The main objective of this paper is to describe the AgroFE and Agrof-MM projects. This projects aims to develop an agroforestry training system based on a common framework and core content, and to promote training at European level. The knowledge databank is a component of the project training system. It aims to gather and share a set of documents, resources that partners can use and which will have been accessed by learners and the public users.

This paper explores the potential of Actor Network Theory (ANT) in understanding how the process of interaction and translation between human and non-human actors contribute to the development, adoption and diffusion of science-based innovations linked to the transition to organic farming. The study relies on two case studies, the French Camargue case covering a range of technical and social innovations, and the case from Bulgaria focusing on the development of a technical and product innovation, i.e. a veterinary product for organic beekeeping.

While a number of works question the alterity of alternative food chains, little has been said about the social processes under which new economic models are, or may be, developed within the broader movement around ‘short food supply chains’ (SFCs) in Europe. Considering SFCs as economic organisations, we propose an analytical framework based on New Economic Sociology and Convention Theory, enriched by Social and Solidarity Economics, to capture the social construction of new economic models in such chains.

Participatory plant breeding (PPB) is based on the decentralization of selection in farmers’ fields and their involvement in decision-making at all steps of the breeding scheme. Despite the evidence of its benefits to develop population varieties adapted to diversified and local practices and conditions, such as organic farming, PPB is still not widely used. There is a need to share more broadly how the different programs have overcome scientific, practical, and organizational issues and produced a large number of positive outcomes.

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.