o e.g., the US. This may relate to how the innovation ecosystems in the EU function. For instance, to meaningfully contribute to the EU Green Deal, a rejuvenation of the agricultural ecosystem including academia, breeding and R&D companies, farm supply industry and farmers, is desirable: It is critical to recognize that agriculture is progressively turning into a business field where big data approaches can create the competitive edge. Integration of data coming from plant, microbial, soil, agronomy, robotization, machine learning, modelling and weather/climate disciplines combined with machine learning approaches, smart data queries and visualizations, may offer cutting edge insights. For academia, it enables data-based feedback loops with farmers and breeders and may prompt scientists to start or revisit experimental questions. Breeders may integrate outcomes from science, farming and down-stream producers, and develop evidence-based breeding strategies. Farmers instead may incorporate into their decision-making the best available information on nearly any aspect that influences productivity, farm sustainability, and product composition, residues and quality.
For this to be a success, an open innovation governance concept is needed that serves the interest of all stakeholders in the ecosystem and goes beyond the proposition of installing an EU-wide virtual predictive workflow as described in figure 3. It should be able to deal with pre-competitive and competitive big data information and activities and run on FAIR access and fair reward principles. Importantly, such a data platform will draw a significant resource, even if it succeeds to build on and interface with existing data platforms and initiatives. For instance, it would need an enterprise component with a robust 24/7 performance, as well as an R&D component provided by specialized research institutes that together cover the agricultural science field. Such a platform should ultimately derive its own sustainability by delivering better varieties and the best possible harvest, and ideally offer a lever to improve farm economics structurally through product branding and traceability. It requires however an extension of the skillsets of all participants, and this may create participation barriers to small scale companies and organizations. The big data trend in agriculture may also lead to formation of multiple parallel closed value chains, where players start cooperating based on pre-agreed working principles.
Smooth adoption of innovation interlinks with pricing and fair economics. It is a “must have” for all parties involved. Any new sustainability attribute should therefore either (1) reduce cost, (2) be cost neutral and have a convincing use benefit, or (3) trigger a surplus cost that is paid for because of benefits or broader policy requirements. In the field of sustainability, that introduces a long-term benefit dimension, one may expect that the innovation in scope will often increase costs in today’s balance sheet. Tailored policies, risk funding and a further activation of informed consumer choice are amongst the most promising enablers of the desirable market development underlying the Green Deal, and they need to complement seamlessly the EU innovation goals and resources with the proper time order in mind.
ES: But it is not just the seed sector that needs to make changes. Which actors are also involved?
MC: I think it is all of us collectively. We are the ones that slow down the migration to a sustainable world, and we do that at three levels: with our job in the economic system, as a consumer when shopping, and as a small shareholder looking for financial returns. To put it in other words: an abrupt migration to a sustainable world is unthinkable because the majority of society derives their welfare and income from the existing business environment.
Society as a whole is locked into a complex socio-economic equilibrium, and migration to a sustainable future needs to deal with business continuity at macro-level. This implies a gradual shift is the best