Leaf disease detection using ensemble classification approach in machine learning.

The identification and diagnosis of plant diseases is one of the key factors in determining crop losses in crop production and agriculture. An analytical study of plant diseases is the study of any visible points in any part of a plant that help us to distinguish between two plants, technically or any dots or shades of color. Crop sustainability is one of the key factors in agricultural development. Diagnosis of plant disease requires a lot of work and expertise, a lot of knowledge in the field of plants, and research to diagnose those diseases. Therefore, image processing is used to differentiate plant diseases. Disease diagnosis follows methods for image acquisition, image removal, image classification, and pre-image processing. Leaf color, amount of damage to leaves, leaf area of the unhealthy plant is used for sorting. In this case, we reviewed the learning algorithms of the various machines to identify the leaf diseases of different plants and to determine the best accuracy. [ABSTRACT FROM AUTHOR]