Time Series Modelling And Forecasting Of Pulses Productivity In Tamil Nadu, India

Abstract

Pulses are staple protein-rich food for Indian vegetarians, and India is one of the largest producers in the world. Pulse production is influenced by a variety of elements such as rainfall, fertilizer, crop area as well as productivity. Analysis of production behavior, modeling and forecasting of productivity taking all these factors in to consideration play vital roles in human nutritional security. The present investigation is an attempt to predict and forecast the productivity of total pulses in Tamil Nadu using time series data. The present study was carried out to efficiently forecast the productivity of black gram, chickpea, green gram, horse gram, red gram, and total pulses in Tamil Nadu. Yearly data were used for the period from 1970 to 2020. based onthe results of model adequacy criteria, the most suitable ARIMA (autoregressive integrated moving average) model and Holt's Linear Trend model are chosen to capture the pulse productivity. Results revealed that Holt's linear trend model fits best for black gram, chickpea, green gram, and red gram. ARIMA (0,1,1) fits best for horse gram and ARIMA (3,1,0) fits best for the total pulses productivity. The forecasted value of pulses using the bestfitted model shows that there is a steady increase in the productivity of pulses. The productivity of total pulse increases in 2021,2022,2023 but slightly decreases in 2024 and again increases in 2025. This study will play an important role in determining the gap between the productivity of and demand for pulses in the future.