Crop Environment Resource Synthesis (CSM-CERES)-Wheat model was used to simulate responses of two wheat varieties with various sowing environments. In this context, during the year 2007-08 and 2008-09, experiments on three sowing dates viz. November 20, December 15, and January 9 and two varieties (PBW-343 and WH-542) with three replications were conducted at the Norman E. Borlaug Crop Research Centre of G.B. Pant University of Agriculture & Technology, Pantnagar (29°N, 79.29°E with 243.80 m above msl). Soil, plant, management and climatic data were collected from the experimental field. The data of 2007-08 and 2008-09 were used for model calibration and validation, respectively. Results revealed that the for model outputs were in good agreement with their corresponding observed values with 20th November sown crop than other sowings of crop in terms of phenological events, biomass accumulation and grain yields. However, variety PBW-343 showed close proximity between simulated and observed outcomes with all sowing dates. The percent root mean square error (% RMSE) values ranged from 5.9 – 15.6%, 2.2 – 7.6% for days to attain anthesis and physiological maturity, respectively. Moreover, %RMSE and t-value ranged from 5.7–12.2% (t= -4.5 to 1.8), 1.6 – 3.3% (t= -4.1 to 4.5) and 1.9 – 5.8% (t= -3.7 to 1.5) for product weight, vegetative weight and product harvest index, respectively. Inspite of that, model fails to simulate maximum leaf area index having % RMSE from 53.2 – 62.9%. These results indicate that CERES-Wheat model can be used as a tool to support decision-making for wheat production in Tarai region of Uttarakhand.
CERES-Wheat, Sowing dates, Wheat varieties
Bannayan, M., Crout, N.M.J. and Hoogenboom, G. (2003). Application of the CERES-Wheat model for within –season prediction of wheat yield in United Kingdom. Agron. J., 95: 114–125.
Bannayan, M., Kobayashi, K., Marashi, H. and Hoogenboom, G. (2007). Gene-based modeling for rice: an opportunity to enhance the simulation of rice growth and development ? J. Theor. Biol., 249: 593–605.
Bassu, S., Asseng, A., Motzo, R. and Giunta, F. (2009). Optimizing sowing date of durum wheat in a variable Mediterranean environment. Field Crops Res., 111: 109–118.
Datt, S., Shukla, S.N., Singh, S.S. and Shoran, J. (2009). Wheat: Many physiological traits have strong correlation with terminal heat tolerance. The Hindu Survey of Indian Agriculture, pp. 41-42.
Dhaliwal, L.K., Singh, G. and Mahi, G.S. (1997). Dynamic simulation of wheat growth, development and yield with CERES-wheat model. Annals of Agricultural Research, 18 (2): 157-164.
Department of Agriculture & Co-operation (2012), Statewise Area, Production and Yield of Wheat for the year 2011 -12.http://www.agricoop.nic.in/imagedefault/trade/wheat%20profile.pdf
Ghaffari, A., Cook, H.F. and Lee, H.C. (2001). Simulating winter wheat yields under temperate conditions: exploring different management scenarios. Eur. J. Agron., 15: 231–2440.
Heng, L.K., Asseng, S., Mejahed, K. and Rusan, M. (2007). Optimizing wheat productivity in two rainfed environments of the west Asia-North Africa region using simulation model. Eur. J. Agron., 26: 121–129.
Heng, L.K., Baethegen, W.E. and Moutoonnet, P. (2000). The collection of a minimum data set and the application of DSSAT for optimizing wheat yield in irrigated cropping systems, pp. 7–17. In: Optimizing Nitrogen Fertilizer Application to Irrigated Wheat, IAEA TECDOC-1164, p. 245.
Hoogenboom, G., Jones, J.W., Wilkens, R.W., Batcheloro, W.D., Hunt, L.A., Boot, K.J., Singh, U., Uryasev, O., Bowen, W.T., Gijsman, A.J., du Toit, A., White, J.W. and Tsuji, G.Y. (2010). Decision support system for Agro-technology Transfer Version 4.5 [CD- ROM] University of Hawaii, Honolulu, HI.
Hundal, S.S. and Kaur, P. (1997). Application of the CERES-Wheat model to yield predictions in the irrigated plains of the Indian Punjab. J. Agric. Sci. Cambridge., 129: 13–18.
Jones, J.W., Hoogenboom, G., Porter, C.H., Boot, K.J., Batchelor, W.D., Hunts, L.A., Wilkens, P.W., Singh, U., Gijsman, A.J. and Ritchie, J.T. (2003). DSSAT cropping system model. Eur. J. Agron., 18: 235–265.
