Post-harvest soil nutrient prediction in hybrid castor (Ricinus communis l.) Cropping sequence using a multivariate analysis technique

In the era of precision agriculture, fertilizer prescription based on soil fertility status is much required. Analyzing after each crop necessary for recommendation and developing an alternative technique to forecast available nutrient value rather than analyzing soil. Multiple linear regression (MLR) equation was developed using filed experiment data predict in castor cropping sequence. The post-harvest considered as dependent variable initially values, added, yield uptake independent variable. general, model's prediction accuracy notable had a coefficient determination less 0.90. By calculating RMSE (root means square error), R2 value, ratio performance deviation (RPD) and, RE (relative error) MLR model confirmed.Using validated model, nutrients were predicted compared with laboratory tested nutreints. It turned out that established more precisely effective equally precise. Fertilizer could be made subsequent hybrid nutrients.