Kazibwe Edward, a farmer from Mpigi District in Central Uganda, has been growing the Robusta coffee variety for the last ten years, and since then, he has never known a reliable solution to one of the cash crop's seemingly unending problems—diseases.
To Mr. Kazibwe and many other farmers in Mpigi, coffee remains the crop that powers their lives. Its existence is as good as theirs, and its thriving means better lives for the people and the economy of Uganda.
The industry has, however, suffered a major setback for a lack of proper ways to deal with the problem of diseases, such as coffee leaf rust, black rot, brown eye spot disease, berry blotch, and root diseases, which have frustrated farmers' yields and rendered the enterprise almost profitless.
Berry blotch caused by Cercospora infection [Photo-PlantVillage]
The Coffee AI Model in the Nuru App
The Cultiva Dream Team, a PlantVillage unit in Uganda that brings together youths with knowledge and skills in agriculture, has been working around the clock to advance an artificial intelligence program already incorporated into the PlantVillage Nuru app, called the Coffe AI model.
The team, which operates in Mpigi, Kalungu, and Masaka districts, has been collecting different images of infected and healthy coffee leaves and berries for the purpose of advancing the system in disease identification.
The Nuru App, through a set of simple procedures, scans, diagnoses, and detects disease and pest infections on crops and has been efficiently working to help maize, potato, and cassava farmers in Kenya.
Cultiva Dream Team Uganda research extension officer, Owamaani Promise, shows a farmer how to scan for diseases in coffee using the Nuru app [Photo-Cultiva Dream Team]
Just like the mentioned plants, a survey is carried out on a coffee plant, and the incorporated AI program scans, diagnoses, and detects infections on the crop.
From the latest advancements, the AI program can detect coffee leaf and coffee red blister, which are the major issues for coffee production in Uganda.
Coffee red blister disease [Photo-Cultiva Dream Team]
When carrying out this survey, three unhealthy leaves are scanned separately on the undersides, and if infected, leaf rust will be detected. If the plant doesn't have berries, the survey will end and management practices on how to control the disease will be given.
If the plant has berries, after scanning the three leaves, the extension officer or farmer separately scans three branches for unhealthy berries. The red blister disease will be detected if the berries are infected.
At the end of the process, management practices for disease(s) control will be provided. This will give the farmer instant feedback.
The Nuru App and the Future of Coffee Growing in Uganda
The Cultiva Dream Team is looking forward to modifying this AI model to detect more diseases, including brown eye spots, as well as pests such as coffee twig borer, berry borer, and stem borer, which are increasingly becoming a threat.
The technology in the Nuru app has already been taken up by Ugandan farmers, who have learned how to simply download it from the Google Playstore and execute the functions.
"This Coffee AI is what I have been waiting for. It is going to be a real-time solution to diseases affecting my coffee," Kazibwe Edward says while navigating the app.
The brazen technology has not only been embraced by farmers but also by agricultural experts who have commended its human-friendliness.
"My work as an extension officer will be simplified as farmers will adapt to this technology, which will increase their production," Namare Joan, a government extension officer, says.
- Written by Promise Owamaani