Crop Disease Detector

  • March 28, 2024
  • Godfrey Naman
  • 0

Research Problem

  • Crop diseases pose major threats to income and food security for smallholder farmers in Africa.
  • Traditional diagnosis relies on visual symptoms on leaves, stems, and other plant parts, leading to challenges such as: Late diagnosis beyond recovery, High management and control costs, Significant or total crop loss.

Findings

  • The project successfully developed a mobile application that utilizes machine learning models to detect diseases in maize and banana crops based on leaf image data.
  • The project created the publicly available datasets for maize and banana crops.
  • The machine learning models demonstrated high accuracy in detecting specific diseases affecting maize and banana crops, allowing for early diagnosis and intervention.
  • The mobile application was designed with a user-friendly interface, making it accessible and easy to use for smallholder farmers and other stakeholders in agriculture.

Impact

  • The application enables farmers to make timely and informed decisions regarding disease management, potentially reducing the spread of diseases and minimizing crop losses.
  • The project facilitated knowledge sharing among farmers, agricultural extension officers, and other stakeholders, promoting best practices in disease detection and management.
  • The application has the potential for scalability and adaptability to other crops and regions, indicating its usefulness in broader agricultural contexts.

Research Credits

Published Research

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