Crop Yield Prediction Using Machine Learning Techniques Based on Soil and Environment Traits – A Survey

In research, the examination of agriculture is increasing rapidly. Crop yield prediction is an important aspect in agriculture. In earlier days, farmers get good yielding. Due to the inefficiency in soil nutrients level and climatic changes crop yield level decreasing day by day. Hence, estimating the production is a crucial role in agriculture area also it helps to farmer for storing and marketing their yielded products. For predicting the precise agricultural yield, a variety of techniques, including remote sensing and machine learning, are used. This paper discussed a number of strategies for predicting crop yields that had been used by various researchers. In accordance to this review, the deployment of machine learning in agriculture indicates more effective and precise farming with fewer human assistance, as well as higher quality goods.