Development of agro-climatic grape yield model for Nashik region, Maharashtra, India

Abstract

Prediction of the crop yield is need of time according to the change in climate conditions. In the present study, the Agro-Climatic Grape Yield (ACGY) model has been developed with monthly climatic parameters using multi-regression analysis approach. The developed model was statistically tested for its predictive ability. The discrepancy ratio, the standard deviation of discrepancy ratio, mean percentage error and standard deviation of mean percentage error for the model was obtained as 1.03, 0.19, 0.03% and 0.19, respectively. Sensitivity analysis was carried out for the developed ACGY model using the parametric sensitivity method. In order to know the future grape yield using ACGY model, climate scenarios were generated under Canadian Earth System Model (CanESM2) for three emissions representative concentration pathways as RCP2.6, RCP4.5, and RCP8.5. According to the analysis using ACGY model, increasing yield was observed in grape up to year 2050 as compared to current yield.

Studying on Crop Response Model for Grapes under Climate Change Scenario: Statistical Study Approach

“…Multiple regression approach was used to develop an agro-climate grape yield (ACGY) model using climatic parameters and the developed model had been statistically tested for its predictive ability. Sensitivity analysis was carried out for the developed ACGY model using the parametric sensitivity method [7].…”

Crop Production Prediction Models in Indian Agriculture: Possibilities and Challenges

“…Stepwise multiple linear regressions (SMLR) is a regression technique where potential variables are added and weakly correlated variables are removed at each step based on the p-value and checked for statistical significance. Kadbhane and Manekar (2020) developed Agro-Climatic Grape Yield (ACGY) model based on multi regression analysis. Climatic factors for every month were used as input parameters.…”