In this paper the High Nature Value (HNV) livestock farming systems are defined. These systems are found mainly in marginal areas where physical factors, and in some cases social factors, have prevented intensification of land-use. NV-LINK is a Horizon2020 project that seeks to improve the socio-economic and environmental sustainability of HNV farming in 10 Learning Areas, and more widely across the EU, by promoting innovation.
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.
The purpose of the TATA-BOX project was to develop a toolbox to support local stakeholders in the design of an agroecological transition at local level. A participatory process based on existing conceptual and methodological frameworks was developed for the design of new configurations of stakeholders and resource systems in the farming systems, supply-chains and natural resources management that were to form a new agroecological territorial system. This process, presented here, was adapted and tested on two adjacent territories in south-western France.
For farmers, the transition towards agroecology implies redesigning both their production system and their commercialisation system. To engage in this type of transition, they need to develop new knowledge on practices adapted to local conditions, which will involve new actors in their network. This chapter explores the role of actors’ networks in the agroecological transition of farmers, with a particular focus on farming practices and modes of commercialisation.
Innovation policies are considered the long-term strategy to overcome the present systemic crisis. But this crisis is questioning such policies, their presuppositions and institutional arrangements. This questioning includes the Triple Helix theory and its impact on research and innovation policies. The goal is to examine how this theory can respond to theoretical and practical challenges, how the theory needs to evolve in order to fit the present context.
This material was presented duting the conference: Big Data, a multiscale solution for a sustainable agriculture in Copenhagen Denmark in 2017 and brings an overview of the technological innovations of the French agricultural sector.
Agricultural machinery manufacturers historically referred to the intermediate players for selling, maintenance, customer service and/or training of equipment appear to interact with farmers and end-users. Intermediate players have therefore faced the burden to master the technology, in constant evolution, and the associated training needs at the interface between sophisticated equipment and the end-user and its sociological characteristics (age, education, background, etc.).
The research programme URBAL (Urban-driven Innovations for Sustainable Food Systems) (2018–2020), funded by Agropolis Fondation (France), Fondation Daniel & Nina Carasso (France/Spain), and Fundazione Cariplo (Italy), and coordinated by CIRAD (France) and the Laurier Center for Sustainable Food Systems at Wilfrid Laurier University (Canada), seeks to build and test a participatory methodology to identify and map the impact pathways of urban-driven innovations on all the dimensions of food systems sustainability.
L’une des avancées les plus importantes dans le domaine de l’observation de la terre est la découverte des indices spectraux, ils ont notamment prouvé leur efficacité dans la caractérisation des surfaces agricoles, mais ils sont généralement définis de manière empirique. Cette étude basée sur l’intelligence artificielle et le traitement du signal, propose une méthode pour trouver un indice optimal. Et porte sur l’analyse d’images issues d’une caméra multi-spectrale, utilisée dans un contexte agricole pour l’acquisition en champ proche de végétation.
Mobiliser les approches issues de l’Intelligence Artificielle (IA) en Santé Animale (SA) permet d’aborder des problèmes de forte complexité logique ou algorithmique tels que rencontrés en épidémiologie quantitative et prédictive, en médecine de précision, ou dans l’étude des relations hôtes × pathogènes.