Review of Crop Yield Prediction using Machine Learning Techniques

Abstract

Machine learning (ML) could be a helpful decision-making tool for predicting crop yields, in addition as for deciding what crops to plant and what to try throughout the crop's growth season. To help agricultural yield prediction studies, variety of machine learning techniques are used. I performed a literature review (LR) to extract and synthesize the algorithms and options employed in crop production prediction analysis. Temperature, rainfall, and soil types are most common measure used in the prediction as per my knowledge, whereas Artificial Neural Networks is the foremost normally used methodology in these models.