Sidhu, Prabhjyot KaurSarabjit Singh2019-04-222019-04-222019http://krishikosh.egranth.ac.in/handle/1/5810100815A simulation study was conducted for predicting and optimizing wheat yield in Punjab under climate change scenarios using CERES-Wheat and InfoCrop-Wheat models. The actual data on phenology and yield of three wheat cultivars (WH 1105, HD 2967 and PBW 621) sown under five dates of sowing (28 October, 4 November, 11 November, 18 November and 25 November) during rabi 2014-15 were used for calibration and during rabi 2015-16 were used for validation of the two models. The anthesis and physiological maturity of wheat cultivars was predicted within -9 to +3 days and -7 to +1 days, respectively by CERES-Wheat and -3 to +11 and -10 to +1 days, respectively by InfoCrop-Wheat model. The calibration and validation of the CERES-Wheat and InfoCrop-Wheat model showed good agreement between the observed and simulated values with RMSE value 493.8 kg/ha and 434.4 kg/ha for grain yield respectively. Keeping in view the observed trends in climate variability, phenology and yield of wheat were simulated under climatic scenarios of changes in temperature (0.5, 1.0, 1.5, 2.0, 2.5, 3.0 oC from normal), solar radiation (2.5, 5.0, 10.0, 12.5, 15.0 20.0 % from normal) and their combined interactive effects during whole season, vegetative phase, grain filling phase, 0-30 days after sowing (DAS), 30-60 DAS and 60-90 DAS. In general, with an increase in temperature above normal, both the CERES-Wheat and InfoCrop-Wheat model predicted advancement in phenological development in wheat and vice versa. With the imposition of increase in temperature and decrease in solar radiation the CERES-Wheat model predicted decrease in grain yield. The maximum reduction in grain yield of wheat was observed in whole season followed by grain filling phase, vegetative phase, 60-90 DAS, 30-60 DAS and 0-30 DAS in decreasing order. On the other hand, InfoCrop-Wheat model did not respond to the change in phenology or yield with increase or decrease in solar radiation. The CERES-Wheat model predictions showed that wheat cv WH 1105 was more tolerant to heat and radiative stress than cv HD 2967 and cv PBW 621 and hence may be recommended for cultivation due to its tolerant traits towards maintaining its yield as well as harvest index. The InfoCrop-Wheat model predicted the sowing on 26 November with nitrogen application of 135 to150 kg/ha is best option for optimizing wheat yield but the InfoCrop-Wheat model did not respond under change in plant population. Hence as is indicative from several unexpected results simulated by the InfoCrop-Wheat model, the present version 2.1 of the model needs further scrutiny and refinement. The CERES-Wheat model predicted that amongst the growing windows, sowing of wheat on November 19 with plant population of 100 m-2 and nitrogen application of 135 to 150 kg/ha is the best for optimizing wheat yield in the state.ennullThesis