An Intelligent Leaf Image–Based Plant Disease Detection and Pesticide Recommendation System Using Deep Learning

Plant diseases are one of the major reasons for reduced agricultural productivity across the world. Identifying these diseases at an early stage and applying the right treatment is essential for maintaining crop health and ensuring food security. Traditionally, disease detection depends on human observation, which can be slow, expensive, and sometimes inaccurate. In this work, we present a smart system that uses deep learning to detect plant diseases from leaf images. The model is based on Convolutional Neural Networks (CNN), which can automatically analyze images and classify plants as healthy or diseased. It also identifies the exact type of disease and explains possible causes. In addition, the system suggests suitable pesticides and calculates the required dosage based on the user’s input area. This approach not only improves accuracy but also helps farmers make better decisions while reducing unnecessary pesticide usage.