Soybean and wheat crop yield forecasting based on statistical model in Malwa agroclimatic zone

Abstract

Pre harvest crop yield forecast is required for storage, pricing, marketing, import, export etc. weather is the main factor which affects crop yield. Variability in weather causes the losses in the yield. Use of weather can be done for crop production forecast. Weather plays important role in crop growth. Therefore model based on weather parameters can be provide reliable forecast in advance for crop yield. In this study, the focus was on the development of crop yield forecast model through stepwise regression technique using weather variables and historic crop yield. The model uses, maximum and minimum temperature, rainfall, relative humidity and relative humidity II during crop growing period and long term yield data of soybean and wheat crop. Yield prediction was carried out for soybean and wheat in 8 districts of Malwa agro climatic zone during 2017-18. Accuracy of these models are tested with coefficient of determination (R2).