An application of principal component analysis for pre- harvest forecast model for wheat crop based on biometrical characters

Abstract

An application of principal component analysis for the development of suitable statistical models for pre-harvest forecast of wheat yield based on biometrical characters has been illustrated in the present paper. The data obtained from the experiments on wheat under normal and late sowing situations have been utilised to develop the model. The result have revealed that the proposed model can provide reliable pre- harvest forecast of wheat yield in both the situations within the reasonable range of per cent standard error of 2.16 to 4.96 per cent.