Dakar, Senegal — The Islamic Organisation for Food Security (IOFS), OIC-COMSTECH and Université Cheikh Anta Diop de Dakar (UCAD) held a training workshop from 3 to 5 November 2026 on the use of emerging technologies for the automated early detection of diseases in edible crops.
Hosted by UCAD, the three-day workshop brought together expertise in plant pathology, crop protection and digital agriculture. The programme paired established diagnostic methods, including microscopy and rapid detection kits, with emerging approaches such as machine learning, image analysis and the use of sensors and drones to monitor crop stress.
Case studies covered disease management in cassava in Gabon, the use of deep learning to identify mango diseases and estimate their severity, and the application of machine learning to detect groundnut diseases in The Gambia. These examples illustrated how digital tools can flag visible symptoms for closer investigation and help plant protection services decide where to focus field visits and diagnostic testing.
For IOFS, the workshop advanced cooperation on a practical food security priority: helping agricultural services identify crop health problems early enough to give farmers timely advice. The programme also included roundtable discussions on participants’ training needs and how digital tools could be adapted to local crops, growing conditions and available diagnostic services.
The collaboration among IOFS, OIC-COMSTECH and UCAD connected university research with the needs of plant protection services and producers. It provided a forum for sharing experience across countries and exploring how these methods could support crop surveillance in OIC Member States.
