Discover the future(s)!
Climate change, new biotechnologies and changing consumer habits and farming practices are just a few examples which illustrate the dramatic changes that agriculture in the EU may undergo until the year 2050. But how exactly will the challenges, trends and uncertainties develop? The answer to this question is of crucial importance if CropBooster-P wants to meet its goal of developing a future-proof roadmap for a sustainable food supply in Europe. As no one can predict what will happen, the CropBooster-P team did the next best thing: creating a set of diverse learning scenarios that allows us to discuss what might happen and what this would mean for the development of our roadmap. Over the course of the CropBooster-P Scenario Analysis, the project team explored 45 trends and a number of uncertainties that are related to the future of agriculture in Europe. The process resulted in four learning scenarios.
Workshop
On 14th April 2019, these scenarios were introduced to a large group of external stakeholders from science, politics and the food industry. The intensive one-day workshop took place in Brussels and was facilitated by the innovation consultancy SOMMERRUST and organized by the European Technology Platform (ETP) ‘Plants for the Future’. In order to foster in-depth discussion about the scenarios, the group was asked to imagine specific aspects of the four future worlds — like the typical dinner of a French middle-class family or the required training of a farmer in 2050. Based on the gained intuitive understanding of the scenarios, the CropBooster-P team and the stakeholders jointly worked out the potential practical implications and challenges regarding the key topics of yield, sustainability and nutritional quality.
Click on the scenario and read more about its content.
Scenario 1 Scenario 2 Scenario 3 Scenario 4
Not predictions but learning scenarios
Learning scenarios serve as a general framework for contemplating future worlds. By design, they are plausible but unlikely. Hence, reality in the year 2050 will probably include aspects from each of the four learning scenarios above as well as some unforeseen outcomes. Therefore, they cannot be considered as predictions. Nevertheless, the current set of scenarios covers a wide range of possibilities and therefore fulfills its purpose: to provide new perspectives, to make project results more robust, and to facilitate a more proactive stance towards future threats and opportunities.
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