A State-of-the-Art Survey of Machine Learning in the Agricultural Sector

Food is regarded as a basic human requirement that may be met through agriculture. The globe over, agriculture is seen as a source of employment in addition to providing for humankind’s basic requirements. In emerging nations like India, where agriculture provides a source of employment, it is seen as the foundation of the economy. 15.4% of India’s GDP is derived from agriculture. Pre-harvest, harvest, and post-harvest activities in agriculture are typically divided into these three categories. Gains in agriculture have improved as a result of advancements in the field of machine learning. Machine learning is a cutting-edge technology innovation that assists farmers in lowering their farming losses by providing thorough recommendations and insights into the crops. In order to address problems in the three stages of agriculture namely pre-harvesting, harvesting, and post-harvesting, this study gives an exhaustive assessment of the current machine learning applications in agriculture. Utilizing machine learning techniques in agriculture enables added precise and effective agriculture with high-quality output using less human labor.