A Statistical Approach for the Assessment of Trend Dynamics of Maize Crop in India using Temporal Data

This paper analyzes the trend dynamics in production, area and yield of maize crop in India, based on temporal data over the period from 1994 to 2023. The trend values are obtained on fitting some well-known models viz., linear, quadratic, cubic and exponential models to the concerned data. Moreover, the precision of the fitted models have been examined using various statistical measures viz., coefficient of determination (R2 ), root mean square error (RMSE) and relative mean absolute percentage error (RMAPE). The outcomes of the analysis reveal that the fitted models are appropriate to investigate and predict the trend dynamics in production, area and yield of maize over the concerned period of study. Furthermore, in terms of production and yield, the cubic model exhibits higher precision as compared to the other fitted models. Also, in terms of area, the exponential model is preferable in comparison to other fitted models. The findings of the investigation could be effectively utilized for policy formulation regarding global trade policies on import and export of maize for attaining global food demand and nutritional security.