soils and cropping pattern of coastalareas of Haldia, Paradip and Visakhapatnam ports.Journal of Indian Society of Coastal Agricultural Research30(2): 12-18.

Soil Survey Staff (2010) Keys to Soil Taxonomy. EleventhEdition. U.S.D.A.: Washington, D.C.

Srinivasan R, Mukhopadhyay S, Nayak DC and Singh SK(2015) Characterization, classification and evaluationof soil resources in coastal ecosystem- a case study ofGosaba Block (Part), South 24 Parganas, West Bengal.Agropedology 25(2): 195-201.

Sys C, Van Ranst E and Debaveye J (1991) Land Evaluation,Part-II- Methods in Land Evaluation. AgriculturalPublications No.7, GADC, Brussels, Belgium.

Velayutham M, Sarkar D, Reddy RS, Natarajan A, KrishanP, Shiva Prasad CR, Challa O, Harindranath CS,Shyampura RL, Sharma JP and Bhattacharyya T (1999)Soil resource and their potentialities in coastal areas ofIndia. Journal of Indian Society of Coastal AgriculturalResearch 17: 29-47.


Assessment of Soil Degradations in Coastal Ecosystem ofSundarbans, West Bengal- A Case Study

R Srinivasan*1, SK Singh2 and DC Nayak3

1ICAR-National Bureau of Soil Survey and Land Use Planning, RC, Hebbal, Bangalore-560024, India2ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur-440010, India

3ICAR-National Bureau of Soil Survey and Land Use Planning, RC, Kolkata-700091, India*Corresponding author E-mail: [email protected]

Abstract

Soil degradation in Gosaba Block of West Bengal representing Sundarbans ecosystem was assessed based ondetailed soil characterization at 1:10,000 scale. The soils of study area were severely acidic (<4.5) to moderatelyacidic (4.5-5.5) in reaction and associated with slight to severe salinity (>10 dS m-1). Organic carbon contentranged from 0.67 to 1.66% in surface and 0.15 to 3.4% in sub-soils. Nutrient status of soils was deficient inavailable N, P and Zn and sufficient in available K, S, Mn, Cu and Fe. Soil properties (pH, ECe, CEC, clay andESP) highly influenced the availability of plant nutrients. Based on severity, soil degradation was assessedusing parametric approach and results revealed that management units MU-1 (Chan-Sicl-D5-A-S3) and MU-6(Bhu-Sic-D5-B-S1) were under moderately degraded to highly degraded condition. Other management unitswere grouped into weakly to moderately degraded condition. Location specific management practices havebeen suggested to control the existing degradation problems.

Key words: Sundarbans, Soil salinity, Acidity, Soil fertility, Soil degradation, Management practices

Introduction

Coastal region is the priority location for majorhuman settlements in the world (Steffen et al.,2004) and these areas are more vulnerable tocontinuous degradation by human activity(Bajocco et al., 2012). In India, about 20% ofthe population lives in coastal areas alongcoastline of 7517 km and provides significantcontribution to the food grain production(Yadav, 2008). The major threat for productivityof agricultural lands in coastal areas is increasingarea of salt-affected soils. On global basis salt-affected soils occupy an estimated area of 952million ha, nearly 7% of total land area orapproximately 33% of the potential arable landarea of the world (Szabolcs, 1979). In India, outof 9.38 million hectares of salt-affected soil(Dagar, 2005), 3.1 million hectares are found inthe coastal region (Yadav et al., 1983). The coastalwetlands cover an area of 41,401 km2 (Dagar,2005). West Bengal has the largest area (0.82million hectares) under salt-affected soils (Mitranet al., 2014).

Sundarbans delta is situated at the Ganga-Brahmaputra deltaic region of India andBangladesh and is one of the largest mangrovecoastal delta, which falls under unique complex-diverse-risk prone (CDR) agro-ecosystem (Yadavet al., 2009). About 68% of the total cultivablelands in Sundarbans are low lying, mostly mono-cropped with long duration traditional variety ofpaddy in rainy (kharif) season and remain fallowduring the rest of the period of year. Thecrop yield in the area is usually very poor (2.0 -2.5 Mg ha-1) due to biophysical constraints(Bandyopadhyay et al., 2010). The croppingintensity and production levels are much lowercompared to national average. Salt accumulationand dense subsoil layers negatively affect the cropgrowth and it’s the principal reason for thedegradation of farmlands (Ganjegunte et al.,2014). Increasing soil acidity, water logging (inkharif) and drainage congestion are the other majorbiophysical problems in these areas. Theseproblems are also compounded by naturaldisasters like cyclone, sea water intrusion, droughtand flood etc. The situation is expected to be grave



in the scenario of climate change and sea levelrise (Dagar et al., 2016).

The soil salinity shows wide spatial andseasonal variability, being minimum in themonsoon season and maximum in the summerseason (Bandyopadhyay et al., 2003; Bandyo-padhyay et al., 2011). Among the naturalenvironmental features, groundwater level andgroundwater salinity have been considered as thecritical factors for irrigation quality and soilsalinity (Keesstra et al., 2012) in coastal areas. Thepresence of excess salt disperses soil structure,reduces permeability and accelerates the soildegradation process which makes the situation notconducive to plant growth (Kijne, 2005) byreducing the ability of the plant water uptake andion-exchange (Munns, 2005). Moreover, it inducesnutritional imbalance in plants and therebyreduces the yield of many crops. This ranges froma slight crop loss to complete crop failuredepending on the type of crop and severity of thesalinity problem.

Other important limitation for optimal use ofland resources for higher crop production in theSundarbans is increasing soil acidity. The soilacidification due to estuarine sediments of coastalfloodplains (Bandyopadhyay et al., 2010) and lossof productivity due to increasing acidity wasreported by many researchers (Bandyopadhyayand Maji 1995; Bandyopadhyay et al., 2003;Burman et al., 2010). The estuarine sediments ofcoastal floodplains provide ideal conditions forpyrite formation, which reduces the pH below 4.Under these conditions, H+, Al3+, Fe2+ and organicacids accumulate to levels that are toxic to plants(Ponnamperuma et al., 1972) and reduce theavailability of different soil nutrients (Behera andShukla, 2014). The degraded soil and water qualitytogether with climatic adversities led to the poorlivelihood security and low agriculturalproductivity of the Sundarbans coastal areas(Govt. of India, 1981). Detailed characterizationof land resources of Sundarbans and delineatemajor degraded zones help to prepare moreefficient crop production strategies including landshaping and amelioration practice. In this context,the present study was carried out in Gosaba Blockof Sundarbans to assess the level of degradation

and to suggest location specific technologies toovercome the existing problems.


Study area

Gosaba Block is in the North-Eastern part ofSouth 24-Parganas district, West Bengal, India andlies between 21o32′7′′ to 22o17′17′′ N latitudeand 88o42′14′′ to 89o04′30′′ E longitude. For thepresent case study, Western part of Gosaba Block,consisting of 15 villages covering an area of 4173ha was selected (Fig.1). Geologically the areacomes under sub-recent to recent alluvium of theGanga river system. Lands are almost flattopography with elevation ranged from 3-8 mMSL. The climate of the block is sub-tropical withmean maximum and minimum air temperaturesare 34.5oC and 18.3oC, respectively. The averageannual rainfall is 1800 mm. The area belongs toAgro-Eco Sub Region (AESR) 18.5, which is hotsub-humid plain with length of growing period(LGP) of 180-210 days having soil temperatureclass is hyperthermic and aquic soil moisture regime.Major land uses are kharif paddy followed byfallow in winter (rabi) and summer season. Paddy-paddy, paddy-vegetables, and paddy-pulsescropping systems are also observed in somepockets (Table 1).

