A Machine Learning Model for Prediction of Crop Yield

  • M.Chenna Keshava, K.Swetha, R.BramhaTeja, M.Kirandeep


Agriculture is the important contributor and revenue producing sector in India. Every farmer is interested to know about the amount of yield he is going to obtain. In Agriculture, most of the things have been changing due to global warming and other factors which lead to decline in crop yield. To overcome the issue, we developed a model that can predict the yield of the crop based on the previous crop data statistics. Machine Learning algorithms are the better choice to predict crop yield. This machine learning model also suggests the farmers to harvest high producing crops to increase profits and to meet the food needs of the country like India. We can analyze this using various machine learning algorithms like Linear Regression algorithm, Decision Tree algorithm, Random Forest algorithm. This research presents a short analysis of crop yield prediction for the selected state i.e., Andhra Pradesh in India. The complete research comes up to a conclusion that Decision Tree algorithm is the suitable technique for prediction. The experimental results showed that proposed machine learning model efficiently predicts the crop yield production.  

 Keywords: agriculture, crop yield, decision tree, linear regression, machine learning, prediction, random forest, suggests.