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Soybean is grown predominantly under rainfed conditions where weather variability is high. To analyse the effects of climate change on soybean growth and production, CROPGRO model (DSSAT v 4.5) was applied with four different sowing dates for the diverse environment of akola region of Vidarbha, India. Environmental modification simulated with up scaling of maximum temperature from 1 °C to 5 °C decreased the yield by -4.7-50.4% under 27 MW sowing whereas the magnitude of yield reduction was to a greater degree with delayed 30 MW sowing recorded -8.1 to 78.8% reduction. The down scaled minimum temperature increased the yield by +1.2% at 1 °C downscale. Subsequently, downscaled minimum temperature by 2 to 5 °C decreased the seed yield by -2.5 to -23.7% under 27 MW sowing whereas downscaled minimum temperature by 1 to 5 °C decreased the seed yield by -1.6 to -42.9% under 30 MW sowing. Simulation of CO2 concentration raised by 100, 200 and to 300 ppm, over the base value (392 ppm) increased seed yield by 16.5 to 38.6% under 27 MW sowing whereas under 30 MW, it increased the seed yield only by 12.8 to 30.4%. Elevated CO2 concentration of 100 ppm coupled with elevated maximum temperature level by 1, 2 and 3 °C decreased the yield level by -5.4 to -25.7% under 27 MW sowing and -28.4 to -50.8 under 30 MW sowing. Thus overall results show that delay in sowing date in rainfed regions has more negative consequences on soybean productivity under different climate change scenario than early sowing of soybean.

international journal of bio-resource and stress management/international journal of bio-resource and stress management

Application of the CROPGRO-Soybean Model (DSSAT V 4.5 ) for the Assessment of the Environmental Modification Effect on Soybean Productivity in the Akola region of Vidarbha, India