Soil characterization

Detailed soil survey was carried out on 1: 10,000scales during 2013-2014. The 3-tier soil surveyapproach viz. image interpretation, soil survey andlaboratory investigation and mapping werefollowed to identify the different soil mappingunits (Fig. 2). Remote sensing satellite data (1RS-P6 LISS IV) merged with village cadastral mapwas used as base map. Physiographic units weredelineated by visual interpretation of remotesensing data. Profile study and auger checkingwere done to cover all the soil landforms and majorsoil units. The latitude, longitude and elevation ateach sampling site were recorded using a handheld global positioning system (GPS). Twenty-eight soil profiles and 182 auger samples werestudied to delineate the soil variability viz. acidity,salinity and nutrients availability.

Soil degradations in Sundarbans 259

Table 1. Major soils, land use and yield of the study area

Series Management Units (MU) Land use Yield (kg ha-1)

Chandipur Chan-Sicl-D5-A-S3 Paddy- fallow 1900Chan-Sic-D5-B-S2 Paddy-fallow 2000

Manmathanagar Man-Sicl-D5-B-S0 Paddy (kharif) 2600Black gram (rabi) 625

Man-Sic-D5-B-S0 Paddy (kharif) 2500Chilli (rabi) 3500

Bhupendrapur Bhu-Sil-D5-B-S1 Paddy-fallow 1750Bhu-Sicl-D5-A-S1 Paddy (kharif) 2100

Vegetables (rabi) -

Fig. 1. Location of study area and observation sites

Soil analysis

The soil samples were collected horizon-wise, air-dried, powdered and sieved using 2 mm sieve. ThepH of the soil was determined in 1:2.5 soil: watersolution and electrical conductivity of the soilsaturation paste extract was determined with thehelp of Wheatstone Conductivity Bridge asdescribed by Jackson (1973). Organic carbon in

soil was determined by method described byWalkley and Black (1934). Estimation of availablenitrogen was done by alkaline permanganatemethod (Subbiah and Asija, 1956). Availablephosphorus in soil was determinedcalorimetrically following ascorbic acid reluctantmethod as outlined by Bray and Kurtz (1945).Available potassium of the soil samples was


Fig. 2. Soil map of the study area:Chan- Chandipur series, Man- Manmathanagar series, Bhu- Bhupendrapur series; sic-silty clay,sicl-silty clay loam, sil-silt loam; D5-very deep; A-slope (0-1%), B-slope (1-3%); S3- severe salinity, S2-moderate salinity, S1-slightsaline, S0-very slight saline

extracted with neutral 1N ammonium acetatesolution (Jackson, 1973). Available sulphur (S)was estimated turbidmetrically by barium chlorideprocedure (Chesnin and Yien, 1951). DTPAextractable Fe, Mn, Zn and Cu of the soil sampleswere estimated using atomic absorptionspectrophotometer (AAS) following the methodof Lindsay and Norvell (1978).

Map preparation software and statistics

Soil map of major degradation (drainage, salinityand acidity) and distribution maps were preparedby using of Arc GIS Ver. 10.1. The relationshipamong the estimated soil properties data weresubjected to descriptive analysis. The minimum,maximum, mean and ranges for each soilproperties were computed for data analysis. Themajor soil properties and salinity characteristicson relation with plant available nutrients were

established using Pearson’s correlation coefficientswere determined by the windows based SPSSprogram (ver. 17.0, SPSS Inc).

Assessment of soil degradation

The soil degradation in the study area was assessedby using Snakin et al. (1996) procedure. The soilis degraded when anthropogenic and naturalprocesses occurring in the soil have lowered thequantity and quality of biomass production. Themajor soil chemical degradation in coastalSundarbans are salinization, acidification,accumulation of toxic elements and low soilfertility. The major types of degradation andassociated indicators in Sundarbans coastalecosystem are presented in Table 6. The degreeof degradation is the combined effect of loss ofsoil function as shown by all attributes (indicators)of soil quality (i.e. the absolute decrease of thedegradation indicator value, increasing ratio, etc.).


Based on extent and severity, five stages ofdegradation were proposed.

0 - High quality (non-degraded) soils: soils whoseproductivity corresponds to their natural fertility;the deviation of productivity from the standarddoes not exceed 5%.

1 - Weakly degraded soils: productivity is 5-25%lower than the standard.

2 - Moderately degraded soils: productivity is 25-50% lower than the standard.

3 - Highly degraded soils: productivity is 50-70%lower than the standard.

4 - Very highly degraded soils: productivity is morethan 75% lower than the standard.

The stages of soil degradation are not definedas absolute values of indicators but as relative tosome initial (or designated as the initial) state ofthe soil. Special attention was given to theimportance of the indicator with respect to thequality and quantity of the primary biologicalproduction as well as other ecological functionsof the soil.


Soil characteristics

During survey, three soils series (Chandipur- Fine,mixed, hyperthermic Typic Halaquepts;Manmathanagar- Fine, mixed, hyperthermic TypicEndoaquepts and Bhupendrapur- Fine silty, mixed,hyperthermic Fluventic Endoaquepts) were identifiedin the study area and mapped by six soilmanagement units (MU). The major soil physico-chemical characteristics of identified soils arepresented in Table 2 and Table 4. The soils ofstudy area were highly acidic to neutral in overall,varied from pH 4.3 to 5.4 in surface and 3.2 to 7.7in sub-soils. In Bhupendrapur soil series pH wasless than 3.5 at bottom of the soils (>100cm depth)due to occurrence of acid sulphate materials(Kalyan and Sarkar, 2009). Development of acidsulphate soils in coastal areas is the result of thepoor drainage of soils rich in pyrites (FeS2), whichon oxidation produce sulphuric acid in presenceof excess sulphate ions in soil (Bandyopadhyayand Maji, 1995). Electrical conductivity (ECe)ranged from 1.1 to 10.2 dS m-1 in surface and 1.0-13.3 dSm-1 in sub-soils which shown irregular

Table 2. Physico-chemical characteristics of soils

Depth Horizon pH ECe OC CEC Ex-acidity Na ESP Clay Texture(cm) (1:2.5) (dS m-1) (%) cmol (p+) kg-1 % (USDA)

Chandipur (Fine, mixed, hyperthermic Typic Halaquepts)0-15 Ap 4.9 10.2 0.90 15.8 0.65 2.8 17.7 37.8 sicl

15-42 Bw 6.3 4.4 0.26 14.5 0.25 3.0 20.7 42.9 sic

42-62 Bwg1 5.5 5.0 0.23 15.2 0.20 2.8 18.4 34.1 sicl

62-95 Bwg2 4.6 5.5 0.26 14.9 0.85 2.2 14.8 42.3 sic

95-114 Bwg3 6.3 5.6 0.28 14.0 0.10 2.5 17.9 31.7 sicl

114-130+ Bwg4 7.1 4.7 0.24 14.1 0.00 3.0 21.3 28.9 sicl

Manmathanagar (Fine, mixed, hyperthermic Typic Endoaquepts)0-16 Ap 5.4 1.1 0.67 18.2 0.30 2.5 13.7 34.0 sicl

16-35 Bwg1 7.0 1.1 0.43 18.0 0.00 3.4 18.9 45.6 sic

35-66 Bwg2 7.3 1.0 0.43 17.4 0.10 3.6 20.7 39.0 sicl

66-90 Bwg3 5.7 1.5 0.58 15.0 0.15 1.8 12.0 40.4 sic

90-140+ Bwg4 4.5 1.1 0.43 12.5 1.80 1.4 11.2 24.3 sil

Bhupendrapur (Fine silty, mixed, hyperthermic Fluventic Endoaquepts)0-13 Ap 4.6 2.7 0.87 16.4 0.0 2.2 13.4 35.1 sicl

13-37 Bwg1 6.9 1.2 0.26 16.7 0.75 2.8 16.8 22.8 sil

37-67 Bwg2 5.3 1.5 0.34 18.0 0.20 2.9 16.1 36.8 sicl

67-101 Bwg3 4.0 3.9 0.97 16.3 5.85 2.4 14.7 36.1 sicl

101-132 Bwg4 3.6 8.5 1.33 11.9 5.45 1.6 13.4 21.2 sil

132-150+ Bwg5 3.2 12.5 0.44 13.2 10.4 1.5 11.4 30.3 sicl


distribution with different depths. Chandipur andBhupendrapur soil series have high ECe values(5.6 and 12.5 dS m-1) in lower layers due to gradualupward movement and subsequent evaporation ofsaline groundwater during summer months(Bandyopadhyay et al., 2003). This indicated thatregular tide plays an important role in influencingthe salinity level in such soils.

