ML Algorithm-Based Detection of Leaf Diseases

In day-to-day life, while the plant is important for every human being to get rich vitamins of vegetables, the plant disease rate is increasing proportionally. The disease on the plant causes severe suffering to farmers economically. So, the plant disease is either to be controlled or predicted before it leads to big damages. To solve this issue, machine learning algorithms have been proposed to analyze the root causes of the disease and to prescribe suitable pesticides to cure the plant. Though many methods have been encountered to detect the disease of a crop, the existing methods failed to give accurate results. While many existing methods failed to apply image processing techniques and databases to store the crop data, the proposed CNN algorithm adopted these features by creating web applications to know the different types of disease that have occurred on the plant. The result witnesses that the proposed algorithms have shown improved accuracy (93.3%) which helps the farmer to raise the productivity of a crop. The developed app also helps young farmers to read and select suitable image options to improve the good yielding of their agriculture.