Sugarcane Yield and Price Prediction Using Forecasting Models

Abstract

Sugarcane is one of the most significant commercial crops that grow in India. Machine learning (ML) make advancements in many fields including agriculture. Through the provision of detailed advice and insights into the quality and output of the crops, machine learning is a modern technology that helps farmers reduce their farming losses. Estimation of sugarcane yield and prices are performed in order to make a profitable decision prior to the cultivation of the crop. The machine learning algorithms Decision Tree Regressor, Multi Linear Regression, Random Forest, Adaboost Regressor, Lasso (Least Absolute Shrinkage and Selection Operator) Regression, are used to forecast yield of the sugarcane crop. The ARIMA model is used to forecast the sugarcane crop's price. Forecasting sugarcane yield is depending on the parameters like previous sugarcane yield in particular area, rainfall, state where sugarcane is cultivated. Sugarcane price is forecasted based on time series analysis of previous history of prices.