Harnessing Regenerative Agriculture, Unmanned Aerial Systems, and Artificial Intelligence for Sustainable Cocoa Farming in West Africa: A review

Cocoa production in West Africa—dominated by Côte d’Ivoire, Ghana, Nigeria, Cameroon, and Togo—faces interconnected agronomic, environmental, and socio-economic challenges that limit productivity and threaten smallholder livelihoods. Integrating Regenerative Agriculture (RA), Unmanned Aerial Systems (UAS), and Artificial Intelligence (AI) present a transformative framework for achieving sustainable and climate-resilient cocoa farming. This review synthesizes evidence from 2000 to 2024 and establishes a tri-axial model that unites ecological regeneration, spatial diagnostics, and predictive intelligence. Regenerative practices such as composting, mulching, cover cropping, and agroforestry rebuild soil organic matter, enhance biodiversity, and strengthen ecosystem services. UAS-based multispectral, thermal, and LiDAR sensing provide high-resolution insights into canopy vigor, nutrient stress, and microclimatic variability across heterogeneous cocoa landscapes. When coupled with AI-driven analytics for crop classification, disease detection, yield forecasting, and decision support, these tools collectively enhance soil organic carbon by 15–25%, stabilize yields by 12–28%, and reduce fertilizer and water inputs by 10–20%. The integrated RA–UAS–AI framework also facilitates carbon-credit quantification, ecosystem-service valuation, and inclusive participation through cooperative drone networks. Overall, this convergence defines a precision-regenerative model tailored to West African cocoa systems, aligning productivity gains with ecological restoration, resilience, and regional sustainability.