Geographic information system (GIS) data is often used to map socio-economic data with a spatial component. This data, which is obtained from multiple open-source databases, complements official statistics and generates additional spatial inputs to statistical and econometric analyses. IFAD uses impact assessments using data from face-to-face interviews in order to determine the impact of their projects on strategic goal and objectives. However, the COVID-19 pandemic meant these interviews could no longer take place.
The co-creation and sharing of knowledge among different types of actors with complementary expertise is known as the Multi-Actor Approach (MAA). This paper presents how Horizon2020 Thematic-Networks (TNs) deal with the MAA and put forward best practices during the different project phases, based on the results of a desktop study, interviews, surveys and expert workshops. The study shows that not all types of actors are equally involved in TN consortia and participatory activities, meaning TNs might be not sufficiently demand-driven and the uptake of the results is not optimal.
In this report, food distribution is analysed within the context of food systems in Tanzania. This study looks at entry points for further studies of food system issues within the country that will affect progress towards the achievement of Sustainable Development Goal (SDG) 2. Both qualitative and quantitative methods are used, first to map and conceptualize the complexity of the food system in Tanzania, and then to quantify the likely impacts of scenarios of action and inaction.
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".
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.
In Nepal, the Plantwise programme, in collaboration with International Development Enterprises (iDE), has established networks of locally owned plant clinics, run by community business facilitators (CBFs) trained as plant doctors, who provide practical plant health advice. This study examines how gender is integrated into this programme in three purposively selected study districts. It presents the experiences of farmers, the challenges they faced in accessing plant health services through a gender and social inclusion lens.