• Gyan Prakash Pandey
• Dr. Harish Taluja
• Gaurav Shishodia
• Ansh Shukla
• Ansh Tyagi,Gaurav Sharma

—India is one of the largest producers of wheat in the world, with agriculture forming the backbone of its economy. Over 60% of India’s population relies on agriculture for their livelihood, and wheat is one of the most important crops grown across the country. In 2023, India produced over 100 million metric tons of wheat, making it the second-largest producer globally, just behind China. However, wheat crops in India are often vulnerable to various diseases such as rust, blight, and powdery mildew, which can lead to significant yield losses if not detected early. This research introduces an advanced system using Convolutional Neural Networks (CNNs) to detect wheat diseases by analysing images of wheat leaves. The system processes over 10,000 images of wheat plants, identifying 12+ types of diseases with an accuracy of 98.85%. It also incorporates environmental factors like temperature, humidity, and location, allowing for region-specific disease predictions. With the rise of climate change and unpredictable weather patterns, this system provides a valuable tool for Indian farmers, helping them manage crops more efficiently and reduce the use of pesticides. By enabling early detection, the platform assists in minimizing crop loss and increasing wheat production, thus improving the income of millions of farmers in India. This research aims to transform wheat disease management, enhancing both productivity and sustainability for Indian agriculture.

Wheat Disease Classification, Crop Management, Disease Detection, Early Detection, Indian Agriculture, Image Processing, AI in Farming.

"DISEASE CLASSIFICATION IN WHEAT FROM IMAGE USING CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.a366-a371, May-2025, Available :http://www.jetir.org/papers/JETIR2505035.pdf

"DISEASE CLASSIFICATION IN WHEAT FROM IMAGE USING CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppa366-a371, May-2025, Available at : http://www.jetir.org/papers/JETIR2505035.pdf