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.
Even prior to COVID, there was a considerable push for food system transformation to achieve better nutrition and health as well as environmental and climate change outcomes. Recent years have seen a large number of high visibility and influential publications on food system transformation. Literature is emerging questioning the utility and scope of these analyses, particularly in terms of trade-offs among multiple objectives.
The global impacts of the climate crisis are becoming ever clearer, and natural resources and ecosystems are being depleted. Despite some progress, hunger and poverty persist, and inequalities are deepening. The world is realizing that unsustainable high external inputs and resource-intensive industrialized systems pose a real danger of biodiversity loss, increased greenhouse gas emissions, shortages of healthy food, and the impoverishment of dispossessed peasants around the world.
El Proyecto "Desarrollo de capacidades para los sistemas de innovación agrícola: ampliación del marco común de la Plataforma de Agricultura Tropical" (en resumen, Proyecto TAP-AIS) es implementado por la Organización de las Naciones Unidas para la Alimentación y la Agricultura (FAO) en países de África (Burkina Faso, Malawi, Eritrea, Ruanda, Senegal), América Latina (Colombia), Asia y el Pacífico (Camboya, Lao PDR, Pakistán), con el objetivo estratégico de contribuir al fortalecimiento de capacidades para fomentar, reconocer y fortalecer la innovación rural en el contexto de la transformaci
Multi-actors innovation platforms (MAIPs) are increasingly deployed as a model for participatory and inclusive innovation to address the challenges of sustainability in complex systems like the agri-food systems. The facilitation of co-innovation and multi-actor partnerships is critical to the success of MAIPs, as a common lesson learned across the multitude of initiatives around the world. The guideline was developed for Master Trainers to train MAIP facilitators. The guideline first gives an introduction to the definiton, principles, design, establishment and facilitation of MAIPs.
The Newsletter of the Tropical Agriculture Platform (TAP) provides regular updates on activities by TAP and its partners, on the projects and on upcoming events. This issue specifically refers to the period from February 2022 to April 2022.
The Newsletter of the Tropical Agriculture Platform (TAP) provides regular updates on activities by TAP and its partners, on the projects and on upcoming events. This issue specifically refers to the period from November 2021 to January 2022.
The Newsletter of the Tropical Agriculture Platform (TAP) provides regular updates on activities by TAP and its partners, on the projects and on upcoming events. This issue specifically refers to the period from May 2022 to July 2022.
The Newsletter of the Tropical Agriculture Platform (TAP) provides regular updates on activities by TAP and its partners, on the projects and on upcoming events. This issue specifically refers to the period from August 2022 to November 2022.
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.