AI tool helps Ghanaian farmers identify crop threats from field observations

For a farmer, a yellow spot on a tomato leaf may seem insignificant. But that small change could be an early sign of a disease or pest infestation that, if not identified and addressed quickly, could spread across a farm and threaten an entire harvest. The challenge is that many farmers rely largely on experience to determine what may be affecting their crops.

By the time the cause becomes clear, significant damage may already have occurred. Changing weather and climate conditions are adding another layer of uncertainty, influencing pest behaviour and creating conditions that can favour outbreaks. It is against this backdrop that a Ghanaian researcher has developed an artificial intelligence technology designed to help farmers identify crop threats from what they observe in the field.

Known as Ndua Analytics, the platform was developed by University of Ghana Research Assistant and YARA Research Fellow, Nana Benyin Eboe Nyamekye Essel-Biney. Rather than requiring farmers to have specialised agricultural knowledge, the system allows them to describe what they are seeing on their crops and receive a possible diagnosis. “I implemented my few-shot learning model into a web application which is able to take in observations from farmers on the condition of their crops from what they see, and the system is able to diagnose the crops to give it what is wrong, the disease or the pests that’s wrong with it,” he explained.

Ndua Analytics is currently being piloted on maize, cassava and tomatoes. A farmer who notices yellow spots on tomato leaves, for example, can select tomatoes on the platform and enter the symptoms observed. The system analyses the information and generates a possible diagnosis before providing recommendations on treatment, prevention and longer-term management.

The developer has also incorporated language accessibility into the platform for farmers who may struggle with technical agricultural terms or English. The system uses speech and translation technology to provide responses in English and a local Ghanaian language, with different voice settings also available. “In case the farmers cannot read or understand the English, if it’s in [the local language], it will be easier for them to have an idea what to do and what is wrong,” Nana Essel-Biney said.

Unlike several agricultural AI tools that depend heavily on images, Ndua Analytics currently does …