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The estimation of crop yield before harvest helps in different policy making in an order for storage, distribution, marketing, pricing, import-export etc. Crop productions depend on several factors such as weather factors, plant characters and agricultural inputs. The present study was carried out to develop the appropriate statistical model for estimation of rice yield before harvest in the year 2018-19. This research was done on plant biometrical characters along with farmer’s appraisal. Sample survey was done on farmer’s field through multistage stratified random sampling method and recorded fourteen parameters such as X1 (Number of irrigation), X2 (Average plant population), X3 (Average plant height), X4 (Average number of effective tillers), X5 (Average length of panicle), X6 (Average length of flag leaf), X7(Average width of flag leaf), X8 (Average number of filled grain), X9 (Damage due to pest and disease infestations), X10 (Applied nitrogen), X11 (Applied phosphorus), X12 (Applied potassium), X13 (Average plant condition) and Y (Yield). By the help of step-wise regression technique to select thirteen models on the basis of minimum BIC value and then after best models were selected on the basis of minimum AIC value. | Yield estimation of rice crop at pre-harvest stage using regression based statistical model for arwal district, Bihar, India
