International Research Journal of Agricultural Economics and Statistics

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An Application of Principal Component Analysis for Pre-Harvest forecast Model for Wheat Crop Based on Biometrical Characters


Affiliations
1 Department of Agricultural Statistics, Narendra Deva University of Agriculture and Technology, Kumarganj, Faizabad (U.P.), India
2 Department of Agricultural Statistics, Narendra Deva University of Agriculture and Technology, Kumarganj, Faizabad (U.P.), India
     

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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.

Keywords

Principal Component Analysis, Biometrical Characters, Pre-Harvest Forecast Model, Wheat Experiment.
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  • An Application of Principal Component Analysis for Pre-Harvest forecast Model for Wheat Crop Based on Biometrical Characters

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Authors

Annu
Department of Agricultural Statistics, Narendra Deva University of Agriculture and Technology, Kumarganj, Faizabad (U.P.), India
B. V. S. Sisodia
Department of Agricultural Statistics, Narendra Deva University of Agriculture and Technology, Kumarganj, Faizabad (U.P.), India
V. N. Rai
Department of Agricultural Statistics, Narendra Deva University of Agriculture and Technology, Kumarganj, Faizabad (U.P.), India

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.

Keywords


Principal Component Analysis, Biometrical Characters, Pre-Harvest Forecast Model, Wheat Experiment.

References