PROIntensAfrica · Towards a long-term Africa-EU partnership to raise sustainable food and nutrition security in Africa

PROIntensAfrica intends to develop a proposal for a long term research and innovation partnership between Europe and Africa, focusing on the improvement of the food and nutrition security and the livelihoods of African farmers by exploring and exploiting the diversity of pathways to sustainable intensification of African agro-food systems. The exploration will include environmental, economic and social externalities along the whole value chains. PROIntensAfrica has the ambition to formulate a research and innovation agenda, identifying the domains in need for further research to realize the potential of African food systems. In addition, PROIntensAfrica will suggest governance mechanisms that are effective in supporting the partnership. Key is the perception that pooling resources is the best way to align existing and initiate new research. This perception follows the policy of the EC, where instruments of joint programming like ERA-NET, JPI and article 185 aim to accomplish synergy and increase the effectiveness of resources. Pooling resources goes beyond the scientific domain and reaches into the policy domain. Consequently, besides being rooted in sound and challenging research, a partnership proposal needs to meet national and international policies to fly. Therefore PROIntensAfrica pay specific attention to engage with the policy domain, as exemplified by the intended creation of a policy support group. The rationale of the project is that a variety of pathways leads to sustainable intensification of African food systems. Different pathways are advocated in literature. High-input farming systems, for example, contrast with organic farming systems, each with their own supporters and criticasters. It is the conviction of the PROIntensAfrica consortium that moving beyond that debate will open exciting new pathways, and that combining elements of different systems will yield innovative systems that are optimally adapted to specific contexts.