• Rameshwar S. Devhade
• Ranjana D. Raut

Agriculture Productivity is the key component of Indian economy. Therefore the contribution of cash crops and food crops is highly important for both the environment and human beings. In India, cotton is one of the most important commercial crops cultivated. Cotton is said to be the most important cash crop in India it is also known as “White Gold” or “The King of fibers” among all cash crops in the country. The Indian textile industry uses a wide variety of fibers and yarns, with the approximately cotton to non-cotton fibers consumption ratio is 60:40. Due to crops diseases, many crops succumb to those diseases every year. It is very difficult for the human eye to identify the exact type of disease on the leaves of the crop. Many crops succumb due to insufficient diagnosis and lack of information. For agricultural improvement and growing economy of India, detection of leaf diseases of cotton is essential. Early detection of cotton leaf hoppers can increase crop yields, reduce losses and make agriculture more sustainable. Cotton disease sampling plays an important role in research to detect and classify cotton leaf diseases. It extracts various features of images. Like the color of the actual infected image, there are many diseases on the cotton leaf so the color of the leaves also varies for different diseases. Thus, in order to detect the cotton leaf diseases accurately, the use of image processes, machine learning and deep learning techniques can be helpful. The main goal of this paper is to detection and classification of cotton leaf diseases. The cotton crops leaves images are collected from cotton fields using a digital camera/smart phone. Various pre-processing techniques as filtering, background removal, segmentation and enhancement are done. Classification based on selecting appropriate features such as color, shape and texture of images done by using CNN classifier techniques.

Keywords- Cotton, Leaf diseases, Image pre-processing, filter, Image segmentation, Machine learning, deep learning, detection, classification etc.

"Cotton Leaf Diseases Detection and Classification using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 12, page no.a711-a723, December-2024, Available :http://www.jetir.org/papers/JETIR2412064.pdf

"Cotton Leaf Diseases Detection and Classification using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 12, page no. ppa711-a723, December-2024, Available at : http://www.jetir.org/papers/JETIR2412064.pdf