The latest comprehensive research agenda in the Journal of Agricultural Education and Extension was published in 2012 (Faure, Desjeux, and Gasselin 2012), and since then there have been quite some developments in terms of biophysical, ecological, climatological, social, political and economic trends that impact farming and the transformation of agriculture and food systems at large as well as new potentially disruptive technologies.
Social farming (SF) has emerged as a social innovation practice shaping heterogeneous approaches and results. This study discusses the complexity of SF policy and practices, and it is led by the main hypothesis that the relationship between agricultural and social dimensions might be very heterogeneous, not only in different national contexts but also within the same national and local level. SF policy and practices are investigated testing the hypothesis of three main different modalities of interaction according to how the social and the agricultural perspectives interact.
The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify “bottlenecks” in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual’s decisions.
The profound changes in European policy for farms advisory services (FAS) require a period of experimentation and results observation before the new CAP 2021-2027. This paper focuses on Measure 2 of Rural Development Programme (RDP) 2014-2020. The paper is focused on the description of case studies in three Italian regions: Campania, Emilia-Romagna and Veneto. Different Measure 2 – sub-measure 2.1 models are analyzed through a qualitative approach, using a conceptual framework adapted by Birner et al. (2009).
SALSA is an EU Horizon 2020 project that set out to assess the current and future role of small farms and related small food businesses (suppliers, processors, distributors) in achieving sustainable Food and Nutrition Security (FNS). SALSA studied small farms in 30 reference regions in 20 countries - 25 regions (at the so-called NUTS3 administrative level) in Europe and 5 regions in Africa.
SALSA est un projet Horizon 2020 de l'UE qui visait à évaluer le rôle actuel et futur des petites exploitations agricoles et des petites entreprises alimentaires associées (fournisseurs, transformateurs, distributeurs) dans la réalisation d'une sécurité alimentaire et nutritionnelle (SNA) durable. SALSA a étudié de petites exploitations dans 30 régions de référence dans 20 pays : 25 régions (au niveau administratif dit NUTS3) en Europe et 5 régions en Afrique.
mNutrition was a five-year global initiative supported by the Department for International Development (DFID) between 2013 and 2018, organised by GSMA and implemented by in-country mobile network operators (MNOs) and other providers. The evaluation was carried out by a consortium of researchers from Gamos, the Institute of Development Studies, and the International Food Policy Research Institute. This briefing summarises key evaluation findings and presents lessons learned on three key topics: 1.
This paper calls for a better integration of place-based, evidence-based and inclusive dimensions in the implementation of the Science, Technology and Innovation (STI) plans and industrial policies in sub-Saharan Africa. To this end, the analysis contrasts with and takes inspiration from the recent and ongoing international experiences in the elaboration of Innovation Strategies for Smart Specialisation (S3).
The core idea of the article is the existence of complicated array of deterrent factors that influences innovation activity of agriculture organizations, and subjective, psychological factors among those factors as well. The main goal of this work is to assess the top management and proprietors’ of AIC enterprises readiness to implement the innovations. As a research’ working hypothesis used the decisive role of human factor in answering the question whether to innovate or not.
Le Mali a quadruplé sa population entre 1960 et 2020. Cette croissance démographique implique des besoins d’accès à la sécurité alimentaire et nutritionnelle, à la santé, à l’éducation et à l’emploi pour les primo arrivants. C’est le secteur agricole qui est sollicité par les politiques publiques pour répondre à cette demande. Quelle est la tendance démographique dans la zone cotonnière du Mali ? Quelles ont été les réponses locales face aux implications de cette croissance démographique en termes d’accès à la santé et à l’éducation ?