ANN-Based Wheat Crop Yield Prediction Technique for Punjab Region

Abstract

Crop yield prediction is one of the most important aspects related to agriculture. Pre-harvest prediction of a crop can not only help farmers in pre-planning their activities, but also help the government of a country in formulating plans regarding import or export of a crop and also in being ready to face any upcoming challenge. Many researchers have used crop process models for the purpose but sometimes their results are not reproducible on the fields. The need of the hour is to find a technique that can deal with the nonlinear behaviour that is inherent in the study. The tremendous success of machine learning techniques in various fields has raised new hopes in the field of agriculture, especially in the area of crop yield prediction. In this study, we have employed artificial neural network (ANN) to predict yield of wheat in the region of Punjab. The experimental results have shown good potential for ANN as compared to multivariate linear regression.