The simulation results obtained on the mitigatory option for reducing the negative impacts of temperature increases indicate that delaying the sowing dates would be favourable for increased soybean yields for this region. There was a decrease (ranging between 20 and 35 %) in soybean yield when the effect of the rise in surface air temperature during soybean growing season was considered. The projected temperature scenarios for the Indian subcontinent as reported by IPCC have been used in the present study. The validated APSIM model was also used to simulate the impact of climate change on soybean production in central India. There was a significant decrease in yield (37 %) from the maximum when the drought spell occurs at some parts of the growing season. The yield reduction was 56 % when a drought spell of around 2 weeks occurs during mid-vegetative stage. There was a significant decrease in soybean yield (as high as 96 %) when the rainfall receded during the initiation of flowering to maximum pod stage. soybean belt the model had to be modified to simulate tile drainage. The distribution of rainfall rather than the amount during the soybean growing season is important for soybean yield. The model APSIM is a component-based simulation frame. The long-term prediction revealed that there was an interannual variation in soybean yield due to the variation in rainfall pattern. A well-calibrated and validated APSIM model was used for a long-term simulation study on the impact of rainfall pattern on soybean yield. Hence, the present study aims at using the APSIM model in the decision-making process to evaluate the impact of climate change on soybean yield.įor the simulation study, the optimum date of sowing was chosen based on the literature available for this region. They have been evaluated and used as a research tool to study risks associated with various management strategies and to assist in decision-making. The APSIM model was parameterized for soybean and wheat crops grown during the year 20032005 in field experiments conducted at the research farm of the Indian Institute of Soil Science, Bhopal (23.28 N, 77.48 E). Simulation models with demonstrated accuracy and reliability provide an alternative method of investigating both short- and long-term agricultural practices with less time requirements and low cost. So, proper management practices which include crop management (use of nutrients, planting time and plant population) will play a major role in future productivity in these regions. The climate change (increase in temperature, CO 2 concentration and rainfall) will affect this rainfed crop in the future. Despite its phenomenal growth in this agro-climatic zone, the average productivity of soybean has remained more or less at 1 t ha −1 due to several abiotic, biotic and socio-economic factors.
Soybean has emerged as one of the major rainy season oilseed cash crops in central India.
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