Leaf Disease Detection Using Machine Learning Algorithm
T. Priyaradhikadevi, R. Mohan, T. Ragupathi, S. Prasanna, K. Madhan, R. Ananthi
Abstract
Agriculture plays a significant part in a developing country like India. Agricultural intervention in rural India's livelihood accounts for around 58% of the total. The production of the crop is affected by different diseases in plants. Plant diseases are one source of obstructing plant quality and productivity, leading to a food supply crisis. As a result, the classification of plant diseases is critical in the agriculture industry. Early detection of the plant disease may reduce crop yield loss; hence, in this system, image processing, and machine learning algorithm is used to classify the plant leaf disease recognition is presented. This system uses the Plant Village dataset, which comprises apple, corn, grape, and tomato plant leaves with healthy and diseased categories. The texture and shape features are extracted from the plant leaf and classified using a decision tree and Gradient boosting algorithm. The performance of the system is evaluated using the accuracy parameter.