Kaur, M., Singh, K.N., Singh, H., Singh, P. and Tabasum, S. (2007). Evaluation of model CERES-wheat (v4.0) under temperate conditions of Kahmir Valley. World J. of Agril. Sci., 3(6): 825-832.
Kour, M., Singh, K.N., Singh, M., Thakur, N.P. and Kachroo, D. (2010). Phenophase prediction model for wheat (Triticum aestivum L.) growth using agrometeorological indices sown under different environments in temperate region of Kashmir. J. Agrometeorol., 12(1): 33-36.
Meza, F.J., Silva, D. and Vigil, H. (2008). Climate change impacts on irrigated maize in Mediterranean climates. Evaluation of double cropping as an emerging adaptation alternative. Agric Syst., 98: 21–30.
Mitchell, R.A.C. (1996). Predicting the effects of environmental change on winter wheat yield in genotypes with different flowering dates. Aspects of Applied Biology, 45: 133-138.
Nain, A.S. and Kersebaum, K.Ch. (2007). Calibration and validation of CERES-Wheat model for simulating water and nutrients in Germany K.Ch. Kersebaum (Ed.) et al., Modeling Water and Nutrient Dynamics in Soil-Crop -Systems, Springer, pp. 161–181.
Nain, A.S., Dadhwal V.K. and Singh T.P. (2002). Real time wheat yield assessment using technology trend and crop simulation model with minimal data set. Current Sci., 82(10): 1255-1258.
Ouda S.A., El-Marsafawy, S.M.; El-Kholy, M.A. and Gaballah, M.S. (2005). Simulating the effect of Water Stress and Different Sowing Dates on Wheat Production in South Delta. Journal of Applied Sciences Research 1: 268-276.
Pal, R.K., Murty, N.S. and M.M.N. Rao (2012). Evaluation of yield, dry matter accumulation and leaf area index in wheat (Triticum aestivum L.) genotypes as affected by different sowing environments. Environ. Ecol., 30 (4A): 1469-1473.
Pal, R.K., Rao, M.M.N. and Murty, N.S. (2013). Relative temperature disparity and wheat yield as influenced by sowing environments and genotypes in Tarai region of Uttarakhand. Environ. Ecol., 31 (2B): 979-983.
Pal, R.K., Tripathi, Padmakar and Mishra, A.K. (2008). Simulation modeling of growth parameters of wheat genotype using CERES-wheat model, J. Agrometeorol. (Special Issue-Part- I): 125-126.
Patel, H.R., Patel, G.G., Shroff, J.C., Pandey, V., Shekh, A.M., Vadodaria, R.P. and Bhatt, B.K. (2010). Calibra-tion and validation of CERES-wheat model in middle Gujrat region. J. Agrometeorol., 12(1): 114-117.
Ritchie, J.T., Singh, U., Godwin, D.C. and Bowen, W.T. (1998). Cereal growth, development and yield G.Y. Tsuji, G. Hoogenboom, P.K. Thornton (Eds.), Understanding options for agricultural production, Kluwer Academic publishers, Dordrecht, The Netherland, pp. 79–98.
Sarkar, R. and Kar, S. (2006). Evaluation of management strategies for sustainable rice-wheat cropping system, using DSSAT seasonal analysis. J. Agr. Sci., 144:421-434
Timsina, J. and Humphreys, E. (2006). Performance of CERES–rice and CERES-Wheat models in rice–wheat systems: a review. Agric. Syst., 90: 5–31.
Timsina, J., Sigh, U., Singh, Y. and Lansigan, F.P. (1995). Addressing sustainability of RW systems: testing and applications of CERES and SUCROS models Proceedings of the International Rice Research Conference, 13–17 February 1995, IRRI, Los Banos, Philippines, pp. 663–656.
USDA (2014). Production, Supply, & Distribution: Field Crops Production- Wheat Area, Yield, and Production at www.fas.usda.gov/psdonline, Date Created 04/09/2015.
Wajid, A., Hussain, K., Maqsood, M., Khaliq, T. and Ghaffari, A. (2007). Simulation modeling of growth, development and grain yield of wheat under semi arid conditions of Pakistan. Pak. J. Agri. Sci., 44(2): 194-199.
Zhang, X., Wang, S., Sun, H., Chen, S., Sho, L. and Liu, X. (2013). Contribution of cultivar, fertilizer and weather to yield variation of winter wheat over three decades: a case study in the North China Plain. Eur. J. Argon., 50: 52–59.
This work is licensed under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) © Author (s)