(untitled) (International Journal of Food and Nutritional Sciences, 2022)
In order to predict paddy output in Tamil Nadu, this study uses time series analysis using the robust ARIMA (AutoRegressive Integrated Moving Average) and SARIMA (Seasonal AutoRegressive Integrated Moving Average) models. This research makes use of historical data covering a number of years in order to investigate the complex temporal patterns and seasonal fluctuations that greatly affect paddy yields in the area. The research is conducted with the intention of developing a reliable framework for forecasting future paddy output, taking into account relevant aspects such as meteorological fluctuations, irrigation techniques, and governmental interventions. Farmers, policymakers, and others in the paddy cultivation sector can greatly benefit from a deeper understanding of the non-stationary and seasonal components within the industry thanks to the combination of ARIMA and SARIMA models. Sustainable and resilient paddy production in Tamil Nadu is ensured thanks to this study’s contribution to the improvement of agricultural plans and policies.