Review of crop modelling approaches to address climate change challenges in Africa

Abstract

Africa is facing an urgent need to increase food production to meet increasing demands. Targeted investments in integrated agriculture and, water management systems are required to meet this challenge. However, there is a lack of comprehensive information on the potential applications of climate-smart agriculture (CSA). This paper reviews current crop modeling technologies and their applications within the scope of climate change and the CSA framework in Africa. It evaluates current research trends in various crop simulation models and suggest advanced approaches to improve crop and environmental assessment, crop management, and decision-making. A total of 140 relevant papers were considered. Results showed that 84% of studies used process-based models, with Maize being the most studied crop. Additionally, DSSAT crop models and analysis of variance models have the highest contribution of physical and empirical crop modeling studies respectively. Over 72% of studies have contributed to adaptation strategies and reducing yield gaps, while only 8% of studies have been conducted on climate change mitigation and their trade-offs with adaptation using crop models under CSA. To ensure food security through sustainable agricultural practices in Africa, there is crucial to implement CSA models with a focus on the climate change mitigation component.