The 2016 Global Agricultural Productivity Report advocates policies and innovations in five key areas to help the agriculture and food sectors manage uncertain seasons of fluctuating business cycles and climate change, while fostering competitiveness today and sustainable growth tomorrow.
IFPRI’s flagship report reviews the major food policy issues, developments, and decisions of 2016, and highlights challenges and opportunities for 2017 at the global and regional levels. This year’s report looks at the impact of rapid urban growth on food security and nutrition, and considers how food systems can be reshaped to benefit both urban and rural populations. Drawing on recent research, IFPRI researchers and other distinguished food policy experts consider a range of timely questions:
■ What do we know about the impacts of urbanization on hunger and nutrition?
il est possible et nécessaire aujourd’hui d’opérer un bilan du développement durable (DD) en s’appuyant sur les formes concrètes qu’il a prises depuis plus de vingt ans. Malgré les discussions, interrogations ou critiques que le terme a suscitées, il est sans conteste, depuis la conférence de Rio en 1992, l’horizon normatif des projets, programmes et politiques d’aide publique au développement qui opèrent concrètement sur les territoires, et il accompagne maintenant les stratégies d’entreprise.
This paper comparatively analyzes the structure of agricultural policy development networks that connect organizations working on agricultural development, climate change and food security in fourteen smallholder farming communities across East Africa, West Africa and South Asia.
Development education, it combines various methodologies of education to promoting knowledge, so that agriculture sector needs development education to revive productivity through agriculture. ICT (Information communication technology) help to provide knowledge to the door step of farmers.
The aim of this study is to conduct a comprehensive analysis of Russian grain production, to determine country’s production potential and its possibility to remain one of the major grain producers on the world market. On the one hand was estimated the technical efficiency during the period of transition to the market economy. By applying a novel approach to the estimation of production efficiency on a regional level, we assess the grain production potential and determine factors that influence productivity beyond the control of the farmers.
The aim of this paper is to propose an innovative operational framework that couples life cycle assessment (LCA) and a participatory approach to overcome these issues. The first step was to conduct a progressive participatory diagnosis of the socio-ecological structure of the rural territory and to characterise the main cropping systems. The results of the diagnosis and other data were progressively triangulated, validated and consolidated with the stakeholders at the territorial level. The paper discusses the quality and validity of data obtained using a participatory approach.
The IFAD-NUS project, implemented over the course of a decade in two phases, represents the first UN-supported global effort on neglected and underutilized species (NUS). This initiative, deployed and tested a holistic and innovative value chain framework using multi-stakeholder, participatory, inter-disciplinary, pro-poor gender- and nutrition-sensitive approaches.
Fall Armyworm (Spodoptera frugiperda), or FAW, is an insect native to tropical and subtropical regions of the Americas. In the absence of natural controls or good management, it can cause significant damage to crops. It prefers maize, although it can feed on more than 80 additional species of crops including rice, sorghum, millet, sugarcane, vegetable crops and cotton.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.