Abstract

In general, the paddy blight affects all plant parts above ground. The effects of the disease shown in leaves, bark, node, neck, part of rays, and sometimes leaves sheath. The leaves are pale yellow to pale green with sharp tips, with eye-shaped lesions. The margins of these fractures are distorted and its center is gray or white. The extent of degeneration depends on the age of the crop, the time of disease onset and their type. As these lesions grow, the leaves gradually dry out. If the area where the leaves and sheaths join is affected, rot will appear on the neck and the leaves above the junction will die. The ankle will also be affected. It forms brown nodules and the stems may break off, occasionally dying throughout the nursery and young crops. In this paper, a disease detection machine learning approach was demonstrated. In this algorithm analyze the different changes in paddy leavess and link with the existing paddy images. Based on that this will identify the issues and provides the treatment details accordingly.