Title:   A Review on Machine Learning Techniques Used in Modern Agricultures

Authors: Dr. K. Murugan, Assistant Professor, Department of Computer Science, Government First Grade College, K R Puram, Bangalore

Abstract: Agriculture plays a very pivotal role in the global economy of the country. Due to the growth in population, there is constant pressure on the agricultural system to increase the productivity of the crops and to grow additional crops. Machine Learning (ML) is a trending technology nowadays and it can be used in modern agriculture production. The use of machine learning in agriculture helps to create well seeds and produce more crops. Machine learning has developed together with big data technologies and high-performance computing to create new opportunities to unravel, quantify and understand data intensive progressions in agricultural environments. Machine learning is a tool for revolving information into knowledge. It is one of the most significant and powerful technologies in today’s world. Machine Learning is becoming part of the engine behind it, continuously learning and improving from every interaction. A number of relevant papers are presented that emphasize key and unique features of popular ML models. In this paper discuss the concept of ML algorithms used in agriculture. The results obtained in this paper are useful for farmers to make decisions to develop agriculture in advance for further implantation.

Keywords:  Machine Learning, Agriculture, Quality, Deduction, Classification

DOI: 10.5281/zenodo.8140412

International Journal of Applied Pattern Recognition, 2023 Vol.7 No.3, pp.189 - 193

Received: 20 Dec 2022
Accepted: 24 March 2023
Published online: 27 June 2023