This report provides an overview of the Tropical Agriculture Platform (TAP) since its inception in 2012, when it was officially launched by FAO at the first G20 Meeting of Agriculture Chief Scientists (MACS) in September 2012 in Mexico, until December 2018. The G20 Agriculture Deputies agreed on this stock taking exercise that started under the 2018 Argentinian G20 Presidency.
This exercise was done on the occasion of the G20 MACS meeting in April 2019 in Japan. Its purposes are the following:
The study was conducted in Thakurgaon sadar Upazila to determine farmers’ perception of the extent and factors of ICTs effectiveness in transferring farming information. A total of 250 people who were already been taken services from different ICT center was selected as sample respondents following a random sampling technique. Primary data were collected using a predesigned interview schedule.
Technology and innovation are important in addressing complex problems in the agricultural sector in many developing communities. However, ways and mechanisms to integrate them in the agricultural sector are still a challenge due to the lack of clear pathways and trajectories. Value chains are seen as a strong policy instrument to increase profitability in the agricultural sector; there is also debate around whether value chains can be a potential option to organize technology and innovation trajectories in agriculture.
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”.
Le projet RIVAGE veut favoriser l’adoption de pratiques alternatives pour gérer les impacts de la pollution diffuse dans le bassin versant de la rivière Pérou en Guadeloupe. Son objectif est de produire et partager les connaissances sur les processus, les impacts et les pratiques innovantes avec les acteurs du territoire. Pour faciliter la prise en compte des résultats, le projet a créé une « école-acteurs ». L’école-acteurs est un espace d’échanges autour des thématiques liées à la pollution diffuse agricole.
Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the total yield, resulting in a decrease in the farmers' profits. To overcome this problem, many re-searchers have presented different state-of-the-art systems based on Deep Learning and Machine Learningapproaches. However, most of these systems either use millions of training parameters or have low classificationaccuracies.
Capacity development interventions are considered critical entry points for advancing gender equality in agricultural research systems. However, the impacts of capacity development programs are often difficult to track. Academic reviews highlight that insufficient attention is paid to the suitability of gender training programs to increase capacity and limited evidence is available on their longer-term impacts.