African agriculture is one of the less productive of the world because of low use of available water resources and of limited fertilizer input. A large increase in agricultural production is needed to meet increasing food requirements of the growing population of Africa, augmenting the risk of environmental pollution. In order to limit this risk adoption of sustainable irrigation and fertilization practices is required. The efficiency of these practices depends on numerous and conflicting objectives which lead to a complex multi-objective decision process. In this work we quantified the trade-offs among the agricultural gross margins and nitrates pollution for the major African crops. Based on an integrated biophysical model and a multi-objective evolutionary algorithm, we estimated optimal solutions (Pareto front) among both objectives to identify efficient irrigation and fertilization management patterns in several African countries. This analysis pointed out how the increase of farmer benefit is always related to a higher amount of nitrates losses. Knowledge of these sets of solutions helps decision-makers to choose optimum alternative strategies specifically tailored to each country. The multi-objective analysis indicates that in most of African countries farmers can significantly increase their income while preserving at the same time environment by adopting efficient fertilization and irrigation strategies.