Diseases of Sugar Cane and Diseases Classification: The Review

Sugarcane's importance in India stems from its role as a vital cash crop providing raw materials for a large agro-based industry, generating significant employment and income for farmers and laborers, and contributing to the national economy through sugar, jaggery, and ethanol production. As the source of the second-largest agro-based industry after textiles, it supports rural economies, offers export potential, and contributes to India's goal of producing bio-fuels and saving foreign exchange by reducing crude oil imports through ethanol blending. The productivity and quality of sugarcane, a crucial commodity for the world's sugar industry, are greatly impacted by a number of illnesses. Effective management and prevention methods depend on fast and accurate disease detection. To find problems like rust, red rot, mosaic, wilt, and ratoon stunting disease, sugarcane disease detection uses both conventional visual examination and contemporary machine learning (ML) approaches, especially deep learning for image analysis. Deep learning (DL) models, trained on images of diseased leaves, can predict diseases with high accuracy (e.g., 96%), enabling farmers to take timely action using mobile applications to mitigate losses.