Statistical Modeling and Significance of Inputs Studies for the Rice Crop Productivity in Pakistan

Abstract

Lower production of rice crop and increasing population trend is a tangible question for Pakistan. The current study based cross-sectional data collected from crop reporting service Punjab. The multiple linear regression (MLR) model is applied to investigate the significant factor for rice crop yield enhancement. The inputs variable i.e. owned land, seed rate, DAP, Urea, no. of water, no. of ploughs, no. of levels, crop life periods days, other fertilizers, variety super yes or no, seed type yes or no, spray no or yes and disease attack yes or no are studied in MLR model for rice productivity. All the factors found to be statistical significant except land, level, crop life period and super variety. Adj R2 is found to be 0.422 and it is good fit for cross-sectional data.