k.venkata rama krishna goud, J.Aravinda chary, k.venkatesh, J.Bharath, sk.nageena,

Abstract

A country's productive innovation is tied to its agriculture sector. Agriculture, the "mother" of all human societies, is the source of food and building materials. We rely heavily on it as a food source, thus its importance cannot be overstated. As a result, plant diseases pose a serious challenge to society. Pests and diseases affecting plants might occur at any moment. It's possible for this to occur between planting and harvesting. The market's economic worth has dropped significantly as a result. Consequently, the ability to identify leaf diseases is crucial in the agricultural industry. Thus, conventional approaches were utilized for illness detection. However, conventional leaf disease diagnosis relies only on the trained eyes of agriculturalists and plant pathologists. Using this approach for disease detection in plant leaves was labor intensive, time consuming, expensive, and needed a deep understanding of plant pathogens. Software solutions that have been evaluated ex