Forecasting Productivity of Sugarcane in Coimbatore using ARIMA with Exogenous Variables

This paper proposes an appropriate ARIMAX model that is used to forecast the Sugarcane Productivity in Coimbatore. The Auto Regressive Integrated Moving Average with exogenous inputs (ARIMAX) model can take the impact of covariates on the forecasting process into account to improve the comprehensiveness and accuracy of the forecasting. The data used for the study is sourced from the indiastat website for a period of 56 years from 1960 to 2015. The Akaike Information Criterion AIC is adopted to assess the adequacy of the models. The ARIMAX (2,1,4), ARIMAX (1,1,2), ARIMAX (1,1,2), ARIMAX (1,1,3) with AIC values of -2.016, -1.920, -1.964, -2.013 are considered as the appropriate model to be combined with the Exogenous Variables such as Temperature, Rainfall, Sunshine Hours, and Evaporation. Commercial greenhouse operations can reap numerous advantages from employing Productivity forecasting. It allows growers to allocate resources as efficiently as possible, to start. It also helps with decision-making and crop planning. Producers are able to forecast market demand and adjust planting dates accordingly.