Foliar Disease Classification in Apple Trees

Apple is commercially the most important temperate fruit and is third among the most widely produced fruits in the world. Jammu and Kashmir are one of the leading apple producers accounting for about 60% of production in our country and Himachal Pradesh apple accounts for about 90% of horticulture production. The diseases like apple scab, apple rust, and brown rot affect apple trees. During wet cool weather between 55- and 75-degrees Fahrenheit in the spring and early summer, the fungal spores are dispersed by wind and rain. Apple scab is the most important disease of apple which results in a 70% yield loss or even more if not managed properly. Currently, crop disease diagnosis mainly relies on farmer scouting, which is time-consuming, expensive, and ineffective due to the difference in diagnosing experience. The proposed method uses Deep Learning algorithms like VGG16, Dense Net121 and ResNetlS to classify images into four classes healthy leaves, apple scab leaves, apple rust leaves, and multiple diseases leaves. Model performance is evaluated by comparing the prediction accuracy and confusion matrix and finds the best model for this classification