The soil clay content varied from 22.6 to 48.5%in surface and 10.8 to 48.3% in subsoil layers.Varying soil textures are depending on theirphysiographic locations, climatic conditions andsoil parent materials (Maji et al.,1998). The heavysoil texture, which controls the capillary rise, mayalso one of the factors influencing soil salinity dueto weak response to leaching. The distribution

pattern of cation exchange capacity [15.8-18.2cmol (p+) kg-1], exchangeable acidity [0.1-1.95cmol (p+) kg-1] and exchangeable sodium [2.1-2.8cmol (p+) kg-1] were almost similar with respectto location and soil depth. Organic carbon variedfrom 0.67 to 1.66% in surface and 0.26 to 1.33%in sub-soils. Among the sites, Bhupendrapur seriesrecorded comparatively higher organic carbon(1.33%) than others due to difference in soiltemperature, precipitation, land management,vegetation and biological activity (Bandyopadhyayet al., 1998).

Macronutrient status

The available nitrogen content in all the soils wererated as low to medium and ranged from 90 to502 kg ha-1 (Table 3). The high N availability in

Table 3. Depth wise distributions of nutrients in study area

Management units Depth N P K S Fe Mn Cu Zn(MU) (cm) kg ha-1 mg kg-1

Chan-Sicl-D5-A-S3 0-15 209 1.1 462 269 164 17.8 6.57 1.6915-42 141 1.6 375 83 27 20.3 2.33 0.5442-62 113 1.1 353 173 87 8.33 3.52 0.7762-95 130 0.7 378 228 195 5.21 5.0 0.7295-114 124 4.0 403 140 68 2.17 2.4 0.27

114-130+ 120 1.2 432 140 208 29.0 8.3 2.56

Chan-Sic-D5-B-S2 0-16 400 14.6 428 611 25 2.96 1.35 0.4516-35 293 1.4 467 357 146 33.2 14.5 3.0835-66 282 0.5 447 261 140 17.8 7.82 2.2466-89 231 5.2 450 430 141 26.5 9.77 2.84

89-120+ 383 10.6 572 706 321 28.9 0.63 1.56

Man-Sicl-D5-B-S0 0-16 333 5.9 284 102 165 17.3 4.8 0.6016-35 248 14.1 334 25 34 5.04 4.01 0.3435-66 209 21.1 338 52 336 3.08 5.76 1.0066-90 265 0.6 272 34 196 25.6 7.32 1.43

90-140+ 203 1.1 286 75 142 17.5 5.42 1.15

Man-Sic-D5-B-S0 0-17 412 15.2 281 106 225 17.0 5.82 1.7917-36 321 21.7 296 166 178 10.1 6.04 1.4336-56 345 17.6 344 253 19 8.53 1.66 1.6656-92 416 15.0 333 281 116 14.3 6.31 1.3992-120 339 12.6 321 237 47 15.5 4.93 1.13

120-145+ 345 11.2 318 291 19 18.0 3.53 1.66

Bhu-Sil-D5-B-S1 0-13 185 2.6 322 103 87 9.44 5.94 1.4513-37 156 7.0 271 28 87 9.51 5.79 1.5337-67 135 4.9 259 66 109 8.45 2.65 3.4667-101 152 9.4 270 287 186 26.7 4.04 2.72101-132 230 11.7 178 600 95 25.5 6.29 4.73132-150+ 180 1.2 88 609 289 37.6 2.53 3.96

Bhu-Sicl-D5-A-S1 0-17 502 16.4 384 151 244 18.6 9.09 1.3617-43 180 14.1 394 154 112 17.3 9.30 1.4143-68 186 10.6 347 143 153 11.4 7.19 1.1768-87 152 24.7 302 77 213 8.5 3.12 0.8587-120 107 0.8 373 103 156 7.56 1.58 0.93

120-145+ 90 2.6 431 103 36 32.2 1.44 1.00


surface soils (average of 340 kg ha-1), may be dueto presence of higher level of organic matter. Sametime the available nitrogen content in the in sub-soils was low (217 kg ha-1). The presence of saltsin the sub-surface layers may affects themineralization rate of soil organic nitrogen andthe release of native soil nitrogen to plants(Bandyopadhyay, 1990).

The available phosphorus content in the soilsvaried from 1.1 to 1.4 in surface and 0.5 to 24.7kg ha-1 in sub-soils and was rated as low withaverage of <10 kg ha-1. Highest available P wasobserved in sub-soil of MU-6, MU-3 and MU-4.The availability of P in saline soil may decrease,increase or remain unchanged depending upon thenature and degree of salinity (Yadav, 1980).Generally, phosphate solubility and its availabilityare reduced in acid saline soils not only becauseof ionic strength effects that reduce the activityof phosphate but also the P concentration in soilsolution is tightly controlled by sorption processes,due to formation of Fe/Al-P complexes withhumic acids (Garai et al., 2007).

Average available potassium in the study areawas 360 and 344 kg ha-1 in surface and sub-soils,respectively. Availability of potassium depends onthe parent material, clay minerals and weatheringconditions. Coastal soils of West Bengal are richin both available and non-available form of K andthere may not be any depletion of available Kcontent of soil even after repeated crop cultivationwithout K fertilizers (CSSRI, 1990). The availablesulphur in the soils was more than 200 mg kg-1 inboth conditions, which rated as sufficient in allsoils. The management unit, MU-2 and MU-6 hadhigher amount of available sulphur in sub-surfacesoil than surface. However, the highly acidic withabundance of appreciable amount of sulphate atsurface/ sub-surface soil horizons found in thecoastal acid soils of Sundarbans of West Bengalhas also been reported from Coastal areas ofKerala, West Bengal, Orissa and Andaman andNicobar group of Islands (Bandyopadhyay andMaji, 1995).

Micro nutrient status

The DTPA extractable iron, manganese, zinc andcopper content varied from surface to sub-soilhorizons (Table 4). This was widely scattered and T

able

4.

Ran

ge o

f m

ajor

soi

l pro

pert

ies

in s

tudy

are

a

Site

spH

EC

eC

EC

Exc

h-A

cidi

tyN

aC

lay

OC

Av.

NA

v. P

Av.

KA

v. S

Av.

Fe

Av.

Mn

Av.

Cu

Av.

Zn

1:2.

5dS

m-1

cm

ol (p

+) k

g-1%

k

g ha

-1m

g kg

-1

Surf

ace

rang

e4.

3-5.

41.

1-10

.215

.8-1

8.2

0.1-

1.95

2.1-

2.8

22.6

-48.

50.

67-1

.66

185-

502

1.1-

16.4

281-

462

102-

611

25-2

442.

96-1

8.6

1.35

-9.0

90.

45-1

.79

Mea

n+SE

m(±

)4.

7± 0

.16

5.08

± 1

.44

17.1

± 0

.36

0.82

± 0

.30

2.4±

0.1

136

.1±

3.4

1.08

± 0

.16

340±

50.

49.

3± 2

.836

0± 3

1.1

223±

81.

715

1.6±

33.

813

.8±

2.5

5.5±

1.0

31.

2± 0

.23

Sub-

soils

Ran

ge3.

2-7.

71.

0-13

.311

.9-1

8.4

0.0-

10.4

0.80

-3.6

10.8

-48.

30.

15-3

.490

-416

0.50

-24.

788

-572

25-7

0619

-336

2.17

-37.

60.

63-1

4.5

0.27

-4.7

3M

ean+

SEm

(±)

5.0±

0.2

44.

76±

0.5

915

.5±

0.3

72.

