Author(s):

Bhola Nath, SN Singh and Gaurav Kumar Rai

Abstract: Reliable and timely forecast of crop production are required for various policy decisions related to storage, distribution, pricing, marketing, import-export etc. Pre-harvest forecast of rice yield has a great importance in Bihar as there is much more area and production of paddy in this state [Kumar et al. (2013)]. To establish the relationship among Yield (Y), Average Plant Population (X₁), Average Plant Height (X₂), Average number of effective Tillers (X₃), Average Length of Panicle (X₄), Nitrogen (X₅), Phosphorous (X₆), Potash (X₇), Number of Irrigations (X₈), Pest and Disease Infestation (X₉) and Average Plant Condition (X₁₀), a questionnaire based on biometrical character and farmer’s appraisal for rice crop was developed. The variable Y was used as dependent and all other X’s were as independent. Further, five regression models were selected for minimum RMSE. Regression analysis was performed for each model. All five models were highly significant. Out of five selected regression models, Model-V i.e. had the minimum Standard Error of Mean Predicted (1.08670) value. Its residuals value was zero and RMSE value was 3.36722. From these analyses it was reflected that Model-V is the best which was used for pre-harvest forecast of rice yield. By using this model pre-harvest forecast of rice yield in Bhagalpur is about 43.80967 (q/ha) for the year 2016-17 based on biometrical characters and farmer’s appraisal.

Pages: 2342-2345  |  826 Views  211 Downloads

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