Various diseases are caused by fungi, bacteria, viruses, insects and nematodes on agricultural and horticultural crop plants. These diseases reduce the crop yield by 20 to 40 percent annually worldwide. Therefore, these pathogenic microorganisms and insect pests are major threat to sustainable agriculture. For detection recognition and classification of plant diseases, agriculture experts carry out the inspection of field crops visually or microscopically, which is time consuming and laborious. Recently, rapid detection of plant diseases is being done by image processing of disease affected leaves, roots and fruits of agriculture and horticultural crops using machine vision technology. Expert systems involving computer vision image processing (CVIP), colour co-occurrence matrix (CCM), neural network classifier, fuzzy clustering and image segmentation algorithms etc. have been developed for diagnosis of diseases and disorders in various crops. In addition, artificial intelligence, artificial neural network, Bayer’s classifier, fuzzy logic and hybrid algorithms have been found to reduce large work of disease monitoring in big farms at very early stage. Using these expert systems involving artificial intelligence and image processing, disease recognition rate and accuracy rate has been achieved upto 96.2 and 92.3 per cent, respectively. Furthermore, the development of novel computational and bioinformatics tools could help in the analysis of large biological databases related to plant diseases and their control using pesticides. The image processing system can be used as agricultural robot to inspect the field using artificial intelligence for detection, diagnosis and classification of crop disease. Thus, the use of computational and bioinformatics tools will help in minimizing the disease occurrence and severity on crop plants, which will prevent environmental pollution by reducing the quantities of pesticides applied for disease control.

Plant disease, Image processing, Artificial intelligence, Expert systems, Disease detection, Agriculture crops

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