0± 0

.44

2.4±

0.1

333

.9±

1.6

10.

75±

0.1

421

7± 1

7.5

8.1±

1.3

344±

17.

721

7± 3

4.2

137±

16.

316

.9±

1.9

5.1±

0.5

81.

6± 0

.20


hardly sufficient to bring the variability inherentin the soils (Maji and Bandyopadhyay, 1992).Average DTPA extractable available Fe and Mnwere 156.6, 137.7 and 13.8, 16.9 mg kg-1 in surfaceand sub-soils, respectively in the study area. Thehigher concentration of Fe and Mn was recordedin sub-soil than surface horizons. The highconcentration (toxic level) may be due to presenceof mono cropping system (kharif paddy)particularly in water logging condition (SisirKumar, 2013). Under flooding condition, soilorganic matter contributes to Fe and Mnavailability through the formation of metallo-organic complexes with organic substances. Thisphenomenon may be attributed to the productionof chelating agents from compost that generallykeep the micronutrient elements soluble andconsequently more available to plants (Subba Raoet al., 2011). DTPA extractable Zn ranged from0.6 to 1.79 mg kg-1 in surface and 0.27 to 4.73 mgkg-1 in sub-soils (Table 4).

Increased soil pH conditions enhancedsorption of cation Zn occurred on the colloidalsurface of clay particles with concurrent decreasein their mobility rendering the cations in the soilsolution (Das, 2000). All management units werefound to be sufficient of available copper (average> 5.0 mg kg-1), as all the values were well abovethe critical limit (0.2 mg kg-1) proposed by Lindsayand Norvell (1978). The available Cu content wasmore in surface layers and decreased with depth,Cu being highly soluble under low pH conditionsenhanced Cu concentration in soil solution underreduced soil environment (Sah et al., 2009). InSundarbans area, due to poor drainage conditionand heavy texture of soil slightly excess amountof rain or irrigation creates water logging in rainyseason which results in low soil aeration and toxicavailability of Fe, Mn and Cu in soils. This causesconsiderable damage to grow crops andsometimes it may lead to total crop failure(Bandyopadhyay et al., 2011).

Correlation between major soil properties

The correlation matrix with soil salinity propertiesand plant available nutrients are shown in Table5. The observed result detected a higheravailability of N in soil was usually associated withthe higher level of organic C (r= 0.568; p ≤0.01), T

able

5.

Cor

rela

tion

bet

wee

n m

ajor

soi

l pro

pert

ies

Par

amet

ers

pHE

Ce

Na

ESP

CE

CE

x-A

cidi

tyC

lay

OC

Av.

NA

v. P

Av.

KA

v. S

Av.

Fe

Av.

Mn

Av.

Cu

Av.

Zn

pH1

EC

e-0

.517

**1

Na

0.47

4**N

S1

ESP

0.59

4**N

S0.

896**

1C

EC

NS

NS

0.60

8**N

S1

Ex-

Aci

dity

-0.6

92**

0.60

5**-0

.355

*-0

.369

*N

S1

Cla

yN

SN

S0.

435*

0.35

7*N

SN

S1

OC

-0.5

31**

0.60

5**N

SN

S0.

419*

0.35

3*N

S1

Av.

NN

SN

SN

S-0

.451

**0.

383*

NS

NS

0.56

8**1

Av.

PN

SN

SN

SN

SN

SN

SN

SN

S0.

486**

1A

v. K

NS

NS

0.50

5**0.

431*

0.37

0*-0

.349

*N

S0.

494**

NS

NS

1A

v. S

-0.5

78**

0.89

8**N

SN

SN

S0.

690**

-0.3

52*

0.66

5**N

SN

SN

S1

Av.

Fe

NS

NS

NS

NS

NS

NS

NS

NS

NS

NS

NS

NS

1A

v. M

nN

S0.

468**

NS

NS

NS

0.50

6**N

S0.

373*

NS

-0.3

50*

NS

0.41

8*N

S1

Av.

Cu

NS

NS

NS

NS

NS

NS

NS

NS

NS

NS

NS

NS

NS

NS

1A

v. Z

n-0

.376

*0.

405*

NS

NS

NS

0.62

8**N

SN

SN

SN

S-0

.346

*0.

481**

NS

0.60

2**N

S1

** in

dica

tes

sign

ific

ant a

t 1%

leve

l and

* in

dica

tes

sign

ific

ant a

t 5%

leve

l (2-

taile

d).


CEC (r= 0.383; p ≤0.05) and negative correlationwith ESP (r= -0.451; p ≤0.01). The availablephosphorus contents of the soils had positivecorrelation with N (r= 0.486; p ≤0.01) due tophosphate ions were adsorbed on organic colloidsthrough metal bridging or co-adsorption (Tan,1998).

Soils were high in available potassium contentand positively correlated with OC and Na contentat level of p≤0.01, whereas, CEC, ESP andexchangeable acidity had significant at p ≤0.05level. The available sulphur content was sufficientin all the sites, positively correlated with soil OC,exchangeable acidity, ECe and negativelycorrelated with pH and clay content. Available Feand Cu content of the soils in different sites werenot significant with other properties and rated assufficient. The available Mn content of the soilshad positive correlation with ECe (r= 0.468; p≤0.01), exchangeable acidity (r= 0.506; p ≤0.01),OC, available S and negative correlation withavailable P (r= -0.350; p ≤0.05). The available Zncontent of soil under different sites was similarand positive correlation with exchangeable acidity

(r= 0.628; p ≤0.01), available Mn (r= 0.602; p≤0.01), available S (r= 0.481; p ≤0.01), ECe (r=0.405; p ≤0.05) and negative correlation with pH(r = -0.376; p ≤0.05) and available K (r= -0.346; p≤0.05).

Assessment of soil degradation

The coastal Sundarbans are facing different typesof soil degradation, due to accumulation of salts,drainage congestion, drought, soil acidity,nutrients deficient and toxicity. Based on severityand intensity of different elements, soildegradation was assessed (Table 6 and 7). Theresults indicated that MU-1 and MU-6 are undermoderate (productivity was 25-50% lower than thestandard) to high degradation (productivity was50-75% lower than the standard). Rest of the soilsare grouped into weak (productivity was 5-25%lower than the standard) to moderate degradation(productivity was 25-50% lower than thestandard). Maps of degraded soils at 10,000 scales(drainage, acidity and salinity) is being shown inFig. 3, which have more spatially depictedquantitative and qualitative changes in soil quality.

Table 6. Major indicators and criteria of evaluating degradation of soils

Indicator The degree of degradation0 1 2 3 4

Thickness of organo-genic layer : reduction in terms of the total <0.1 0.1-0.2 0.3-0.5 0.6-1.0 >1.0profile thicknessContent of main nutrient elements (multiple decrease) < 1.2 1.2-1.5 1.6-2.0 2.1-5 >5Content of readily soluble salts resulting from secondary < 0.10 0.11-0.20 0.21-0.40 0.41-0.80 > 0.81salinization (increase by %)Content of exchangeable sodium resulting from secondary < 5 5-10 11-25 26-50 > 50solonetzization (increase by % of CEC)Soil redox potential (decrease, mV) < 50 50-100 101-200 201-400 > 400

Table 7. Assessment of soil degradation by using rank method in different soils

Indicators Management units (MU)1 2 3 4 5 6

Thickness of organo-genic layer : reduction in terms of the total profile thickness 1 0 0 2 0 2Content of main nutrient elements (multiple decrease) 3 2 2 3 2 3Content of readily soluble salts resulting from secondary salinization (increase by %) 3 3 2 1 2 1Content of exchangeable sodium resulting from secondary solonetzization (increase 3 3 2 2 2 2by % of CEC)Soil redox potential (decrease, mV) 3 1 2 1 2 3Average 2.6 1.8 1.6 1.8 1.6 2.2Rank 2-3 1-2 1-2 1-2 1-2 2-3

266 Srinivasan et al.T

able

8.

