Al-Powered Approaches for Image-Based Wheat Disease Identification in Smart Agriculture

Agricultural productivity depends a lot on finding plant diseases early because they can greatly reduce crop yield and affect food supply. Wheat, which is one of the most important crops, can get diseases like rust, blight, and mildew. Often, these diseases are noticed only after they have already caused serious damage. Traditional methods to detect these diseases take a lot of time, need expert knowledge, and can sometimes be unreliable. This study focuses on finding faster and better ways to detect wheat diseases using images of wheat leaves. By carefully examining these images, it is possible to identify signs of disease and understand how they affect the plants. Using such methods can help monitor crops in real time, reduce the need for manual checking, and support farmers to make better decisions. This approach shows good results and can help improve wheat production, make farming more efficient, and protect food resources.