Time Series Forecasting for Sustainable Sugar Cane Farming in Tamil Nadu

Abstract

The present research study aims to examine the importance of sustainable sugarcane growing in Tamil Nadu, India, through the utilization of modern time series forecasting methodologies. This study aims to examine the complex dynamics and fluctuations within the sugarcane production sector. It specifically explores the effects of climate variations, irrigation techniques, and agricultural regulations on sugarcane yield. The research endeavors to generate precise forecasts for future sugarcane production by employing the robust ARIMA (AutoRegressive Integrated Moving Average) and SARIMA (Seasonal AutoRegressive Integrated Moving Average) models. The study sheds light on the temporal variability and long-term trends that impact the sustainability of sugarcane production by incorporating historical data and seasonal patterns. The findings obtained from this study play a pivotal role in educating stakeholders, farmers, and policymakers about the essential elements of sustainable sugarcane farming. This knowledge facilitates the establishment of resilient agricultural methods and policies that safeguard the ongoing expansion and stability of the sugarcane industry in Tamil Nadu.