The Progress towards Sustainable Agriculture initiative (PROSA) is a framework that seeks to complement ongoing efforts on the Sustainable Development Goals (SDGs), and particularly indicator 2.4.1, to support country-level assessments using data already available at the national level. Making agriculture more sustainable – productive, environmentally friendly, resilient and profitable is fundamental, as agriculture remains the main source of livelihood for the majority of the world’s poor and hungry.
The objective of this study is to evaluate the ability of soil physical characteristics (i.e., texture and moisture conditions) to better understand the breeding conditions of desert locust (DL). Though soil moisture and texture are well-known and necessary environmental conditions for DL breeding, in this study, we highlight the ability of model-derived soil moisture estimates to contribute towards broader desert locust monitoring activities.
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 "Renforcer les capacités des systèmes d'innovation agricole: application et adaptation de l’approche de la plateforme d'agriculture tropicale (TAP-AIS)" vise à stimuler l'innovation pour la transformation des systèmes agricoles et alimentaires des pays partenaires en vue de mieux résister aux effets du changement climatique. Il intéresse ainsi le public technique ou pas, les jeunes et les media.
Dans de nombreux pays, les décideurs ont besoin d'informations pertinentes sur les systèmes d'innovation agricole (SIA) pour guider la formulation des stratégies et des instruments politiques de soutien à l'innovation.
L’une des avancées les plus importantes dans le domaine de l’observation de la terre est la découverte des indices spectraux, ils ont notamment prouvé leur efficacité dans la caractérisation des surfaces agricoles, mais ils sont généralement définis de manière empirique. Cette étude basée sur l’intelligence artificielle et le traitement du signal, propose une méthode pour trouver un indice optimal. Et porte sur l’analyse d’images issues d’une caméra multi-spectrale, utilisée dans un contexte agricole pour l’acquisition en champ proche de végétation.
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.
This paper addresses how co-producing knowledge can assist local farmers in reshaping their territories into sustainable farming systems. We describe the emergence and consolidation of an agroforestry system in an Eastern Amazon forest frontier, unpacking the co-production of a new farming system over recent decades. Instead of assuming pre-defined categories (e.g., traditional/technical, local/external), the analysis focuses on interactions among knowledge holders and how multiple knowledge sources are intercalated.
This paper contends that the exclusion of millions of poor from agricultural development gains is inexorably linked to the innovation system features that have evolved over time. An oft repeated lament of the Government of India about the inadequacy of reforms in agricultural research and extension, is used to explore the structure and institutions of agricultural innovation. Three main components of the agricultural innovation system, are the agricultural research and extension actors, the farming communities, and policy making agencies.
Where CGIAR breeding programs rely on the private sector for the multiplication and distribution of improved cultivars, persistent challenges have dampened their impact on varietal adoption and turnover rates. Part of the problem is that research and practice in CGIAR and among its national breeding program partners tend to treat the private sector as a vehicle for seed delivery, rather than as commercial businesses facing a range of unique constraints and threats.