Identification of Diseases in Rice Plant Using Machine Learning and Deep Learning

Rice is one of the primary staple foods globally, contributing significantly to the sustenance of millions. However, rice production faces substantial challenges due to various diseases that afflict the crop, leading to yield losses and economic repercussions. Effective farming strategies depend on the early detection and precise identification of these disorders. The nine most significant diseases that affect rice plants such as rice yellow mottle virus, rice blast, brown spot, sheath blight, sheath rot, leaf scald, false smut, kernel smut and grain rot are examined in this survey. Machine learning and deep learning algorithms have been favored for identifying certain disorders, and they have been compared using various factors.