AI-based crop disease detection using machine learning
Applicant: Rwanda AgriTech Research Group
Institution: National Agricultural Research Centre
1. Objectives
The project proposes a machine-learning system to identify common crop diseases from field images and provide early alerts to extension workers and farmers.
2. Methodology
The proposed approach combines machine learning models trained on annotated maize leaf images with a mobile-assisted field data collection workflow.
3. Expected Outcomes
A validated prototype, an annotated image dataset, field deployment guidance, and training materials for agricultural extension teams.
4. Workplan
Data collection and annotation will precede model development, field validation, and deployment preparation.
5. Budget
Personnel, data collection, compute, field validation, training, and project administration are included in the proposed budget.