Author(s): Aishwarya Patil and Nishant Shende

Abstract: The present study has been conducted to study the impact of climate change on productivity of soybean in Akola district. Time series data ranging from 1901 to 2020 on area, production, productivity of soybean has been taken from government publications, websites. The data of selected climatic factors such as rainfall, maximum temperature, minimum temperature, morning relative humidity, evening relative humidity, wind speed, bright sunshine hours, evaporation has been collected from Department of Agronomy, Dr. PDKV, Akola. The Shapiro-Wilk test has been used for checking normality of data. Karl Person’s Correlation Coefficient and Spearman’s Rank Correlation has been used to examine the relationship between area, production, productivity and climatic factors for soybean crops. Furthermore, Multiple Linear Regression Technique has been used to study the impact of climate change on productivity of soybean. Mann-Kendall test and Sen’s Slope Estimator has been used to identify the trends in selected climatic factors with their magnitude. The results revealed that, Productivity of soybean data follows normal distribution where area and production does not follows normal distribution. Area of soybean is strongly positively correlated with production of soybean which is significant both at 5 per cent and 1 per cent level of significance. For soybean crop, minimum temperature does not follow the normal distribution. Productivity of soybean is positively correlated with rainfall which is significant at 5 per cent level of significance. The results of multiple regression indicates that 33 per cent of variation in productivity of soybean is due to climatic factors. The result of trend analysis indicates that for soybean crop there is negative (decreasing) trend for wind speed and bright sunshine hours.

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