IJFANS International Journal of Food and Nutritional Sciences

ISSN PRINT 2319 1775 Online 2320-7876

Iot And Machine Learning Based Effective Plant Disease Classification And Detection For Agricultural Applications

Main Article Content

Kusuma Praveen Kumar, Barinderjit Singh, Malini K V, Arti Ranjan, Shailejkumar D Bonde, Sandeep Rout, Firos A

Abstract

Plant diseases are a key source of diminished productivity and farmer income. Researchers are now working to develop a mechanism for automatically detecting plant disease. A number of plant disease identification studies are under ongoing. Plant disease diagnosis may help farmers not only increase yields but also promote a variety of agricultural approaches. Using machine-learning algorithms, this study aims to develop a novel technique for forecasting plant illnesses. Following the detection and recording of the infected zone, image pre-processing is carried out. Following that, the pieces are gathered, the infected location is recognised, and feature extraction is carried out. Accurate plant disease identification may assist in the fast finding of a treatment to reduce loss. The results of the tests imply that plant diseases might be diagnosed and prevented earlier.

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