Pomegranate is one of Tunisia’s highest-value tree crops and an important source of income for smallholders. Yet many decisions – from irrigation and fertilisation to pest management and harvest timing – still rely largely on field experience rather than on continuously recorded data.
BRIDGE-IA‘s Tunisian pilot, led by the University of Sousse, is working to connect that local expertise with a structured evidence base.
Between June and August 2026, the team carried out field campaigns at the Sousse pilot site and worked with 22 growers through a farmer-centred protocol designed to gather real-world data on orchard management practices.
The campaign documented orchard structures, irrigation systems, crop conditions and management practices. The team has also established the site’s soil typology and consolidated historical records for the area, creating a baseline dataset that can already support analysis while the monitoring system is being prepared.
Monitoring equipment has been identified and ordered. Once installed, it will record air temperature, humidity and atmospheric pressure, together with soil moisture and temperature at different depths. High-resolution satellite imagery is also planned as an additional layer of information.
These sources will be combined into a harmonised multimodal dataset for pomegranate cultivation, feeding BRIDGE-AI’s GenAI-based decision-support tools. The aim is to co-design tools with growers around practical questions such as irrigation, fertilisation and pest management, and then validate them under real orchard conditions.
The pilot is also designed to make the resulting data and services FAIR and interoperable, supporting transfer to other tree-crop systems in Tunisia and comparison with BRIDGE-AI’s use cases in Kenya and Nigeria.
With the first field campaign completed, Sousse now has the data foundation needed to move towards more informed, locally grounded orchard management.
