UENR is developing an AI application for crop disease detection

When completed, the app will detect diseases of four crops – maize, cassava, cashew and tomato, said Dr. Patrick Kwabena-Mensah, senior lecturer in the department and principal investigator of the Artificial Intelligence for Agriculture and Food Systems (AI4AFS) project at UENR. In an interview with Ghanaian News Agency in Sunyani.

Dr Mensah said the project is being funded by the Kenya-based International Development Research Center (IDRC) which is also providing funding from Canada and is expected to be completed within 18 months, six months already.

The app is currently in the development phase, he said and said that by July this year the team had finished development and then engaged farmers around September to train them on how the app would work.

Turning to the application methods, Dr. Mensah explained that the photos of the four selected crops will be taken, where the diseased and healthy parts of the plant will be taken and then trained as a model for artificial intelligence, which will then be developed into a mobile application and then installed on the android phone and the iPhone operating system (IOS). ).

He also said that a web application will be developed and a farmer who has access to a computer must cut a leaf from a sick crop, with the help of the computer’s webcam, the AI ​​application can detect what kind of diseases are on the computer.

Using a mobile phone, a farmer on the farm who realizes that a crop is infected or has had an unusual appearance, Dr. Mensah said, “should take a picture of that part and the app will identify the diseases affecting the crop as well as prescribe environmentally friendly recommendations on how to control a particular disease.”

He said that the team realized that most of the farmers either do not have phones or computers or their phones are not running Android/IOS, thus as part of the project, “E-kiosk” will be set up in five communities in the pilot phase.

He said the “electronic kiosk” would consist of either a computer, a mobile phone and an attendant to help farmers who do not have these tools to detect diseases from their affected crops.

Dr. Mensah said that the application when running will help boost crop production as it will ensure early detection of pests and diseases on farms and give preventive controls to mitigate crop losses.