The State of the Field for Research on Agrifood Systems

Science is called upon in times of significant change and uncertainty to respond to global challenges and opportunities. Novel approaches are needed to connect science with policy targets so that we can dedicate some of the scientific knowledge that we’ve accumulated over the course of human history on being able to save the world—while we still have a world left to save. Converging crises of hunger, climate, and political unrest remind us there is no time to waste. The impacts of climate change are increasingly evident worldwide, particularly affecting farmers and rural communities in regions that already struggle with poverty, hunger, and access and affordability of nutritious diets. Governments, funders, and public and private sectors are investing significant energy and resources to promote and identify evidence-based solutions across agrifood systems. A proliferation of research published over the past 15 years encourages agrifood systems to contribute towards a broader set of outcomes beyond productivity, and embrace nutrition, women’s empowerment, environmental sustainability, resilience, and inclusion. There is a profound sense of urgency for all actors, and especially global institutions, to innovate and adapt in response to an ambitious set of targets while paying attention to potential trade-offs and unintended consequences that come with integrating multiple objectives simultaneously. ‘The State of the Field for Research on Agrifood Systems’ uses artificial intelligence (AI) to analyse global research distribution from the past 13 years. This report provides a macro-level review of more than six million summaries of scientific papers and reports. It offers a snapshot across agrifood systems research, highlighting where progress has occurred, and where significant gaps remain. The findings of the report are presented in separate sections to facilitate navigation, but we encourage readers to explore the connections more holistically. Artificial intelligence offers a powerful set of innovative technologies, including generative AI. Generative AI optimizes knowledge and data to identify patterns and, where appropriate, combines data from diverse sources to generate new insights. In an increasingly interconnected science and policy landscape, it is crucial to have a comprehensive understanding of how past and future research contributes to broader goals.