{"id":5846,"date":"2026-10-19T23:59:50","date_gmt":"2026-10-19T21:59:50","guid":{"rendered":"https:\/\/bridge-project.ai\/post-2022-14\/"},"modified":"2026-10-20T11:41:35","modified_gmt":"2026-10-20T09:41:35","slug":"pomegranate-farming-tunisia","status":"publish","type":"post","link":"https:\/\/bridge-project.ai\/yo\/pomegranate-farming-tunisia\/","title":{"rendered":"BRIDGE-AI builds a data foundation for pomegranate farming in Tunisia"},"content":{"rendered":"
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Pomegranate is one of Tunisia’s highest-value tree crops<\/strong> and an important source of income for smallholders. Yet many decisions – from irrigation and fertilisation to pest management and harvest timing – \u00a0still rely largely on field experience rather than on continuously recorded data.<\/p>\n

BRIDGE-AI<\/a>‘s Tunisian pilot, led by the University of Sousse<\/a>, is working to connect that local expertise with a structured evidence base.<\/p>\n

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<\/strong> designed to gather real-world data on orchard management practices.<\/p>\n

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<\/strong>, creating a baseline dataset that can already support analysis while the monitoring system is being prepared.<\/p>\n

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.<\/p>\n

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These sources will be combined into a harmonised multimodal dataset for pomegranate cultivation<\/strong>, 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.<\/p>\n

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.<\/p>\n

With the first field campaign completed, Sousse now has the data foundation needed to move towards more informed, locally grounded orchard management<\/strong>.<\/p>\n

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The BRIDGE-AI Tunisian Sousse pilot is combining the knowledge of 22 growers with climatic, soil, historical, and field data to build the groundwork for Generative AI decision support in pomegranate orchards.<\/p>","protected":false},"author":1,"featured_media":95030,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[276],"tags":[],"class_list":["post-5846","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-pilot-news"],"yoast_head":"\nBRIDGE-AI builds a data foundation for pomegranate farming in Tunisia - bridge-project.ai<\/title>\n<meta name=\"description\" content=\"BRIDGE-AI kicks off to support climate-smart agriculture in Africa through Generative AI and digital tools for farmers.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/bridge-project.ai\/yo\/pomegranate-farming-tunisia\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"BRIDGE-AI builds a data foundation for pomegranate farming in Tunisia - 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