• Dr. I.Suneetha
• Shaik Rabbani
• G.Pranay Teja Reddy
• U.Sai Deepthi
• K.Tejaswi

The identification of the plant disease is crucial to obtain a good crop yield along with a good quantity of agricultural products. Detection of plant illness includes the research work of many farm-related factors such as organic farming, constant plant monitoring, and recognition of all diseases. In farms that contain entirely different crops, plant diseases cannot be tracked manually. This requires an enormous amount of work, plant disease expertise, and also a substantial amount of time. The image processing along with k-means clustering and convoluted neural networking algorithms could be used for the accurate prediction of the disease. The detection of the disease includes methods including image segregation, pre-processing data, fragmentation of the image, detection, and recognition of characteristics. This paper also examines the binding segmentation and retrieval functions of two different plant diseases.

image processing, plant disease detection, k-means clustering algorithm, Convoluted Neural Network etc.

"Detection of Plant Illness Using Machine Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.e207-e211, June-2022, Available :http://www.jetir.org/papers/JETIR2206424.pdf

"Detection of Plant Illness Using Machine Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppe207-e211, June-2022, Available at : http://www.jetir.org/papers/JETIR2206424.pdf