Rice Leaf Disease Detection and Selection of Fertilizer Using IOT

Abstract

The project aims to develop a system that can detect rice plant diseases and recommend suitable fertilizers using image processing techniques. The system uses MATLAB as the primary programming language to analyze images of rice plant leaves to identify any visible symptoms of diseases. Based on the identified disease, the system recommends the most appropriate fertilizer to treat the affected plant. The proposed system will provide an efficient and accurate approach to detecting and treating rice plant diseases, thus ensuring increased crop productivity and better yield.