Sugg

este

d la

nd u

se p

lann

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and

man

agem

ent

prac

tice

s fo

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of li

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(kha

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the

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to r

educ

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ean

d hi

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ents

vola

tiliz

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n pr

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s.to

xici

ty a

nd lo

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and

spri

nkle

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ave

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wat

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ater

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ddit

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of li

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ectly

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Suggested land use planning

Coastal Sundarbans needs location specifictechnology, suitable cropping system andmanagement practices according to the soil andsite characteristics (Table 8) to reduce soildegradation and improving the agriculturalproduction. Major soil and water managementpractices recommended are subsurface drainage,reclamation, use of salt tolerant crops and landshaping technology (farm pond, deep furrow andhigh ridge and shallow furrow and medium ridges)besides using high yielding rice varieties replacingthe low yielding indigenous ones in rainy seasonand growing high value horticultural crops induring winter season.

Conclusions

The present study found that soils of Gosaba blockwere severe acidic to moderately acidic (4.5-5.5)and associated with slight (1.0 dS m-1) to severesalinity (12.5 dS m-1). Available nitrogen andphosphorous content were low, whereas, sulphurand micronutrients (Fe, Mn, and Cu) were at toxicthe level. Out of 6 management units identified,2 management units (Chan-Sicl-D5-A-S3 andBhu-Sic-D5-B-S1) are under moderately to highlydegraded condition. Location specificmanagement practices have been suggested toovercome the existing problems and improving thequality and productivity of soil resources.

Acknowledgements

We extend our thanks to the Department ofAgriculture, Govt. of West Bengal for providingthe financial support under RKVY and Mr. G.C.Sarkar, Senior Technician for helping in the soilsurvey/field work. We also acknowledge ourcolleagues Dr. S.K. Reza and Dr. S.Dharumarajan, Scientist for extending help instatistical analysis and manuscript preparation.

References

Bajocco S, De Angelis A, Perini L, Ferrara A and Salvati L(2012) The impact of land use/land cover changes onland degradation dynamics: a Mediterranean case study.Environmental Management 49: 980–989.

Bandyopadhyay BK, Burman D and Mandal S (2011)Improving agricultural productivity in degraded coastalland of India- experiences gained and lessons learned.Journal of the Indian Society of Coastal Agricultural Research29: 1-9.

Bandyopadhyay BK, Subhasis Mandal, BurmanD andSarangi SK (2010) Soil and water management optionsfor enhacing agricultural productivity of coastal area ofWest Bengal. Journal of the Indian Society of CoastalAgricultural Research 28: 1-7.

Bandyopadhyay BK, Maji B, Sen HS and Tyagi NK (2003)Coastal Soils of West Bengal- Their Nature, Distribution andCharacteristics. Bull. No. 1/2003. Central Soil SalinityResearch Institute, Regional Research Station, CanningTown, West Bengal, India, pp1-62.

Bandyopadhyay BK, Sahu GC and Maji B (1998) Status,nature and composition of organic matter in coastal

Fig. 3. Distribution of major soil degradation a) soil drainage b) soil acidity c) soil salinity in study area


areas. Journal of the Indian Society of Soil Science 19: 58-67.

Bandyopadhyay BK and Maji B (1995) Nature of acid soilof Sundarbans delta and suitability of classifying themas acid sulphate or potential acid sulphate soils. Journalof the Indian Society of Coastal Agricultural Research 13:103-107.

Bandyopadhyay BK (1990) Fertility of salt affected soils inIndia – An overview. Journal of the Indian Society ofCoastal Agricultural Research 8: 61-78.

Behera SK and Shukla AK (2014). Spatial distribution ofsurface soil acidity, electrical conductivity, soil organiccarbon content and exchangeable potassium, calciumand magnesium in some cropped acid soils of India.Land Degradation & Development 25: 228–235.

Bray RH and Kurtz LT (1945) Determination of total,organic and available forms of Phosphorous in soils. SoilScience 59: 39-45.

Burman D, Bandyopadhyay BK and Mahanta KK (2010)Management of acid sulphate soil of coastal Sunderbansregion: Observations under on-farm trial. Journal of theIndian Society of Coastal Agricultural Research 28: 8-11.


CSSRI (1990) Annual Report, Central Soil Salinity ResearchInstitute, Karnal, Haryana, India, p265.

Dagar JC (2005) Salinity research in India: An overview. Bull.National Institute of Ecology 15: 69-80.

Dagar JC, Sharma PC, Chaudhari SK, Jat HS and AhamadS (2016) Climate change vis-à-vis saline agriculture:Impact and adaptation strategies. In: Dagar JC, SharmaPC, Sharma DK and Singh AK (eds) Innovative SalineAgriculture, Springer, Dordrecht, pp 5-53.

Das DK (2000) Micronutrients: Their Behavior in Soils andPlants. Kalyani Publishers, New Delhi.

Ganjegunte GK, Sheng Z and Clark JA (2014) Soil salinityand sodicity appraisal by electromagnetic induction insoils irrigated to grow cotton. Land Degradation &Development 25: 228–235.

Garai TK, Roy SC, Ghosh SK, Pal SK and Mukopadhyay(2007) form of phosphorus in some soils of coastalecosystem of West Bengal. Journal of the Indian Societyof Coastal Agricultural Research 25: 102-105.

Government of India (1981) Report on development ofcoastal areas affected by soil salinity. PlanningCommission. New Delhi. pp 1-138.

Jackson ML (1973). Soil Chemical Analysis. Prentice -Hall ofIndia Pvt. Ltd. New Delhi, pp. 40.

Kalyan S and Sarkar D (2009) Studies on Chemical propertiesand nature of acidity of coastal acid soils of West Bengal.Journal of Interacademicia 13: 23-27.

Keesstra SD, Geissen V, Mosse K, Piiranen S, Scudiero E,Leistra M and Van Schaik L (2012) Soil as a filter forgroundwater quality. Current Opinion in EnvironmentalSustainability 4: 507- 516.

Kijne JW (2005) Abiotic and water scarcity: Identifying andresolving conflicts from plant level to global level. FieldCrops Research 97:3-18.

Lindsay WL and Norvell WA (1978) Development of aDTPA soil test for zinc, iron, manganese and copper.Soil Science Society of America Journal 42: 474-481.

Maji B, Bandyopadhyay BK, Sarkar D and Chatterji S (1998)Morphological and chemical characterization of soilsof Sagar Island of the Sundarbans, West Bengal. Journalof the Indian Society of Soil Science 46: 99-103.

Maji B and Bandyopadhyay BK (1992) Effect of submergenceon Fe, Mn and Cu contents in some coastal rice soils ofWest Bengal. Journal of the Indian Society of Soil Science40:390-392.

Mitran T, Mani PK, Basak N, Mandal B and MukhopadhyaySK (2014) Soil fertility constraint assessment usingspatial nutrient map at three selected villages of coastalSundarbans. Journal of Soil Salinity and Water Quality 6:1-8.

Munns R (2005) Genes and salt tolerance: bringing themtogether. New Phytologist 167: 645-663.

Ponnamperuma FN, Attanandana and Tand Beye G (1972)amelioration of three acid sulfate soils for lowland rice.in acid sulfate soils. In: Dost H (ed) ProceedingsInternational Symposium. ILRI 18 (2). Wageningen, TheNetherlands. pp 391-401.

Sah KD, Sarkar D, Seal A and Sahoo AK (2009) Soilcharacteristics and available micro-nutrients status insome acid saline soils of coastal agro-ecosystem in WestBengal. Indian Agriculture 53: 69-74.

Sisir Kumar Si (2013) Status of available Micronutrients inSunderbans, a deltaic locality of West Bengal. Journalof the Indian Society of Coastal Agricultural Research 31:80-83.

Snakin VV, Krechetov PP, Kuzovnikova TA, Alyabina IO,Gurov AF and Stepichev AV (1996) The system ofassessment of soil degradation. Soil Technology 8:331-343.

