This data article contains annotation data characterizing Multi Criteria Assessment (MCA) Methods proposed in the agri-food sector by researchers from INRA, Europe's largest agricultural research institute (INRA, https://institut.inra.fr/en). MCA can be used to assess and compare agricultural and food systems, and support multi-actor decision making and design of innovative systems for crop production, animal production and processing of agricultural products. These data are stored in a public repository managed by INRA (https://data.inra.fr/; https://doi.org/10.15454/WB51LL).
This article starts by describing the evolution of innovation in agricultural research and cooperation for development, including an historical overview of agricultural research for development from green revolution to the re-discover of traditional knowledge. Then the authors analyze participation in...
Industrial agriculture and its requirement for standardized approaches is driving the world towards a global food system, shrinking the role of farmers and shifting decision-making power. On the contrary, a holistic perspective towards a new food-system design could meet the...
The European small ruminants (i.e. sheep and goats) farming sector (ESRS) provides economic, social and environmental benefits to society, but is also one of the most vulnerable livestock sectors in Europe. This sector has diverse livestock species, breeds, production systems...
The paper analyses the determinants of farmers’ adoption of innovations and studies the effect of the source of information and the connection with agricultural research on the contribution of innovation to farm performance. The paper uses primary data collected ad...
Networks and partnerships are commonly-used tools to foster knowledge sharing between actors and organisations in the Agricultural Knowledge and Innovation System (AKIS), but in Europe the policy emphasis on including users, such as farmers and foresters, is relatively recent. This...
