Image-Based Plant Disease Prediction Using Machine Learning Techniques

Plant diseases pose a significant threat to agricultural productivity, causing economic losses and worsening food insecurity. Early and accurate detection is vital for effective management and sustainable farming. This study explores the use of machine learning to develop a reliable system for plant disease prediction. Using image processing and classification algorithms, the system analyzes leaf images to identify disease patterns with high accuracy. Convolutional Neural Networks (CNNs) and other advanced models help distinguish between healthy and diseased plants. Experimental results show the system can detect various diseases with high precision and minimal human input, aiding farmers in decision-making and improving crop health and productivity.