MACHINE LEARNING APPROACHES FOR CROP YIELD PREDICTION-REVIEW

The agriculture is one of the factors in the growth of economy of our country. As changes in environment, it has a great impact on production and maintenance of agriculture crops. Predicting the crop yield help the farmers in estimating the crop's harvest time and further storing and selling of crops. Correctly estimating of crop yield is crucial in agriculture field because it will help in managing crops in future. Here, Machine Learning plays a important role. Use of Machine learning starts from growing of seeding phase to harvesting of crops.ML incorporate various computer vision techniques to capture the visuals of crops to analyze crops, checking weather condition to make effecting decision. The aim of this is to reduce operational costs also. Using ML technology, objects characteristics can be identified, measured and analyzed using devices having sensors without direct contact to that object. These sensor collects large amounts of data remotely and given for ML processing. In this paper, reviews are given about the various developments done to estimate accurate crop yield prediction.