Leaf Disease Detection and Classification by Decision Tree

Abstract

Agricultural productivity is very dependent on the economy. Plant diseases play an important role in agriculture because plant diseases are very natural and failure to care will have serious consequences for plants and therefore affect the quality, quantity, or productivity of the product. Timely and accurate diagnosis of leaf diseases plays a major part in preventing loss in productivity and loss or reduction of agricultural products. Detection of plant diseases by automated techniques is beneficial because it reduces monitoring efforts on large plants and detects an indication of disease which occurs when they came on the leaves of plants very early. More researchers have proposed leaf disease detection techniques. The existing systems have less detection accuracy. This proposed system uses a decision tree to identify and classify leaf disease and increases its detection accuracy with less time compared with the existing system.