Following the remarkable success of performance testing in the commercial sector, the Agricultural Research Council's Animal Improvement Institute (ARC–AII) initiated a beef cattle performance testing scheme for smallholder farmers in 1996. The scheme, which became known as Kaonafatsho ya Dikgomo (Sotho for animal improvement), has been running well in the Northern and North West Provinces and is set to spread gradually to the rest of the country.
This Economic and Sector Work paper, “Enhancing Agricultural Innovation: How to Go Beyond the Strengthening of Research Systems,” was initiated as a result of the international workshop, “Development of Research Systems to Support the Changing Agricultural Sector,” organized by the Agriculture and Rural Development Department of the World Bank in June 2004 in Washington, DC.
The CGIAR Research Program on Aquatic Agricultural Systems (AAS) is a research in development program which aims to foster innovation to respond to community needs, and through networking and social learning to bring about development outcomes and impact at scale. It aims to reach the poorest and most vulnerable communities that are dependent upon aquatic agricultural systems. AAS uses monitoring and evaluation to track progress along identified impact pathways for accountability and learning.
The present case study investigated a policy-induced agricultural innovation network in Brandenburg.
This report describes the 2012 NAIS Assessment was piloted in 4 countries: Botswana, Ghana, Kenya and Zambia. Data were collected through a survey questionnaire, open-ended interview questions, and data mining of secondary sources. A team led by a national coordinator took charge of data collection from various partner organizations in each country.
The goal of both of this report is to draw lessons from Katalyst’s experience which could be used more broadly. As the private sector assumes a more significant role in the architecture of development it is important to understand more clearly what benefits companies might get from greater engagement; and also what actions work best to facilitate inclusive market approaches.
The overall objective of the Comprehensive Assessment of the Agricultural Sector (CAAS) is to provide an evidence base to enable appropriate strategic policy responses by the Government of Liberia (GoL) and its development partners in order to maximize the contribution of the agriculture sector to the Government's overarching policy objectives. Given the strong relationship between growth in agricultural productivity and poverty reduction, future efforts in Liberia need to focus on productivity enhancing measures with a pro-poor focus that increase incomes.
Global agriculture will face multiple challenges over the coming decades. It must produce more food to feed an increasingly affluent and growing world population that will demand a more diverse diet, contribute to overall development and poverty alleviation in many developing countries, confront increased competition for alternative uses of finite land and water resources, adapt to climate change, and contribute to preserving biodiversity and restoring fragile ecosystems.
The purpose of this paper is to summarize the challenges and the practical successes that a selected number of countries are experiencing in moving towards 'climate-smart' agriculture while also meeting the food requirements of a growing population, broader economic development and green growth objectives. It complements papers prepared in 2010 on technologies and policy instruments, research, and farmers' perspectives.
This report seeks to understand the successes, challenges and opportunities of Cambodia’s agricultural transformation over the past decade to derive lessons and insights on how to maintain future agricultural growth, and particularly on the government’s role in facilitating it. It is prepared per the request of the Supreme National Economic Council and the Ministry of Agriculture Forestry and Fisheries and is based on the primary farm data surveys from 2005 and 2013, and the secondary data from various sources.