L’érosion hydrique est une préoccupation agronomique, économique et environnementale importante en milieu semi-aride méditerranéen. Le choix de la méthode pour l’estimer dépend des données disponibles et des conditions de la zone d’étude. Cet article vise à quantifier et spatialiser l’érosion hydrique en utilisant l’équation universelle des pertes en sol (Universal Soil Loss Equation [USLE]) dans ses versions modifiée (Modified − MUSLE) et révisée (Revised − RUSLE) et couplées à un Système d’information géographique (SIG) : MUSLE-SIG et RUSLE-SIG.
This study established physicochemical and sensory characteristics of virgin olive oils (VOOs) and linked them to consumers’ liking using external preference mapping. We used five Tunisian and two foreign VOO varieties produced by two processing systems: discontinuous (sp) and continuous three-phase decanter (3p). The samples were analyzed and evaluated by a panel of 274 consumers. The external preference mapping revealed five VOO clusters with a consumer preference scores rating from 40% to 65%.
This case study presents an analysis undertaken for the IFAD-funded Agropastoral Value Chains Project in the Governorate of Médenine, Tunisia. High-resolution imagery makes it possible to track the development of roads, buildings, irrigation schemes, and other types of investments. Over 140 km of road constructed or rehabilitated by the project are easily detectable on satellite imagery.
Individuals from a diverse range of backgrounds are increasingly engaging in research and development in the field of artificial intelligence (AI). The main activities, although still nascent, are coalescing around three core activities: innovation, policy, and capacity building. Within agriculture, which is the focus of this paper, AI is working with converging technologies, particularly data optimization, to add value along the entire agricultural value chain, including procurement, farm automation, and market access.
The concept of an innovation system is used to understand how innovation contributes to economic growth. However, innovation systems do not evolve evenly in different parts of the world. This paper contributes to the ongoing debate on the emergence of innovation systems in the context of developing countries. It uses the Rwandan case, where agriculture is a dominant socio-economic sector with high innovation potential. It explores how stakeholder interactions and policies contribute to the emergence of an agriculture innovation system in Rwanda.
Agriculture is crucial for the livelihood of millions of people worldwide and is one of the main drivers of deforestation, biodiversity loss and resource degradation. The contribution of agriculture to these environmental problems has been exacerbated by subsidies, which constitute the dominant public policy to support farmers. At the same time, other economic instruments introducing more sustainable land-use practices and incentivizing better environmental and social outcomes are already being applied worldwide.
The study was designed to answer the following three key questions:
(1) What types of investment instruments have been tested to support innovation in agri-food systems in the Global South, and how can these be categorized into a working typology?
(2) What is the evidence on how well different instruments have supported SAI's multiple objectives (e.g. social equality and environmental) at scale and what contextual and design factors affect their success or failure in achieving these objectives (e.g. type of value chain, who participates)?
What are the patterns of funding in agricultural innovation for the Global South1 ? Who are the key funders in this innovation and who are the key recipients? How doesthis funding split between various topics and value chains? What proportion of these funds support Sustainable Agricultural Intensification (SAI)? And how is SAI innovation funding split across different parts of the agriculture sector funding and innovation canvas?
Increasing investment and spending in agricultural innovation is not enough to meet Sustainable Development Goal (SDG) targets of ending poverty and hunger because the effectiveness of investments in low- and middle-income (LMI) countries is affected by the low quality of infrastructure and services provided, and by different norms and practices that create a considerable gap between financing known technical solutions and achieving the outcomes called for in the SDGs.