From 4 June to 1 July 2012, the UN Food and Agriculture Organization (FAO) hosted a moderated email conference on "Ensuring the full participation of family farmers in agricultural innovation systems: Key issues and case studies". It was a highly successful global dialogue, with a very stimulating discussion. About 560 people subscribed to the conference, of whom 114 people (20% of the total), from nearly 50 different countries, wrote at least one of the 242 messages that were posted.
This paper illustrates the Small Stock Innovation Platform, an initiative which is one of the key tangible outcomes of the Strengthening Capacity in Agricultural Research for Development in Africa (SCARDA) program, focused on strengthening capacity in agricultural research systems in selected countries and institutions in all three sub-regions of Sub Saharan Africa.
This innovation story narrates the experience of Improving Productivity and Market Success (IPMS) project on innovative banana value chain development in Metema district, Amhara, Ethiopia. The project introduced banana production systems in the district for the first time in 2005. IPMS together with the stakeholders provided support along the banana value chain on production, in put supply and marketing.
This paper presents and discusses a diagnostic framework to identify institutional processes in the creation of public-private partnerships (PPPs) for agricultural innovation. The diagnostic framework proposed here combines a conceptualisation of institutions with a conceptualisation of technology. We argue that a performative notion of institutions provides a better tool for institutional diagnostics than the common understanding of institutions as ‘rules of the game’.
Social media (SM) such as Twitter and Facebook are new communication tools for rural communities, and SM has enabled the creation of rural social networks. Increased use by farmers of 'mobile digital devices' and better rural access to broadband services have enhanced so that SM is being used to support farming decisions. However, in depth studies on how SM is used for knowledge sharing amongst farmers and the role of rural professionals (e.g. advisors) in this space is an emergent field with limited literature.
This 2016 report provides an economic overview of the Canadian agriculture and agri-food system using the most recent data available. It is meant to be a multi-purpose reference document that presents: • the agriculture and agri-food system in the context of the Canadian economy and international markets; and, • a snapshot of the composition and performance of the agriculture and agri-food system as it evolves in response to challenges, opportunities and market developments. The report begins with a special feature section on natural resource use and the environment.
In this paper the authors present the development of an analytical framework to study agricultural innovation systems. They divide the agricultural sector into four levels and expand the innovation system approach to study innovation processes.
Innovation is considered as one of the key drivers for a competitive and sustainable agriculture and the European Commission highlights the importance of tailoring innovation support to farmers’ needs, especially in European Rural Development Policy (reg EU 1305/2013). The scientific literature offers a wide panorama of tools and methods for the analysis of innovation in agriculture but the lack of data on the state of innovation in the farms hampers such studies. A possibility to partially overcome this limit is the use of data collected by the Farm Accountancy Data Network (FADN).
This report deals with the adoption of technological innovations in the case of rice farming in Togo.
The following is a summary that introduces the report.
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.