KRISHI MAITHRI

Abstract

This research paper endeavors to present a comprehensive review of machine learning (ML) applications in agriculture, with a particular emphasis on developing content for an agriculture-oriented website. The integration of ML techniques in agriculture has the potential to transform farming practices, augment productivity, and address challenges related to crop management, pest control, and resource optimization. This paper explores diverse ML algorithms and models applied in agriculture and highlights their impact on crop yield prediction, disease detection, precision farming, and sustainability. The goal is to create informative and engaging content for an agriculture website that caters to farmers, researchers, and industry professionals, promoting the adoption of ML technologies for sustainable and efficient farming practices.

To aid farmers and improve the agriculture sector, we sought to design and develop a web-based application that contains all the necessary information required for the sustainable growth of crops. Our team employed HTML5, CSS, JavaScript, and Bootstrap to develop this web-based application. Furthermore, we utilized the PHP framework to administer the MySQL database and Machine Learning Algorithms