Now AI Will Diagnose Crop Diseases: IIIT Kota Scientists Develop Indigenous Technology

To solve the challenge of farmers struggling with inaccurate disease identification and excessive pesticide use, scientists at IIIT Kota—led by Dr. Rajendra Kachhwaha—have developed a lightweight, fast AI model based on LS-CNN (Light Separable Convolutional Neural Network).

Key Highlights:
- How It Works: Farmers simply upload a photo of a suspicious crop leaf via an Android app. The AI analyzes patterns and colors to diagnose diseases with about 95% accuracy in seconds, even working offline in many scenarios.
- Current Scope: Initially trained on over 1,600 images across 27 fields, the app currently detects 7 major cabbage diseases (such as Black Rot, Downy Mildew, Alternaria Leaf Spot, etc.). Future updates will expand to tomatoes, potatoes, wheat, and mustard.
- Key Features: The app will be completely free for farmers, available in multiple Indian languages with simple terminology, and eventually integrate with drones for targeted pesticide spraying.
- International Recognition: The research has been published in the prestigious Springer Nature journal, and Dr. Kachhwaha was invited to present the innovation at a global summit in the Netherlands.