Steffen W, Sanderson A, Tyson PD, Jäger J, Matson PA,Moore B, Oldfield F, Richardson K, Schellnhuber HJ,Turner BL and Wasson RJ (2004) Global Change and theEarth System: A Planet Under Pressure, The IGBP BookSeries. Springer: Berlin.

Subba Rao A, Biswas AK and Maji B (2011) Improved soilmanagement practices for enhancing crop productionand reducing soil degradation in coastal regions in India.Journal of the Indian Society of Coastal Agricultural Research29: 10-18.


Subbaiah BV and Asija GL (1956) A rapid procedure forEstimation of Available Nitrogen in soils. Current Science25: 259-260.

Szabolcs I (1979) Review of research in salt-affected soils.Natural Resource Research 15: UNESCO, Paris. p137.

Tan KH (1998) Principles of Soil Chemistry, 3rd edn. MarcelDekker Inc., New York.

Walkley AJ and Black IA(1934) An examination of theDegtjareff method for determining soil organic matterand a proposed modification of the chromic acidtitration method. Soil Science 37: 29–38.

Yadav JSP (1980) Efficiency of fertilizers used in saline andalkali soils for crop production. Fertilizer News 25: 19-27.

Yadav JSP (2008) Sustainable management of coastalecosystem for livelihood security: a global perspective.Journal of the Indian Society of Coastal Agricultural Research26: 5-11.

Yadav JSP, Bandyopadhyay AK and Bandyopadhyay BK(1983) Extent of coastal saline soils of India. Journalof the Indian Society of Coastal Agricultural Research 1: 1-6.

Yadav JSP, Sen HS and Bandyopadhyay BK (2009) Coastalsoils-management for higher agricultural productivityand livelihood security with special reference to India.Journal of Soil Salinity and Water Quality 1: 1-13.


Quality of Irrigation Groundwater from Palghar andDahanu Tehsils of Coastal Konkan

MV Apraj, KD Patil*, MR Wahane and NH Khobragade

Department of Soil Science and Agricultural ChemistryDr. Balasaheb Sawant Konkan Krishi Vidyapeeth, Dapoli-415712, Maharashtra, India


Abstract

The quality of groundwater for irrigation was studied from different locations of Palghar and Dahanu Tehsilsof Coastal Konkan in Maharashtra in the month of May 2016 (pre-monsoon) and October 2016 (post-monsoon).The results obtained from investigation revealed that all irrigation water samples from Palghar and Dahanutehsil were slightly saline in reaction. Among all the cations, Na+ was dominant in water followed by Ca++,Mg++ and K+. The relative proportion of anions were Cl- > HCO3

- > SO4-2 > CO3

-2. There were no carbonatecontents in majority of water samples. According to SAR, 61% water samples were categorized as class C1

which is suitable for irrigation and 39% water samples were moderately suitable and categorized as C2 in May,while in October 67% and 33% water samples were categorized as suitable (C1) and moderately suitable (C2)class for irrigation, respectively. The pH, EC, Cations, Anions, Boron, SAR and RSC values of irrigation watercollected in pre-monsoon season (May 2016) were high as compared to post monsoon season (October 2016),due to rain water dilution effect.

Key words: GPS, Irrigation water, Salinity, Cations, Anions, SAR, RSC

Introduction

Poor-quality water if used for a long time canmake the soil less productive depending on theamount and type of constituents present in it andthe texture of the soil. Excess of soluble salts inwater leads to their accumulation in the surfacelayer particularly in fine textured or poorly drainedsoils. Chemistry of ground waters is dictated bysupply of various elements from both natural andanthropogenic sources (Bishnoi et al., 1984).Rainfall plays an active role for changing thewater-quality of underground aquifers (Kaushiket al., 2002). The poor-quality of irrigation waterwill have deteriorating effect on soil properties andcrop growth if used indiscriminately. The saltspresent in the poor-quality water affect the cropgrowth, yield and quality of produce by increasingthe osmotic potential thereby reducing wateravailability and uptake of nutrients. Hence, theassessment of quality parameters of well and tubewell water is necessary for judicious use ofirrigation and to obtain a sustainable crop yield(Tiwari et al., 2007; Vihwanath et al., 2008; Palkar

et al., 2008). Therefore, the present assessment hasbeen made in two Tehsils of coastal Konkan.

Material and Methods

The water samples were collected during pre- andpost-monsoon at same site as per GPS location.Total 200 numbers of water samples werecollected using from different locations by randomsampling method from bore wells and wells duringpost-monsoon (October-2016) and pre-monsoon(May-2016). This paper envisages to illustrate thespatial variability of various parameter ofirrigation water quality i.e. pH, electricalconductivity (EC), residual sodium carbonate(RSC) and sodium adsorption ration (SAR). Thesamples were analysed following standardprocedures of irrigation water quality analysis.

The pH and EC of the water samples wasdetermined by using glass electrode pH meter(Jackson, 1973). The Na+ and K+ contents in watersamples were determined by using flamephotometer (Jackson, 1973) and Ca++ and Mg++

were estimated by versanate titration method


Quality of irrigation groundwater from Palghar and Dahanu 271

(Richards, 1954). The Residual Sodium Carbonate(RSC) was calculated by the formula given byEaton (1950) as RSC (me L-1) = (CO3— +HCO3

-)- (Ca++ + Mg++); and the Sodium AdsorptionRation (SAR) computed by following formulagiven by Richards (1954):


Chemical parameters of ground water

pH

The pH of irrigation water samples from PalgharTehsil varied from 7.14 to 8.38 with an averagevalue of 7.63 in May and 7.04 to 8.03 with anaverage value of 7.46 in October, respectively.While pH in samples from Dahanu tahsil rangedfrom 6.81 to 8.43 with an average value of 7.48 inMay and 7.02 to 8.47 in October with an averagevalue of 7.51, respectively. Majority of watersamples collected from selected 23 villages ofPalghar and Dahanu tehsils were found slightlyalkaline in reaction which increased slightly in themonth of May as compared to October (Table 1).Patil et al. (2014) recorded the similar results fromAhmedpur tehsil of Latur district of Maharashtrathat showed high pH values in May (pre-monsoon)as compared to October (post-monsoon).

Electrical conductivity (EC)

Electrical conductivity of irrigation waterscollected in May and October from Palghar tahsilranged from 0.31 to 1.28 and 0.27 to 0.97 dS m-1

with an average value of 0.68 and 0.56 dS m-1,respectively and found to be non-saline (EC <2.0dS m-1). Likewise, EC of samples collected from

Dahanu tehsil varied from 0.44 to 1.45 and 0.32to 0.93 dS m-1 with an average value of 0.79 and0.69 dS m-1 in May and October, respectively. TheEC values of water samples were found low inthe month of October as compared to the monthof May (Table 1).

Sodium, potassium, calcium and magnesium

The sodium concentration of irrigation watersamples from Palghar tehsil varied from 4.98 to109.26 with a mean value of 31.92 me L-1 in May,while in October it was ranged from 3.52 to 105.4me L-1 with a mean value of 28.52 me L-1. InDahanu tehsil sodium concentration were rangedfrom 6.14 to 104.70 me L-1 with a mean value of29.12 me L-1 in May, while in October it rangedfrom 5.54 to 102.5 me L-1 with a mean value of24.98 me L-1, respectively.

The variation of potassium concentration inirrigation water samples varied from 5.30 to 29.70me L-1 with a mean value of 12.17 me L-1 in Maywhile 00.70 to 25.40 me L-1 with a mean value of8.07 me L-1 in October from Palghar tehsil. InDahanu tahsil potassium concentration rangedfrom 00.90 to 31.20 me L-1 with a mean value of9.50 me L-1 in May, while in October it rangedfrom 00.40 to 28.30 me L-1 with a mean value of8.27 me L-1, respectively (Table 2).

