Non-Linear Growth Models for Acreage, Production and Productivity of Food-grains in Haryana

Abstract

In order to understand the growth patterns of diverse commodities, agricultural research heavily relies on the computation of growth rates. For the computation of the growth rate, many researchers adopted the parametric approach rather than the non-linear model. In this paper, an attempt has been made to develop non-linear growth models for acreage, production and productivity of total (kharif + rabi) food-grains in Haryana from 1966 to 2021. We discussed different non-linear growth model viz. Logistic, Gompertz and Monomolecular and also determined the initial value for each parameter. The parameters were estimated using Levenberg - Marquardt’s iterative method of non-linear regression. Best model was selected based on goodness of fit statistics such R2, RMSE and MAE. Finally we concluded that Logistic model was found suitable to fit for acreage, production and productivity of food-grains grown in Haryana followed by Gompertz model. Forecasting for the period 2022–2026 was done using the selected best non linear growth model.