• Arepalli Peda Gopi
• Dr.P.Radhika
• Nagulapally Bhargavi
• Chiratanagandla Pavani
• Muppalla Bhanusri , Gurrapusala Gayathri

Agriculture is an ultimate necessity on the same note it is main source that offers domestic income to many countries around the world. Diseases affecting plants from different pathogens such as viruses, fungi or bacteria are costly to agriculture around the world in terms of losses as indicated below. In the same regard we consider applications from a genomics physiology biochemistry perspective among others. Amongst all the crops that are cultivated in India the rice crop is said to be a major crop that is vulnerable to several diseases in its growth cycle at one time or another. Manual diagnosis of these diseases by farmers is not easy because they do not have the capacity to diagnose them without training. This is why disease identification and treatment of the infected specimens is imperative in order to get to a normal and healthy point of rice plants. In the modern world, disease detection especially on the leaves is very crucial in today’s topic of agriculture. Our algorithm also has the ability to diagnose diseases on rice leaves. Our goal in this study will be to perform classification of disease images in rice leaves with complex backgrounds and different lighting conditions. Using the CNNs based model on the data set acquired from Kaggle, it gives us the accuracy level of 98%. The results of disease identification in rice indicate how useful the proposed method is. Diagnosis of diseases, CNN algorithm, rice leaf, and machine learning are keywords. Rice diseases automatic detection and analysis are needed by the farming industry in order to minimize the wastage of the financial and other valuable resources, reduction of yield loss, increase processing efficiency and attainment of healthy crop yield.

Rice leaf,Convolutional Neural Networks(CNN),Disease Detection,DeepLearning

"RICE PLANT LEAF DISEASE DETECTION USING AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.261-268, October-2024, Available :http://www.jetir.org/papers/JETIRGN06030.pdf

"RICE PLANT LEAF DISEASE DETECTION USING AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. pp261-268, October-2024, Available at : http://www.jetir.org/papers/JETIRGN06030.pdf