Pre-harvest forecast models for wheat yield based on biometrical characters

Abstract

Some statistical models for pre-harvest forecast of wheat yield based on biometrical characters in situation of normal and late sowing of wheat have been developed in the present paper. In both the situations, linear multiple regression model (model-I), where biometrical characters are used in the original form, has been found to be the best forecasting model as it has consistently smaller percent standard errors for the forecast yield of wheat alongwith maximum value of R2adj. (49 to 51%).