Ugochi Okengwu

The ?AI Solutions for Multi-Crop Leaf Disease Detection in Africa? project is designed to help farmers quickly identify and manage plant diseases across multiple crop types using artificial intelligence. Crop diseases are a major cause of yield loss in Sub-Saharan Africa, affecting food security, rural livelihoods, and national economies. Traditional detection methods are slow, require expert knowledge, and are often inaccessible to smallholder farmers. Our innovation uses a trained AI model capable of recognizing and classifying leaf diseases in crops such as Tomatoes, Sweet Potatoes, Cabbage & Pepper with high accuracy. Farmers or extension workers can take a photo of a crop leaf using a smartphone, and the system instantly provides the diagnosis along with recommended treatment options and preventive measures. This technology not only helps reduce crop losses but also promotes sustainable agricultural practices by minimizing unnecessary pesticide use and enabling targeted interventions. Its design ensures accessibility for women farmers, people with disabilities, and underserved rural communities, thereby supporting inclusive growth. The solution is already in early deployment, with successful pilot tests in selected farming cooperatives. Scaling will involve extending the crop database, integrating local languages, and partnering with agricultural extension networks across Africa. With the potential to serve millions of farmers, this innovation will strengthen agricultural resilience, enhance productivity, and contribute to Africa?s broader food security and climate sustainability goals.