Banalytic, early warning system to combat black sigatoka in banana plantations

AI-powered pest and disease recognition

Project Partners: UK Agri Tech Centre, Embrapa Environment, Aya Data and Lacuna Space Ltd

This project will develop an Early Warning System (EWS) to combat Black Sigatoka, a devastating fungal disease affecting banana plantations globally, and specifically in Ghana and Brazil. 

The disease can reduce yields by over 50%, threatening food security, farmer livelihoods, and environmental sustainability (JGI, 2014). Through cross-continental collaboration and advanced technology, this initiative addresses key agricultural challenges while promoting climate-smart farming practices.

The innovation builds on findings from a previous IUK-funded scoping project (DATA-BEE), which identified AI-powered pest and disease recognition, along with climate-linked forecasting, as critical tools for sustainable crop management. In response, this project will deploy a machine learning model based on Neural Ordinary Differential Equations (Neural ODEs) to predict Black Sigatoka outbreaks before symptoms appear. The model will be trained using historic agronomic and climate data from Brazil, alongside real-time sensor and satellite data collected from banana-growing regions in Ghana. A key focus will be on harmonising datasets across geographies with similar agro-climatic conditions to ensure robust comparisons and forecasting accuracy.

The resulting EWS will be deployed through a mobile application, providing farmers with real-time, location-specific infection risk alerts. This will enable timely, targeted interventions—helping reduce crop losses, lower fungicide use, and improve resilience to climate variability.

Collaboration

The project brings together a unique partnership: Embrapa (Brazil) contributes by coordinating and putting together a team—within and beyond Embrapa—dedicated to providing historical data and disease modelling expertise to support the project’s objectives; Aya Data (Ghana) leads local AI development and field validation; Lacuna Space and the UK Agri-Tech Centre provide satellite communications, data science, and coordination support.

Expected impact

Expected impacts span social, economic, environmental, and technological domains. Socially, farmers will gain access to practical, actionable insights to improve decision-making. Economically, the system will support yield protection, reduce input costs, and enhance farmer profitability. Environmentally, optimising fungicide use will improve soil health and reduce runoff. Technologically, this project pioneers a forecasting tool with potential scalability to other crops and regions.

By integrating Brazilian agricultural innovation, Ghanaian AI capability, and UK satellite data analytics, the project will advance sustainable, climate-smart agriculture. It lays the groundwork for scalable digital tools that protect crops, support livelihoods, and promote resilience in the face of climate change.

For more information

For more information on this project, contact us, or view all projects funded under the Climate-Smart Agriculture Partnership programme.

Innovate UK Climate-Smart Agriculture Partnership: UK-Brazil-Africa brings together innovative people and organisations to promote climate-smart agriculture in Africa.