Statistical models for wheat yield using linear regression model based on meteorological parameters

Abstract

In the present paper, an application of regression analysis of weather variables (minimum & maximum temperature, relative humidity 7 hr & 14 hr, rainfall, rainy day and wind velocity) for developing suitable statistical models to forecast Wheat yield in Ayodhya district of Eastern Uttar Pradesh has been demonstrated. Time series data on Wheat yield for 27 years (1990-91 to 2016-17) have been used in the regression model. The forecast yield of Wheat have been obtained from this model for the year 2014-15, 2015-16 and 2016-17, which were not included in the development of the model. This model has been found to be most appropriate on the basis of Adj R2, percent deviation of forecast, percent root mean square error (% RMSE) and percent standard error (PSE) for the reliable forecast of Wheat yield about two months before the crop harvest.