This collection of posters from the TAP-AIS project illustrates key achievements of the project towards strengthening national agricultural innovation systems (AIS) in Africa (Burkina Faso, Eritrea, Malawi, Rwanda, Senegal), Latin America (Colombia), Asia and the Pacific (Cambodia, Lao PDR, Pakistan). For each of these nine countries, and for their respective regions, the posters provide: i) thematic focus and context; ii) constraints in the AIS; iii) capacity development interventions; iv) outcomes; v) the way forward.
The OECD InDeF team developed a portfolio approach to innovation. A portfolio approach takes a balcony view on innovation which helps organizations align innovation processes, resources and performance with organizational objectives and enables them to track innovation with a view to scaling. Coached by the OECD team, Enabel colleagues in Benin, Morocco and Palestine piloted this portfolio approach by reviewing their current innovation supporting activities and investments against a set of key criteria.
Familiar mixed dairy sheep farm is the most widespread system in the Mediterranean basin, in Latin America and in developing countries (85%). There is a strong lack of technological adoption in packages of feeding and land use in small-scale farms. To increase competitiveness, it would be of great interest to deepen the knowledge of how innovation was selected, adopted, and spread. The objective of this research was to select strategic feeding and land use technologies in familiar mixed dairy sheep systems and later assess dairy sheep farms in Spain.
Equipping agricultural extension and advisory services with nutrition knowledge, competencies and skills is essential to promote nutrition-sensitive agriculture. This report presents the results of an assessment of capacity within agricultural extension and advisory services, undertaken in Telangana State, India, with the global capacity needs assessment (GCNA) methodology developed by FAO and GFRAS. The methodology is available online at https://doi.org/10.4060/cb2069en
The potential beneficial and harmful social impacts generated by the introduction of novel technologies, in general, and those concerning nutrient recovery and the improvement of nutrient efficiency in agriculture, in particular, have received little attention, as shown in the literature. This study investigated the current social impacts of agricultural practices in Belgium, Germany and Spain, and the potential social impacts of novel technologies introduced in agriculture to reduce nutrient losses.
The digital transformation in agriculture introduces new challenges in terms of data, knowledge and technology adoption due to critical interoperability issues, and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.
This training manual, which is based on a methodology developed by FAO’s Research and Extension Unit (OINR), presents a training course on assessing AIS consisting of eight modules.
Agrifood system transformation to achieve the Sustainable Development Goals requires increased attention to developing, adapting and diffusing impactful science, technology and innovation (STI). Current levels and patterns of STI uptake are inadequate to facilitate needed agrifood system transformations, especially in today's low- and middle-income countries.
Africa–Europe Cooperation and Digital Transformation explores the opportunities and challenges for cooperation between Africa and Europe in the digital sphere.