Use of Machine Learning: Prediction of Crop Yield in Madhya Pradesh, India

Abstract

Machine learning in agriculture is a very novel research, consists in the application of machine learning techniques to agriculture. Machine learning in agriculture field is a relatively research field. In this article describe an overview of machine learning techniques applied to agricultural and their applications to agricultural related areas. Yield prediction is a very important agricultural problem. Any farmer is interested in knowing how much yield he is about to expect. Previously yield prediction was performed by considering farmer's experience on particular field and crop. In any of machine learning procedures the training data is to be collected from some time back to the past and the gathered data is used in terms of training which has to be exploited to learn how to classify future yield predictions. Madhya Pradesh is the heart land of the country and Agriculture is the backbone of its Economy. Majority of the farmers are not getting the expected crop yield due to several reasons. The agricultural yield is primarily depends on weather conditions. Rainfall conditions also influences the rice cultivation. In this context, the farmers necessarily requires a timely advice to predict the future crop yield and an analysis is to be made in order to help the farmers to maximize the crop production in their crops. Yield prediction is an important agricultural problem. Every farmer is interested in knowing, how much yield he is about expect.