The seasonal variation of calciumconcentration in water samples taken fromPalghar tehsil varied from 3.10 to 42.40 me L-1

and 2.0 to 41.50 me L-1 with a mean value of 11.23and 9.56 me L-1 during May and October,respectively while in Dahanu tahsil it varied from2.00 to 46.80 me L-1 and 2.0 to 45.20 me L-1 witha mean value of 10.53 and 9.21 me L-1 during Mayand October, respectively. The variation of

Table 1. Concentration of pH and EC of water samples from Palghar and Dahanu tehsils

Name of the Pre-monsoon (May 2016) Post-monsoon (Oct.2016)

tehsil pH EC (dS m-1) pH EC (dS m-1)

Palghar Max. 8.38 1.28 8.03 0.97Min. 7.14 0.31 7.04 0.27Mean 7.63 0.68 7.46 0.56

Dahanu Max. 8.43 1.45 8.47 0.93Min. 6.81 0.44 7.02 0.32Mean 7.48 0.79 7.51 0.69

272 Apraj et al.

magnesium concentration in different seasonsvaried from 2.0 to 33.20 and 1.60 to 31.10 me L-1

with a mean value of 7.87 and 7.03 me L-1 in Mayand October, respectively from Palghar tehsil;while in Dahanu tehsil it varied from 00.80 to30.00 and 00.40 to 27.12 me L-1 with a mean valueof 5.70 and 5.39 me L-1 in May and October,respectively (Table 2).

Carbonate, bicarbonate, chloride and sulphate

The carbonate concentration of water varied from0.0 to 6.0 and 0.0 to 3.0 me L-1 with a mean valueof 1.02 and 1.83 me L-1 in May and October,respectively from Palghar tehsil while in Dahanutehsil it was varied from 0.0 to 6.0 and 0.0 to 3.0me L-1 with a mean value of 2.50 and 1.75 me L-

1 in May and October, respectively (Table 3).

The bicarbonate concentration of watersamples in different seasons varied from 4.0 to 26.0and 2.0 to 22.0 me L-1 with a mean value of 12.44and 11.24 me L-1 during May and October,respectively from Palghar tehsil and ranged from3.0 to 26.0 and 2.0 to 23.0 me L-1 with mean valueof 12.72 and 10.72 me L-1 in May and October,respectively in Dahanu tehsil.

The seasonal variation of chlorideconcentration ranged from 3.0 to 50.0 and 3.0 to27.0 me L-1 with a mean value of 14.80 and 11.90me L-1 in May and October, respectively fromPalghar tahsil and ranged from 2.0 to 53.0 and1.0 to 46.0 me L-1 with a mean value of 15.38 and13.86 meL-1 during May and October, respectivelyin Dahanu tehsil.

The sulphate concentration of water samplesin different seasons varied from 0.02 to 2.80 and0.09 to 1.20 meL-1 with a mean value of 0.47 and0.45 meL-1 during May and October, respectivelyfrom Palghar tahsil and ranged from 0.12 to 2.10and 0.03 to 2.05 me L-1 with a mean value of 0.56and 0.36 meL-1 in May and October, respectivelyfrom Dahanu tehsil (Table 3).

Boron

The boron concentration of water varied from0.28 to 1.09 and 0.24 to 0.98 me L-1 with a meanvalue of 0.50 and 0.46 me L-1 in May and October,respectively from Palghar tahsil while in Dahanutehsil it varied from 0.22 to 0.48 and 0.19 to 0.43me L-1 with a mean value of 0.35 and 0.32 meL-1

in May and October, respectively (Table 4).

Table 2. Concentration of soluble cations (me L-1) in irrigation water samples from Palghar and Dahanu tehsil

Name of the Pre-monsoon (May 2016) Post-monsoon (Oct.2016)

tehsil Na+ K+ Ca++ Mg++ Na+ K+ Ca++ Mg++

me L-1

Palghar Max. 109.26 29.70 42.40 33.20 105.4 25.40 41.50 31.10Min. 04.98 05.30 03.10 02.00 03.52 00.70 02.00 01.60Mean 31.92 12.17 11.23 07.87 28.52 08.07 09.56 07.03

Dahanu Max. 104.70 31.20 46.80 30.00 102.5 28.30 45.20 27.12Min. 06.14 00.90 02.00 00.80 05.54 00.40 02.00 00.40Mean 29.12 09.50 10.53 05.70 24.98 08.27 09.21 05.39

Table 3. Concentration of soluble anions (me L-1) in irrigation water samples from Palghar and Dahanu tehsil

Name of the Parameter Pre-monsoon (May 2016) Post-monsoon (Oct.2016)

tehsil Cl- SO42- CO3

2- HCO3- Cl- SO4

2- CO32- HCO3

-

me L-1

Palghar Max. 6.0 26.0 50.0 2.80 3.0 22.0 37.0 1.20Min. 1.0 04.0 03.0 0.02 0.0 02.0 03.0 0.09Mean 1.02 12.44 14.8 0.47 1.83 11.24 11.9 0.45

Dahanu Max. 06 26 53 2.10 03 23 46 2.05Min. 00 03 02 0.12 00 02 01 0.03Mean 2.5 12.72 15.38 0.56 1.75 10.72 13.86 0.36

Quality of irrigation groundwater from Palghar and Dahanu 273

Sodium adsorption ratio (SAR)

The seasonal variation in SAR varied from 2.63to 20.49 and 1.39 to 19.02 with a mean value of10.53 and 10.30 during May and October,respectively from Palghar tehsil. In Dahanu tehsilthe same ranged from 3.11 to 17.22 and 3.55 to17.08 with a mean value of 10.17 and 9.19 in Mayand October, respectively (Table 4).

Residual sodium carbonate (RSC)

RSC value in water samples ranged from 0 to 3.80and 0 to 4.70 with a mean value of 0.74 and 0.79in May and October respectively, from Palghartehsil and ranged from 0 to 4.80 and 0 to 3.80with a mean value of 1.96 and 1.62 during Mayand October, respectively in samples from Dahanutehsil (Table 4).

According to Ayers and Westcot (1976) thewater samples were classified for their irrigationquality as C1, C2 and C3, respectively. Out of 200water samples, 39 (78%) fell in C3 class which werein permissible category for irrigation in May while33 (66%) samples were in permissible category inOctober; while 61 and 67 water samples were ofgood-quality (C2 class) in May and October,respectively. Further, data revealed that 61 per centwater samples were safe for irrigation but theseneed moderate leaching and 39 per cent were fairlysuitable and cannot be used in soils with restricteddrainage in May. While, in October, 67 per centwater samples were safe for irrigation but needmoderate leaching and 33 per cent were fairlysuitable and cannot be used with restricteddrainage.

Conclusion

The data indicated that among the all cations Na+

was dominant and in anions Cl- was dominant.

Majority of carbonate was absent in irrigationwater therefore the quality of water is good. Onthe basis of SAR, 50 per cent water samples ofPalghar district were found safe for irrigation,47percent samples were moderately safe forirrigation while remaining 3.0 per cent watersamples were marginally unsafe for irrigationpurpose in May while in October 54 per cent watersamples of Palghar district were found safe forirrigation, 43 percent samples were moderatelysafe for irrigation while remaining 3.0 per centwater samples were marginally unsafe forirrigation purpose. According to RSC,77 irrigationwater samples were having RSC < 1.25 me L-1

which was suitable for irrigation,10 water samplesmarginally suitable while 13 water samples wasunsuitable for irrigation in May. In October, 79water samples (78%) were found suitable forirrigation, 10 were marginally suitable (10%) while11 were found unsuitable for irrigation (11%).

References

Ayers RS and Westcot DW (1976) Water quality ofagriculture irrigation and drainage. Paper, 29. Food andAgriculture Organisation (FAO), Rome.

Bishnoi SR, Brar SP and Kumar D (1984) Undergroundwater quality of Dhuri Block, Dist. Sangrur (Punjab).Indian Journal of Ecology 11(2): 220-228.

