Abstract: Plant diseases are a major threat to agricultural productivity worldwide, hence prompt and efficient detection techniques are required. Conventional manual inspection techniques take a lot of time, require a lot of work, and are frequently subjective. This study examines the latest developments in machine learning methods for plant disease diagnosis, with an emphasis on image processing, feature extraction, and classification algorithms. The assessment addresses the obstacles and potential paths forward in this subject while highlighting the technology' ability to completely transform the treatment of plant diseases.
Index Terms: Machine Learning, Image Processing, Deep Learning, Convolutional Neural Networks (CNN), Support Vector Machines (SVM).

| DOI: 10.17148/IARJSET.2024.111111