DEEP FARM : CACAO use case dataset

Cacao, an economic pillar for many tropical countries, is of strategic importance to Côte d'Ivoire, the world's leading producer, supplying over 40% of global output. However, the sector is threatened by diseases, including Cacao Swollen Shoot Virus (CSSV), a viral disease transmitted by mealybugs, which causes rapid decline of cacao trees. Traditional control methods, such as eradication of infected plants, are costly and often ineffective, largely due to the difficulty of early detection. To address these limitations, the Deep Farm project, supported by an international consortium, proposes the use of innovative technologies such as imaging and artificial intelligence (AI) to improve early detection of CSSV. In Côte d'Ivoire, this project focuses on cacao cultivation and plans to establish a pilot farm, as well as train students in computer science (ESATIC) and agronomy (INP-HB). These students will collect high-quality images to train AI models capable of visually identifying disease symptoms on leaves, stems, and pods. Acknowledgment:This dataset was collected by the team at ESATIC & INP-HB (Ivory Coast) as part of the Deep Farm Erasmus+ project. Access to the report is restricted. Interested users may request access via Zenodo for research or educational purposes.