Legume Research

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Legume Research, volume 41 issue 5 (october 2018) : 716-721

Water productivity and yield analysis of groundnut using CropSyst simulation model in hyper arid partially irrigated zone of Rajasthan#

Sita Ram Jat, I. J. Gulati, M.L. Soni, Amit Kumawat, N.D. Yadava, Vinay Nangia, M. Glazirina, Birbal, V.S. Rathore
1College of Agriculture, Swami Keshwanand Rajasthan Agricultural University, Bikaner– 334 006, Rajasthan, India
Cite article:- Jat Ram Sita, Gulati J. I., Soni M.L., Kumawat Amit, Yadava N.D., Nangia Vinay, Glazirina M., Birbal, Rathore V.S. (2017). Water productivity and yield analysis of groundnut using CropSyst simulation model in hyper arid partially irrigated zone of Rajasthan#. Legume Research. 41(5): 716-721. doi: 10.18805/lr.v40i04.9003.
CropSyst is one of the most important process-oriented simulation models largely used for field crops all over the world to study the effect of climate, soil and management practices on crop productivity. In the present study, we have calibrated and validated the CropSyst model for groundnut crop grown at farmer’s field in IGNP Stage-II of Bikaner. CropSyst model was calibrated using the experimental data of crop parameters, soil profile data and observed daily weather data of experimental site for 2012 and validated the experimental data of crop growth and yield parameters for 2013. The results of the study showed that the CropSyst model simulated the crop growth parameter data viz. green area index, seed yield, above ground biomass and N-uptake of groundnut reasonably well. The seed yield, above ground biomass and N- uptake was validated well by the model with relative error of 3.3, 2.2 and 8.4 %, respectively. The total water applied in groundnut was 728.9 and 619.6 mm in 2012 and 2013, respectively out of this 664.9 and 530.5mm consumed in evapotranspiration.
  1. Arora, V.K., Singh, C. and Singh, K. (1997). Comparative assessment of soil water balance under wheat in a sub-tropical environment with simplified models. J. Agric. Sci. 128: 461-468.
  2. Aujla, M.S., Singh, C.J., Vashist, K.K. and Sandhu, B.S. (1991). Evaluation of methods for irrigation of cotton (Gossypium hirsutam) in a canal irrigated area of south west Punjab, India. Arid Soil Res. 5: 225-234.
  3. Blake, G.R. and K.H. Hartge. (1986). Bulk Density. In A. Klute (ed.) Methods of Soil Analysis. Part 1 - Physical and Mineralogical Methods. Second Edition. American Society of Agronomy, Madison WI.
  4. Bouyoucos, H.J.(1962). Hydrometer method improved for making particle size analysis of soils. Agron. J. 54:464.
  5. Droogers, P. and Bastiaanssen, W. (2002). Irrigation performance using hydrological and remote sensing modeling. J. Irrig. Drain Eng. 128: 11-18.
  6. Harper, H.J. (1924). The accurate determination of nitrates in soils. Ind. Eng. Chem. 16: 180-183.
  7. Jalota, S.K., Parihar, S.S. and Gajri, P.R. (1985). Drainage loss under different irrigation schedules and stage sensitivity of wheat to
  8. water stress. Indian J. Agr. Sci. 55: 574-581.
  9. Jalota, S.K., Sood, A., Chahal, G.B.S. and Choudhary B.U. (2006). Crop water productivity of cotton (Gossypium hirsutum L.) – wheat (Triticum aestivum L.) system as influenced by deficit irrigation, soil texture and precipitation. Agr. Water Manage. 84: 137–46.
  10. Kijne, J., Barker, R. and Molden, D. (2003). Water productivity in agriculture: limits and opportunities for improvement. Comprehensive Assessment of Water Management in Agriculture, Series No. 1, CABI press, Wallingford, UK. pp 352.
  11. Molden, D. and Sakthivadivel, R. (1999). Water accounting to assesses and productivity of water, J. Water Res. Dev. 15: 55–72.
  12. Molden, D., Murray-Rust, H., Sakthivadivel, R. and Makin, I. (2001). A water productivity framework for understanding and action. Workshop on Water productivity. Wadduwa, Sri Lanka, November 12 and 13. ageconsearch.umn.edu/bitstream/127978/2/25.pdf.
  13. Peech, M., Alexander, L.T., Dean, L.A., and Reed, J.F. (1947). Methods of Soil Analysis for Soil-Fertility Investigations. U.S. Department Agricultural Circular, 25: 757.
  14. Prince, A.L. 1945. Determination of total nitrogen, ammonia, nitrates, and nitrites in soils. Soil Sci., 59: 47-52.
  15. Richards, L.A. (1954). Diagnosis and improvement of Saline and Alkali Soils. USDA Hand book No.60. Oxford and IBH Pub. Co. New Delhi.
  16. Singh, R., Jhorar, R.K., van Dam, J.C. and Feddes, R.A. (2006). Distributed eco hydrological modelling to evaluate the performance of irrigation systems in Sirsa district. India II: impact of viable water management scenarios, J. Hydrol. 329: 714–723.
  17. Stockle, C.O. and Nelson, R. (1999). Biological Systems Engineering Department, Washington State University, Pullman, WA, ClimGen, Manual, 28.
  18. Stockle C O, Martin S A and Campbell, G .S. (1994). CropSyst a cropping system simulation model: Water/nitrogen budgets and crop yield. Agric. Syst. 46:335–59.
  19. Stockle, C.O., Ddonattelli, M. and Nelson, R. (2003). CropSyst, a cropping system simulation model. Eur. J. Agron. 18: 289-307.
  20. Walkley, A. and Black, I.A. (1934). An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Sci. 37:29-32. 

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