Machine learning is a useful decision-making tool for predicting crop yields, as well as for deciding what crops to
plant and what to do during the crop's growth season. To aid agricultural yield prediction studies, a number of machine learning
techniques have been used. We employed a Systematic Literature Review (SLR) to extract and synthesize the algorithms and
features used in crop production prediction research in this investigation This paper provides a comprehensive overview of the
most recent machine learning applications in agriculture, with a focus on pre-harvesting, harvesting, and post-harvesting issues.
