This paper seeks to understand what influences research and extension professionals’ intentions to use AIS approaches and to explore how this can inform implementation and design of more effective AIS. We applied the Reasoned Action Approach through focus groups and structured questionnaires with research and extension professionals from government and non-government organisations in Sierra Leone, where AIS approaches are not widely used although increasingly institutionalised in policy.
Providing economic opportunities for youth in agriculture is essential to securing the future of agriculture in Africa, addressing poverty, unemployment, and inequality. However, barriers limit youth participation in agriculture and the broader food system. This scoping review aimed to investigate the opportunities and challenges for youth in participating in agriculture and the food system in Africa. This review conducted a scoping review using the PRISMA guideline. Published studies were retrieved from online databases (Web of Science, Cab Direct, and Science Direct) for 2009 to 2019.
Participation of actors is essential for achievement of the United Nation’s (UN) Sustainable Development Goals (SDGs). With respect to sustainable agriculture the UN has introduced a collaborative framework for food systems transformation encompassing: 1) food system champions identification; 2) food systems assessment; 3) multi-stakeholder dialogue and action facilitation; and, 4) strengthen institutional capacity for food systems governance. The last two actions are the focus of this thesis.
Networks and partnerships are commonly-used tools to foster knowledge sharing between actors and organisations in the Agricultural Knowledge and Innovation System (AKIS), but in Europe the policy emphasis on including users, such as farmers and foresters, is relatively recent. This paper assesses user involvement in a diverse set of European Union (EU)-funded and non-EU (formal and informal) multi-actor partnerships. This research used a common methodology to review several forms of multi-actor partnerships involving users and other actors.
FAO Eritrea, in partnership with the Ministry of Agriculture is implementing the national component of a global project entitled “Developing capacity in Agriculture Innovation System project: Scaling up the Tropical Agriculture Platform Framework”.
The application of ubiquitous computing has increased in recent years, especially due to the development of technologies such as mobile computing, more accurate sensors, and specific protocols for the Internet of Things (IoT). One of the trends in this area of research is the use of context awareness. In agriculture, the context involves the environment, for example, the conditions found inside a greenhouse.
This document is part of the project “Strengthening the adaptive capacity to climate change in the fisheries and aquaculture sector of Chile”, executed by the Undersecretariat of Fisheries and Aquaculture and the Ministry of the Environment, and implemented by the Food and Agriculture Organization of the United Nations, with funding from the Global Environment Facility. The work was implemented in four pilot coves: Caleta Riquelme (Tarapacá); Caleta Tongoy (Coquimbo); Caleta Coliumo (Biobío); and Caleta El Manzano-Hualaihué (Los Lagos).
The impact of global warming on crop growth periods and yields has been evaluated by using crop models, which need to provide various kinds of input datasets and estimate numerous parameters before simulation. Direct studies on the changes of climatic factors on the observed crop growth and yield could provide a more simple and intuitive way for assessing the impact of climate change on crop production.
Inclusive business models dominate current development policy and practices aimed at addressing food and nutrition insecurity among smallholder farmers. Through inclusive agribusiness, smallholder food security is presumed to come from increased farm productivity (food availability) and income (food access). Based on recent research, the focus of impact assessments of inclusive business models has been limited to instrumental aspects, such as the number of farmers supported, the training provided, and immediate farm outcomes, namely revenue.
Soil texture is a key soil property influencing many agronomic practices including fertilization and liming. Therefore, an accurate estimation of soil texture is essential for adopting sustainable soil management practices. In this study, we used different machine learning algorithms trained on vis–NIR spectra from existing soil spectral libraries (ICRAF and LUCAS) to predict soil textural fractions (sand–silt–clay %). In addition, we predicted the soil textural groups (G1: Fine, G2: Medium, and G3: Coarse) using routine chemical characteristics as auxiliary.