Crop modeling to address climate change challenges in Africa: status, gaps, and opportunities

Africa faces an urgent need to boost food production to satisfy the growing demand. Targeted investments in integrated agriculture and water management systems are essential to address this challenge. However, there is a lack of comprehensive information on the potential applications of climate-smart agriculture (CSA) and its perspectives. This paper reviews current crop modeling technologies and their applications in the context of climate change and the CSA framework in Africa. It assesses research trends in various crop simulation models, selected practices, and appropriate crops to improve crop productivity in a sustainable African environment. A total of 379 relevant papers were considered. Results showed that 55% of studies used process-based models, with Maize being the most studied crop. However, many priority crops in Africa have been overlooked in modeling studies. Additionally, more than 52% of studies have contributed to climate change adaptation strategies and reducing yield gaps. Only 12% of the modeling work focused on CSA practices and on integrated climate change mitigation and adaptation measures. Current simulation modeling studies in Africa have contributed to shaping CSA practices, but their impact is constrained by limited data quality, inadequate model calibration, and regional climate variability. Crop models can indeed help tailor CSA practices by identifying region-specific strategies under changing climate conditions, but they also need to integrate socio-economic factors like access to resources and farmer decision-making. Additionally, strengthening local research capacity and improving data infrastructure will be crucial for maximizing the effectiveness of these models in supporting future CSA adoption. To meet food security goals through sustainable agricultural practices in Africa, it is essential to adopt CSA frameworks with a robust climate change mitigation component. The research outcomes will offer a comprehensive evaluation of the prominent models used across Africa, providing a roadmap for future investigations to select adequate approaches and crops based on available data when implementing crop models for specific areas in Africa.