L’approche Champs-Écoles Producteurs (CEP) est introduite au Ghana en 1996, au Niger en 1999 et au Sénégal en 2000 via le projet « Gestion intégrée de la Production et des Déprédateurs (GIPD) » soutenu par la FAO.
In sub-Saharan Africa, pastoralism is usually practiced especially in the arid lands where the climate is hot and dry with low and erratic rainfall and rugged terrain. The pastoralists are characterized by varying aspects of socio-cultural set ups, production forms and strategies of survival which include mobility. The pastoralists’ main mode of livelihood is livestock keeping where varied species are kept according to desire but the main species being camel, sheep, goats and cattle. Pastoralists have the highest incidence of poverty and the least access to basic services.
The global food supply is increasingly facing disruptions from extreme heat and storms. It is also a major contributor to climate change, responsible for one-third of all greenhouse gas emissions from human activities.This tension is why agriculture innovation is increasingly being elevated in international climate discussions.
Assessing or understanding the agriculture innovation system (AIS) is an essential step to better understand the needs, new skills and functions needed by the actors and the system. To accelerate the uptake of innovation and progress towards eradicating poverty, there is an urgent need for well-coordinated, demand-driven, and market-oriented information, knowledge, technologies and services.
Agricultural Internet of Things (IoT) has brought new changes to agricultural production. It not only increases agricultural output but can also effectively improve the quality of agricultural products, reduce labor costs, increase farmers' income, and truly realize agricultural modernization and intelligence. This paper systematically summarizes the research status of agricultural IoT. Firstly, the current situation of agricultural IoT is illustrated and its system architecture is summarized. Then, the five key technologies of agricultural IoT are discussed in detail.
Droughts are causing severe damages to tropical countries worldwide. Although water abundant, their resilience to water shortages during dry periods is often low. As there is little knowledge about tropical drought characteristics, reliable methodologies to evaluate drought risk in data scarce tropical regions are needed.
The Digital Innovation Strategy (DIS) of the Regional Office for Africa (RAF) of FAO has been prepared to respond to critical challenges facing inclusive and sustainable agrifood system transformation in sub-Saharan Africa. It is enshrined in the new Strategic framework 2022–2030 that aims to accelerate the "transformation to more efficient, inclusive, resilient and sustainable agri-food systems for better production, better nutrition, a better environment and a better life, leaving no one behind".
Facilitation has proved crucial for enabling the interaction of Agricultural Innovation System (AIS) actors to address the target and to innovate. This “Guide on training of facilitators of multi-actor agricultural innovation platform” is aimed at serving facilitators when multi-actor agricultural innovation platforms (MAIPs) are organized. Since MAIPs are still an emerging concept, there are not many cases to refer to.
Digitization in agriculture is rapidly advancing further on. New technologies and solutions were developed and get invented which ease farmers’ daily life, help them and their partners to gain knowledge about farming processes and environmental interrelations. This knowledge leads to better decisions and contributes to increased farm productivity, resource efficiency, and environmental health. Along with numerous advantages, some negative aspects and dependencies risk seamless workflow of agricultural production.
This article extends social science research on big data and data platforms through a focus on agriculture, which has received relatively less attention than other sectors like health. In this paper, I use a responsible innovation framework to move attention to the social and ethical dimensions of big data “upstream,” to decision-making in the very selection of agricultural data and the building of its infrastructures.