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.
This report assesses trends in investments, human resource capacity, and outputs in agricultural research in SSA, excluding the private (for-profit) sector. The analysis uses information collected by Agricultural Science and Technology Indicators (ASTI)—led by the International Food Policy Research Institute (IFPRI) within the portfolio of the CGIAR Research Program on Policies, Institutions, and Markets (PIM).
This study introduces a framework for managing information flow in innovation systems. An organisation's capacity to receive information, to share it with others and to learn from it is assumed to be the key factor that shapes the flow patterns and, hence, the performance of the innovation system concerned. The framework is applied to characterise the information structure underlying the agricultural innovation system of Azerbaijan and to develop an information strategy for the system to accelerate the information flow.
Genetic improvement on local breeds kept by small farmers in developing countries is challenging. Even though good pedigree and performance recording is crucial and an important component of breeding programs, it remain difficult or next to impossible under conditions of subsistence livestock farming. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
The presented model of operations capacity planning allows obtaining quantitative dimensions of the service system parameters for Administrative Services Centre. A methodology for the practical application of this model has also been presented here. The present paper aims at offering support for operations managers in the service sector for decision making regarding the operations capacity. The paper was presented at 7th annual International scientific conference "New dimensions in the development of society", held in Jelgava, Latvia, in 2011.
Here, it is described a new participatory protocol for assessing the climate-smartness of agricultural interventions in smallholder practices. This identifies farm-level indicators (and indices) for the food security and adaptation pillars of CSA. It also supports the participatory scoring of indicators, enabling baseline and future assessments of climate-smartness to be made. The protocol was tested among 72 farmers implementing a variety of CSA interventions in the climate-smart village of Lushoto, Tanzania.
The Colombian Ministry of Agriculture Colombia, an international research center and a national farmers’ organization developed a data-driven agricultural program that: (i) compiles information from multiple sources; (ii) interprets that data; and (iii) presents the knowledge to farmers through the local advisory services. Data was collected from multiple sources, including small-scale farmers. Machine learning algorithms combined with expert opinion defined how variation in weather, soils and management practices interact and affect maize yield of small-scale farmers.