Unveiling Future Trends in Agri-Food using semi automated horizon scanning

Sustainability and climate change represent major challenges for the agri-food sector in the upcoming decades and will significantly alter the requirements for nutrition and food production. The Food and Agriculture Organization (FAO) estimates that food systems contribute over one-third of global greenhouse gas emissions. Conversely, the agricultural sector is among the most vulnerable to the impacts of climate change. This dual role of the food sector as both a significant contributor to and victim of climate change necessitates urgent and concerted efforts to develop resilient and sustainable practices.
The article explores how semi automated horizon scanning - a technique for identifying emerging trends and risks - can be applied to the agri-food sector. By utilizing advanced machine learning and natural language processing, key trends are identified that could contribute to a more resilient food system in the context of climate change and evolving consumer behaviors. This scientifically based and methodologically advanced search for early signals of technological and social change seeks to assist actors in the agri-food system in proactively addressing weak signals, leveraging emerging opportunities, and building resilience against transformations.