Kaushik A, Kumar K, Sharma IS and Sharma HR (2002)Groundwater quality assessment in different land useareas of Rohtak and Faridabad cities of Haryana usingdeviation index. Journal of Environmental Biology 25:173-180.

Jackson ML (1973) Soil Chemical Analysis. Prentice Hall ofIndia, New Delhi.

Palkar JJ, Patil KD, Khobragade SS, Vanave PB and MJKaledhonkar MJ (2008) Quality of irrigation water incoastal districts of Konkan region of Maharashtra. J SoilSalinity & Water Quality 8 (2): 221-223.

Table 4. Concentration of soluble anions (me L-1) in irrigation water samples from Palghar and Dahanu tehsils.

Name of the Pre-monsoon (May 2016) Post-monsoon (October 2016)

tehsil Boron SAR RSC Boron SAR RSC me L-1

Palghar Max. 1.09 20.49 3.80 0.98 19.02 4.70Min. 0.28 02.63 0.00 0.24 1.39 0.00Mean 0.50 10.53 0.74 0.46 10.30 0.79

Dahanu Max. 0.48 17.22 4.80 0.43 17.08 3.80Min. 0.22 3.11 0.00 0.19 3.55 0.00Mean 0.35 10.17 1.96 0.32 9.19 1.62

274 Apraj et al.

Patil SS, Khandare RN and Gajare AS (2014) Assessmentof quality of ground water for irrigation in Ahmedpurtahsil of Latur district, Maharashtra. An Asian Journalof Soil Science 1(9): 73-77.

Richards LA (1954) Diagnosis and Improvement of Saline SodicSoils. USDA Handbook No. 60, Washington, pp 69-82

Tiwari SC, Bangar KS, Khandkar UR, Verma SK and DubeyRachna (2007) Survey, characterization and mapping

of ground water quality of Gwalior District of MadhyaPradesh. Journal of Soil Salinity and Water Quality 7 (2):152-156

Vishwanath J, Ravikumar D, Karegoudar AV, Anand SR andRajkumar RH (2008) Characterization of ground waterfor irrigation in Dharwad District of Karnataka. Journalof Soil Salinity and Water Quality 8(2): 202-206

Received in July 2017; Accepted in September, 2017

Guidelines for Authors Submitting Manuscript for Publicationin the “Journal of Soil Salinity and Water Quality”

The authors are advised to follow the guidelines given in the latest issue of the Journal for preparation ofmanuscript. They are required to submit one electronic copy in the form of CD or email ([email protected];[email protected]) and one hard copy completed in all respects to General Secretary, Journal of Soil Salinityand Water Quality, Central Soil Salinity Research Institute, Kachhwa Road, Karnal-132001, Haryana, India.The receipt of manuscript as well as subsequent correspondences regarding the manuscript will be doneelectronically only.

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It should be a separate page and comprise of following:

Short Title : It should have a short title (not exceeding seven words in ordinary type; 12 font) on the top ofright hand corner.

Title : It should not exceed 15 words and should reflect the contents of the paper. It should be bold intitle case like “Alleviation of Sodicity Stress on Rice Genotypes by Phosphorous Fertilization”.

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Address : Each author’s name should have number as superscript to indicate the address. The correspondingauthor’s name should have number as superscript to indicate more than one address. Thecorresponding author’s name should have asterisk (*) mark as superscript e.g. AK Aggarwal*1

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*1 Central Soil Salinity Research Institute, Zarifa Farm, Kachhwa Road, Karnal-132001, Haryana, India2Indian Institute of Soil Science, Nabibagh,, Berasia Road, Bhopal-462038, Madhya Pradesh, India.

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Each table and figure should have 12 fonts and be given on separate page after References part. Table 1 andFigure 1 should be written as Table 1. (bold) and Fig. 1 (bold), respectively. Table caption should appear on thetop of table whereas figure caption should be just below the figure. Figure caption and matter should be legiblewith 8-12 fonts size. The abbreviations used in Table or Figure must be explained as foot-note. Maximum size oftables and figures should be such that these can be conveniently accommodated in A4 size page. Approximateposition of the tables and figures should be indicated in the text of the manuscript.

References

References should be in alphabetic and chronological order and should not be serial numbered. The author(s)names should start with surname comma after initials. If first author has two publications in a year, singleauthor paper should appear first. Year should be bracketed. The journal names should be in full withoutabbreviation and should be italicized. Volume No. should be in bold. Few examples are given below:

Journal: Dagar JC, Tomar OS, Minhas PS and Kumar M (2013) Lemon grass productivity as affected bysalinity of irrigation water, planting methods and fertilizer doses on a calcareous soil in a semi-aridregion of northwest India. Indian Journal of Agricultural Sciences 83(7): 734-738.

Book: Singh NT (2005) Irrigation and Soil Salinity in the Indian Subcontinent- Past and Present. Lehigh UniversityPress, Bethlehem, USA, p 404

Book Chapter: Tyagi NK (1998) Management of salt-affected soils. In: Singh GB and Sharma BR (eds) 50 Yearsof Natural Resource Management Research. Indian Council of Agricultural Research, New Delhi, India,pp 363-401.

Online Reference: Rhoades JD, Kandiah A and Mashali AM (1992) The use of saline waters for crop production-FAO irrigation and drainage paper 48. Food and Agriculture Organization, Rome. (http://www.fao.org/docrep/t0667e00.HTM.)

Conference/Symposium Proceedings: Suarez DL and Lebron I (1993) Water quality criteria for irrigationwith highly saline water. In: Lieth H and Al Masoom AA (eds) Towards the Rational Use of High SalinityTolerant Plants, Vol 2-Agriculture and Forestry under Marginal Soil Water Conditions. Proceedings of thefirst ASWAS Conference (December 8-15, 1990), United Arab Emirates University Al Ain, UAE.Kluwer Academic Publishers, Dordrecht, the Netherlands, pp 389-397.

M.Sc/ Ph.D. Thesis: Ammer MHM (2004) Molecular Mapping of Salt Tolerance in Rice. Ph.D. Thesis, IndianAgricultural Research Institute, New Delhi, India.

Bulletin: Abrol IP, Dargan KS and Bhumbla DR (1973) Reclaiming Alkali Soils. Bulletin No. 2. Central SoilSalinity Research Institute, Karnal, 58p.

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While writing Short Communication one should focus on studies of limited scope, preliminary data, uniqueobservations or research technique and apparatus. The length of short communication should not exceed 3published pages. Short communication should comprise of short title, title, name (s) of author (s) with affiliationsand text dealing with material and methods, results and discussion and references but there should not be anymain head except of references. It should not have abstract and keywords.

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The terms like Nitrogen, Phosphorous, Potassium and Zinc may be denoted as N, P, K and Zn, respectively anddose expressed as kg ha-1 for field experiments. For pot studies, units like mg kg-1 or kg m-2 should be followed.We must avoid to use units such as q (quantal), lakh and crore.

Common Units and Symbols

time=t, metre=m, second=s, centimeter=cm, cubic centimeter=cm3, cubic metre=m3, degree celsius=°C, day=d,gram=g, hectare= ha (104m2), hour=h, kilometer=km, kilogram=kg, litre=l, megagram=Mg (tons to be given inMg), microgram=µg, micron=µm, milimole=mmol, milliequivalent=meq, micromol=µmol, milligram=mg,milliliter=ml, minute=min, nanometer=nm, square centimeter=cm2, square kilometer=km2,electricalconductivity= (EC)=dS m-1 (deci Siemens m-1), gas diffusion=g m2 s-1, water flow=m3 m2s-1, ion uptake= molkg-1 of dried plant material, leaf area=m2kg-1, nutrient content in plants= mg g-1 (dry matter basis), root densityor root length density= m m-3, soil bulk density= g cm-3, transpiration rate=mg m2 s-1, water content of soil=kgkg-1, water tension=kPa, yield (grain or forage)= Mg ha-1 or kg ha-1 , organic carbon content of soil= percent (%),cation exchange capacity of soil= cmol (p+) kg-1

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