A Systematic Analysis of Deep Learning and Machine Learning Methods for Identifying Apple Leaf Disease

In a nation like India, where so many people rely on farming for their survival, agriculture is crucial to the nation’s progress. Apple manufacturing loses a significant annual sum due to losses caused by illnesses and pests. Agricultural workers sometimes have trouble telling apple diseases apart since their symptoms overlap and are often quite similar. To address these issues, the use of Leaf Disease Prediction in apple agriculture has become more relevant. In this study, the epidemiology, pathogenesis, and consequences of a wide range of apple plant diseases using Machine Learning (ML) and Deep Learning (DL) was examined. Researchers found that automated disease detection and categorization methods for apple trees are in their early stages of development. To prevent financial ruin and maximize fruit yield, farmers need a new, more effective frameworks for recognizing and categorizing apple plant leaf maladies.