Crop Doctor helps smallholder farmers identify crop diseases early using AI image recognition, then guides them towards sustainable, eco-friendly treatment options — reducing chemical use and preventing avoidable crop losses.
Developed by Team Agrivision at the Green Tech Hackathon 2025, Crop Doctor tackles one of the most persistent threats to food security in East Africa: crop disease. Smallholder farmers often lack access to the agronomic expertise needed to correctly diagnose plant diseases, leading to delayed treatment, crop losses, and overuse of broad-spectrum chemicals.
The application allows a farmer to photograph a diseased plant with their smartphone. The AI model — trained on a diverse dataset of common Kenyan crop diseases — analyses the image, identifies the likely pathogen or deficiency, and returns a diagnosis within seconds, complete with confidence score and visual explanation.
Critically, every treatment recommendation prioritises eco-friendly and organic options first. Only where these are insufficient does the system suggest controlled chemical interventions, always with usage guidance to prevent overuse or contamination.
The prototype demonstrated strong accuracy on the validation dataset prepared by the team, and received positive feedback from the hackathon judges for its direct relevance to the Kenyan agricultural context and its focus on sustainable farming practice.