Prediction on Soybean Crop Yield Applying Machine Learning Regression

In modern times, agriculture heavily relies on crop yield prediction systems to provide farmers with various insights into the potential outcomes of their farming practices. The system we developed uses regression to predict the soybean crop yield. The soybean crop yield prediction system is invaluable for farmers, aiding them in making informed decisions regarding the optimal timing for getting analytics about the crops based on different factors to maximize yield. The factors, such as precipitation, solar radiation, and minimum and maximum temperatures, are also considered in the developed model data. In this study, the dataset used consists of soybean crop yield data and all the crop yield affecting parameters from the past thirty-eight years, which are gathered from 105 different locations.