The impact of climate change on agricultural crops is a major concern and threats to the global food security. It also limits the potential of crops and cropping system in a given area. Therefore, the present study was aimed to assess the combined effect of positive (CO2 fertilization, lesser temperature and higher rainfall) and negative (higher temperature, lower rainfall) impacts of the futuristic climatic scenarios on productivity of soybean using APSIM (Agricultural Production Systems sIMulator) model. We have followed the Climate-Crop Modeling Project (C3MP) methodology and generated ninety-nine sensitive test to achieve each test’s temperature, rainfall and CO2 concentration range. Using 30 years of climate data (1980-2010) of Central India as base, the simulation results showed that increasing CO2 concentrations alone resulted in increased soybean yield. Similarly, reduction in rainfall amount indicated negative impact on it. This effect further compounded with increase in temperature and thus, reduced soybean yield. Increasing the temperature with 10% decrease in rainfall declined the soybean yield by 10%. Whereas, increase in temperature along with increase in rainfall also not resulted favorably soybean growth. Decreasing the temperature from the base by 1oC and increasing the rainfall by more than 10% benefitted the soybean productivity, whereas increasing the temperature by 1oC with no change in rainfall resulted decline in soybean productivity by 10-15%.

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Quantifying the yield potential of maize at any given site is a key to understand the existing yield gaps and to identify the most important constraints in achieving optimal yield and profit. A well parameterized and validated APSIM model was used to assess the productivity and yield gap of maize cv Kanchan 101 from multi-year long-term and completed experiments. A total of 30 districts with 74 soil profiles of Madhya Pradesh were considered for the study. For the 30 selected sites, the rainfed potential yield of maize (Ywp) ranged from 3.3 to 5.2 t ha-1 whereas the districts mean yield (Yf) ranged from 0.7 to 3.1 t ha-1 giving yield gaps ranging from 1.7 to 3.1 t ha-1. It was observed from the long-term simulation study that there is a good potential to improve the grain yield of maize crop by 3.0 t ha-1 provided optimum dates of sowing and good management practices are followed in the state.