Intelligence Blight Damage Estimator for Yield Prediction

Abstract Crop diseases are one of the major factors that reduce agricultural productivity worldwide. Among these diseases, blight significantly affects plant health and leads to considerable yield loss. Early detection and accurate estimation of blight damage are essential for farmers to take timely preventive measures and improve crop productivity. This paper proposes an intelligent system for estimating blight disease damage and predicting crop yield using machine learning and image analysis techniques. The system analyses images of plant leaves to detect blight symptoms and estimate the severity of damage. By combining disease detection with predictive analytics, the proposed framework provides insights into potential crop yield reduction. The system aims to assist farmers in making informed decisions regarding crop management, pesticide usage, and disease prevention. Keywords: Blight Disease, Crop Yield Prediction, Machine Learning, Image Processing, Smart Agriculture.