Machine Learning Algorithms In Agriculture: A Literature Review On Climate And Price Prediction, Pest And Disease Detection, And Production Monitoring

The demand for food is growing every year and demands more significant technology applications in the field Furthermore, due to food production, pests and climate change incidents are a real-time challenge for farmers. Due to the growing need to apply algorithms in the field, we investigate the algorithms most cited, used, and ongoing projects in the last three years, from 2019 to 2021 Therefore, we evaluated articles that focus was mainly on supervised learning algorithms This literature review presents an overview of algorithms usage in agriculture. A total of 81 articles were analysed. Our contributions as a) an analysis of the state-of-the-art on applying algorithms to various agricultural functions and b) a taxonomy to help researchers, governments, and farmers choose these algorithms. This article adds discoveries about the application of algorithms in crops, machinery, and processes and points out new lines of research.