Greengram Based Cropping Sequence for Sustainability under Changing Climate in Semi-arid Part of Karnataka, India

Abstract

Background: Greengram based cropping sequences are followed in semi-arid parts of Karnataka, India. But, due to increasingly erratic and changing monsoon patterns under current climates the sustainability and profitability of these sequences are becoming more uncertain. Hence, a modeling study using seasonal analysis tool of DSSAT model was taken up to identify the most reliable sequence.Methods: Field experiments were carried out from 2015-2018 to calibrate and validate DSSAT model for four crop cultivars (greengram, chickpea, wheat and sorghum) under rainfed condition on deep black soils and then Sequential Analysis Tool of DSSAT model was run for 32 years (1985-2016) for three cropping sequences i.e., greengram-sorghum, greengram-wheat and greengram-chickpea. The simulated output analysis was done using yield, number of years crop failed during different seasons and the B:C ratio of each sequence. Result: Out of 32 years greengram crop, grown during kharif, failed only once whereas, during rabi season wheat, sorghum and chickpea failed seven, six and five years, respectively. Greengram-chickpea sequence recorded the highest B:C ratio (2.38) followed by greengram-sorghum (2.25) and greengram-wheat (1.76). Considering chances of crop failure and B:C ratio greengram-chickpea sequence was found to be the most reliable and remunerative system under rainfed condition of Karnataka during current climate.