This brief illustrates the different forms of knowledge, and the ways to create and manage it.
This regional workshop was designed to strengthen the capabilities of representatives of NIFUs for analyzing the situations of their NAIS, and to use their national experiences to identify strengths, weaknesses, and threats/challenges affecting seven key areas influencing development of NAIS, namely: (i) strategy/policy, (ii) institutional aspects, (iii) stakeholders, (iv) content, (v) people, (vi) infrastructure, and (vii) financial aspects. Possible solutions for the key weaknesses and threats /challenges were defined by participants.
This free Massive Open Online Course (MOOC) on Open Data Management in Agriculture and Nutrition was first created in 2016. The course was delivered 5 times between November 2017 and November 2018, reaching over 5000 people globally, before being made available for unrestricted use
Ce cours en ligne massif (MOOC) gratuit sur la gestion des données ouvertes en agriculture et nutrition a été créé en 2016. Déjà en 2017 et 2018, plus de 5000 participants de partout dans le monde ont déjà suivi cette formation, laquelle est maintenant disponible pour une utilisation gratuite et sans restriction.
El Curso Masivo en Línea (MOOC) gratis sobre la Gestión de Datos Abiertos en Agricultura y Nutrición fue creado originalmente en el año 2016. El curso fue dado 5 veces entre Noviembre del 2017 y noviembre del 2018, alcanzando a más de 5000 personas mundialmente, antes de ser hecho disponible para su uso sin restricciones.
This paper discusses a range of approaches and benchmarks that can guide future design of value chain impact evaluations. Twenty studies were reviewed to understand the status and direction of value chain impact evaluations. A majority of the studies focus on evaluating the impact of only a few interventions, at several levels within the value chains. Few impact evaluations are based on well-constructed, well-conceived comparison groups. Most of them rely on use of propensity score matching to construct counterfactual groups and estimate treatment effects.
Following the remarkable success of performance testing in the commercial sector, the Agricultural Research Council's Animal Improvement Institute (ARC–AII) initiated a beef cattle performance testing scheme for smallholder farmers in 1996. The scheme, which became known as Kaonafatsho ya Dikgomo (Sotho for animal improvement), has been running well in the Northern and North West Provinces and is set to spread gradually to the rest of the country.
This learning module on Applying innovation system concept in agricultural research for development has been prepared to serve as a tool in achieving the objective of strengthening the capacity of project staff and other researchers and actors who are believed to have a key role to play in ushering in market-led agricultural transformation. This includes national, regional, international and private sector agricultural researchers, university lecturers, and others engaged in biophysical as well as social science research.
This flyer is about the AgriFood chain toolkit, which has been launched in 2013 by the CGIAR programme on Policies, institutions and markets.The AgriFood chain toolkit acts as a clearing house and learning platform – using the power of information and communication technologies to bring together people and resources.
The aim of this paper is to show the importance of monitoring genetic improvement programmes using the examples of an improvement programme for the Sahiwal breed in Kenya and a progeny testing scheme for Friesian cattle in Kenya. The paper is based on reports by Rege et al. (1992) and Rege and Wakhungu (1992) for the Sahiwal project and Rege (1991a and 1991b) for the progeny testing scheme for Friesian cattle.