Simulating the Capacity of Rainfed Food Crop Species to Meet Social Demands in Sudanian Savanna Agro-Ecologies
West African land use systems have been experiencing one of the fastest transformations in the world over recent decades. The Sudanian savanna is an interesting example, as it hosts the cultivation of some crops typical of the Guinean savanna as well as some of the Sahel. Therefore, this region is likely to experience further changes in its crop portfolio over the next decades due to crop migration processes responding to environmental change. Simulation approaches can guide the development of agricultural production strategies that contribute to sustainably optimize both food and fuel production. This study used crop models already available in the APSIM platform to simulate plant production and the soil water and nutrient cycles of plots cultivated with groundnut, millet, sorghum, maize, and rice on three (two upland and one lowland) soil fertility classes and subjected to five levels of management (conventional tillage without residue incorporated to the soil and nor fertilizer application; conventional tillage without residue incorporated to the soil and 5 kg N ha−1; conventional tillage with residue incorporated to the soil 20 kg N ha−1, and no-till herbicide treated with 50 and 100 kg N ha−1). Simulation outputs were contrasted against data reported in the literature and converted into nutritional, fuel and feed yields based on the qualities and uses of their different plant comparments. Groundnut yields outperformed all of the cereals across most growing conditions, nutritional and feed indicators. Maize and rice provided the highest caloric yields, with the least fertile growing conditions. Sorghum provided average to high caloric and iron yields across all of the treatments. Millet provided the highest iron yields and high fuel yields across most treatments. Some simulated treatments could not be compared against literature review data because of their absence in actual cropping systems and the lack of experimental data. Plant production was simulated with higher accuracy than the other components of the simulation. In particular, there is a need to better parameterize and validate the rice, groundnut and millet models under Sudanian savanna conditions in order to perform more accurate comparative assessments among species.