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1 min readAI System Achieves 95% Accuracy in Identifying Crop Diseases
Our computer vision model can now identify 50 common crop diseases from smartphone photos, enabling faster diagnosis and treatment.
Bringing AI to the Field
After months of development and training on millions of images, our crop disease detection AI has achieved 95% accuracy in identifying common agricultural diseases affecting Nigerian crops.
How It Works
Farmers simply take a photo of an affected plant using our mobile app. The image is analyzed by our AI model, which identifies the disease and provides:
- Disease identification with confidence score
- Description of the disease and its causes
- Recommended treatment options
- Preventive measures for future seasons
- Nearby agro-dealers with relevant products
Diseases Covered
Our system currently covers 50 diseases across major Nigerian crops including:
- Maize: Fall armyworm, rust, leaf blight
- Rice: Blast, brown spot, bacterial leaf blight
- Cassava: Mosaic virus, bacterial blight, anthracnose
- Tomato: Early blight, late blight, leaf mold
- Cocoa: Black pod, swollen shoot virus
Offline Capability
The AI model runs directly on the farmer's phone, meaning it works without internet connectivity. This is crucial for farmers in rural areas with limited network access.
"Early disease detection can save entire harvests. By putting this technology in farmers' pockets, we're giving them the ability to act fast when problems arise."