Volume 10 Issue 4 ( December )

Agriculture is a key employment in several countries throughout the globe. AI is increasingly becoming a part of agriculture industry as traditional methods are insufficient to supply the massive survival needs of millions of people. AI, in form of machine learning and deep learning, is capable of providing a number of strategies that assist in the creation of more healthy seeds. This paper discusses significance of machine learning and deep learning that growers can use to gain access to increasingly sophisticated data and analytical tools, allowing them to make better decisions, improve efficiencies, and reduce wastes in food and bio-fuel production while minimizing negative environmental impacts. On the basis of critical parameters like temperature, rainfall, humidity, soil type, soil characteristics etc., ML and DL operate as recommenders and advise farmers to take the right action. Numerous AI applications in agriculture are addressed, with an emphasis on yield prediction. The article offers a comprehensive review of a variety of ML, DL and hybrid methodologies for correctly forecasting agricultural outputs that will promote the nation's economic growth.

Keywords: Artificial Intelligence, Machine Learning, Deep Learning, Agriculture, Crop Yield Prediction.