The AI solution aim to solve the early detection of Black Sigatoka and Fusarium Wilt in Banana

Diseases like Fusarium Wilt and Black Sigatoka affect the banana plant and lead to a decrease in plant yields. Most local banana farmers use simple naked-eye observation done by the farmers themselves and the agricultural experts to detect the presence of diseases on the plants, which is cumbersome, costly, prone to errors, and time-consuming. The current state of plant disease diagnosis is transitioning from disease identification using visible symptoms by the eyes to the use of automatic, data-driven solutions applying deep learning and computer vision techniques, which are easier and cheaper. 

If the problem is not addressed crucial management steps will not be taken to mitigate or avoid the effects of Black Sigatoka and Fusarium Wilt banana diseases early and this will result in great yield losses between 30% to 100% of banana fruits.

The AI solution addresses the early detection of Black Sigatoka and Fusarium Wilt banana diseases from their symptoms seen on the images of banana leaves and stalks.

The symptoms of Black Sigatoka banana disease are small, pale-yellow spots on young banana leaves, which enlarge, turn brown, and have light gray centers within days with yellowed surrounding tissue. 

The symptoms of Fusarium Wilt include wilting and yellowing older leaves, followed by new ones. As the disease progresses, the yellowed leaves collapse, forming a dead leaf covering around the pseudostem. This continues until all leaves fall and dry up, leading to a dead plant. Splitting of the pseudostem’s base is another common sign. 

Most local banana farmers use simple naked-eye observation done by the farmers themselves and the agricultural experts to detect the presence of diseases on the plants, which is cumbersome, costly, prone to errors, and time-consuming. 

The AI tool aim to improve outcomes by automating the detection of Black Sigatoka and Fusarium Wilt banana diseases.

Based on the report by the Food and Agricultural Organization Statistics, in 2021 the annual global production of bananas was 124 million tons, and 54.4% of these tones were produced in Asia, with India leading by producing 33 million tons and Africa producing 22 million tons which is equivalent to 22.7% of the global production.

In Tanzania, a total of 20 735 banana-growing smallholder farmers were reported to have banana disease occurrences in 2011.

In Tanzania, a total of 20 735 banana-growing smallholder farmers were reported to have banana disease occurrences in 2011.

The purpose of the AI tool is to automate the early detection of Black Sigatoka and Fusarium Wilt banana diseases. 

The AI tool was developed as part of a university research.

Deep learning technology is used in the development of the tool.

Images of banana leaves and stalks collected from the farms in Arusha, Mbeya, Kagera, Kilimanjaro, and Dar es Salaam regions of Tanzania were used to train the AI tool.

The data was annotated using LabelMe software. 

The AI tool is a mobile application that can capture an image using the phone camera or upload images from the gallery. After the image is captured or uploaded it is sent to the server to be detected by the model if it is a healthy banana leaf image, an image of a banana leaf affected by Black Sigatoka disease, an image of a banana leaf or stalk affected by Fusarium Wilt disease, or if the image is not of the banana plant. After a few seconds, the result is sent from the server to the mobile application with the class of the image and the confidence score of the model’s prediction. From these results the farmer will be informed if his banana plant is healthy or if it has one of the two diseases. Then if a disease is detected recommendations for mitigating the effects of the diseases on the farms are provided. 

From the application the farmer can read information about banana, about Black Sigatoka and Fusarium Wilt banana diseases and the farmer can also change the language between English and Swahili which are supported by the application. 

Farmers are the primary users of the tool.

The input data required are the images of banana leaves or stalks.

The output provided by the tool is the predicted class and the model’s prediction confidence score.

Yes. The tool provides recommendations for mitigating the effects of Black Sigatoka and Fusarium Wilt banana diseases. For example fungicides and ways to avoid the spreading to the diseases.

The AI tool improve efficiency compared to traditional methods by making prediction bases on experiences or examples of tens of thousands of labelled images. The AI tool is also cheaper compared to the costs of hiring agricultural experts. 

The AI tool can detect the presence of absence of diseases in less than 5 seconds.

The model was deployed in a server and can allow concurrent users from the mobile applications.

Yes

The application is not in play store yet. 

No there are no guidelines for documentation provided for using the tool.

The AI tool is not always accurate

No recommendations

Not available

The AI tool is not always accurate

Images of plants with similar symptoms from different causes may be predicted to have one of the two detected diseases.

How can the AI tool’s accuracy be improved?

No discrepancies exist

By the number of correct predictions it provides compared to the decisions of agricultural experts

Practical applications of the AI tool are

Disease detection and mitigation

By detecting Fusarium Wilt banana disease, the tool can support decisions to start plantation in a new field because Fusarium Wilt is caused by a soil-borne fungus

By diagnosing many banana plants in an area using the tool, decisions can be made about the extent of the disease in an area and what collective measures can be taken to mitigate the effects of those diseases

Benefits offered by the AI solution to target communities are:

Cost reduction

Ease of use

Yes, there are scalability opportunities for the tool across other regions and other plant diseases

There are no long-term goals for the AI tool.

There are no additional features or upgrades planned.

Partnerships or collaborations can help to improve the tool and increase its accuracy hence enhancing its impact.