The urgency for investment on local data for advancing food assessments in Africa: A review case study for APSIM crop modeling. (March 2023) - Carcedo, Ana J.P.; Vieira Junior, Nilson; Marziotte, Lucia; Correndo, Adrián A.; Araya, Alemo; Prasad, P.V. Vara; Min, Doohong; Stewart, Zachary P.; Faye, Aliou; Ciampitti, Ignacio A.
Abstract: Crop growth models can be useful tools to evaluate potential scenarios, yet the limited field data is an obstacle for providing significant insights at the local level. This certainly applies to several regions in Africa, where crop models built regional scenarios based on low resolution field data, leading to unsupported agricultural interventions on smallholders' systems. This review provides a synthesis analysis of crop modeling efforts in Africa using Agricultural Production Systems Simulator (APSIM) studies as a case-study. This research aims to highlight the value of standardized protocols to collect, store and deploy field data, and highlights the critical issue of limited data accessibility of published manuscripts and unavailability of a data sharing platform.Investment in local-level data collection and data sharing platforms is critical to guarantee the advancement of science and to provide reliable assessments to address complex challenges of food, nutrition, and climate security in Africa. Graphical abstract: Image 1 Highlights: Limited field data represents a challenge for crop models to provide useful insights. This study showcases the need for investments on open data sources. A systematic review was executed to collect crop modeling studies within Africa. There is a need of standardization for field data collection and its accessibility. Investment in local-level data is critical to provide reliable food assessments.