International Journal of Science, Engineering and TechnologyAuthors: Prof. C. P. Lachake Girish Khamkar, Kishor Handge, Aryan Kakade, Siddhant Gadkari
Abstract: Nowadays in India Cotton is considered one of the most important cash crops i.e. White Gold, as most farmers cultivate cotton in large numbers. Agriculture plays a vital role in the economic development of our country. Farmers face various challenges due to unexpected weather changes and plant diseases that reduce crop yield and quality. Cotton, one of the major cash crops, is highly affected by leaf diseases, which are often difficult to detect at an early stage using manual methods. To overcome this issue, the proposed system focuses on automating the detection and classification of cotton leaf diseases using image processing and machine learning techniques. In this project, images of cotton leaves are captured and processed to identify disease symptoms such as color variation, texture, and shape. Using trained machine learning models, the system can accurately classify the type of disease and provide information about suitable remedies or preventive measures.
