Societal Impact StatementTo help save our planet, we need to shift to plant‐based protein food and enhance sustainable agricultural practices. Cultivation of legumes, including soybean, will be key because they produce protein‐rich beans without high applied fertilizer input. This complex challenge involves many stakeholders beyond the agricultural sector. In the ‘Soy in 1000 Gardens’ project, we engaged more than thousand citizens in a 6‐month gardening project aiming at facilitating sustainable soybean cultivation in Belgium. Our work shows that with the right approach, citizen science can provide insights to develop more sustainable agri‐food systems when integrated with fundamental and applied science.Summary
The global food system faces numerous challenges in its pursuit of sustainability. Shifting to more plant‐based protein sources as well as transitioning to self‐reliant agri‐food systems is one way to meet these challenges. This transition requires the involvement of multiple stakeholders beyond the agricultural sector such as the citizens themselves.
In this study, we employed a citizen science approach through the ‘Soy in 1000 Gardens’ project, which engaged more than 1000 citizen scientists in a 6‐month gardening project during which citizens not only observed plant growth but also executed plant growth measurements that meet scientific standards. We aimed at increasing the awareness about the power of soybean and its symbionts for sustainable plant protein production and at isolating efficient nitrogen‐fixing rhizobia to be used by local farmers to produce protein‐rich soybeans.
The results suggest that the success of citizen science projects depends on the level of engagement and the provision of adequate support, among other factors.
This study thus highlights the potential of citizen science to address complex challenges and contribute to more sustainable agri‐food systems when properly integrated. Unique in its scope, the project provided important insights into the drivers of participation, attrition and data quality.