Summary of the project: Food production is the main outcome of agricultural activities. However, the current forms of both intensive and extensive agriculture are intrinsically fragile in terms of sustainability. Solutions based on high level scientific knowledge are needed to develop agricultural systems that require a lower energy input. The challenge is complex. While on the one hand food research and its targets can be designed with a reasonable probability of being correct, on the other hand these models even up to the recent past were adapted to priorities that did not even consider their integration into sustainable agricultural systems. We must instead adopt as preeminent the centrality of sustainability to the process from agriculture to food. This approach should also consider the changing socioeconomic conditions and their impact on the ecology of agro-systems, crucial when adopting modern systems biology approaches.

The dawn of the new millennium has coincided with a technological revolution in all fields of biology: the genomics era, based as it is on high-throughput technologies, is revealing the metabolic networks that shape plant, animal, and microbial traits of agricultural interest. In particular, a massive amount of data on the genetic determinants of useful organisms is produced, in a quantity that is unprecedented for biology but essential for research, both basic and applied. There has also been a parallel exponential growth in the amount of data concerning the impact of nutrition on human health. This has created a web-based information/knowledge resource that can potentially be used to integrate ‘omics’ data in the design and production of the foods of tomorrow.

The task is not easy, as we now need to be able to understand, interpret, and use this huge amount of data, both already available and to come. This is a task that can be successfully completed only by developing systems-based methodologies (mostly artificial intelligence (AI) methods) that fully enable cross-disciplinary integrative approaches. Specifically, big data management technologies must be integrated with an increased understanding of the interactions between the agro-ecosystem drivers that operate in food production as well as in health knowledge and care. Only by achieving this goal, we may hope to govern a properly designed, strategic, knowledge-based development of novel foods derived from self-sustainable agricultural systems.

And only by understanding in depth the interaction of food with the human heritage and culture we can guarantee that such new food is healthier and low-risk. The quality of agricultural production processes, of food products, and the ensuing diets must be the topmost concern and dictate the objectives necessary to identify the right solutions and to succeed in facing the challenge of ensuring a sufficient production of safer, healthier, and more sustainable food for humans.