There is an ongoing debate on what constitutes sustainable intensification of agriculture (SIA). In this paper, we propose that a paradigm for sustainable intensification can be defined and translated into an operational framework for agricultural development. We argue that this paradigm must now be defined—at all scales—in the context of rapidly rising global environmental changes in the Anthropocene, while focusing on eradicating poverty and hunger and contributing to human wellbeing.
The purpose of this study was to generate information that provide comprehensive understanding of the constraints of tree-crop-livestock farming system in four sites of the Africa RISING project in Ethiopia. The study identified relevant institutions in the study locations to develop modalities for establishment of Innovation Platform (IP). The identified institutions were gathered together to identify and prioritize problems and consult on the improvement of mixed farming system in their area.
African farming systems are highly heterogeneous: between agroecological and socioeconomic environments, in the wide variability in farmers’ resource endowments and in farm management. This means that single solutions (or ‘silver bullets’) for improving farm productivity do not exist. Yet to date few approaches to understand constraints and explore options for change have tackled the bewildering complexity of African farming systems. In this paper we describe the Nutrient Use in Animal and Cropping systems – Efficiencies and Scales (NUANCES) framework.
The Africa Research In Sustainable Intensification for the Next Generation (Africa RISING) program comprises three research-for-development projects supported by the United States Agency for International Development as part of the U.S. government’s Feed the Future initiative.
The workshop was attended by over 50 people including partners from CGIAR centres, Regional Research Institutes and Centres, Universities, woredas and kebeles working with Africa RISING. The workshop discussed the use of different approaches, methods and tools for the efficient and
sustained functioning of innovation platforms (IPs) that could improve research and subsequent scaling up of suitable technologies and value chains to improve livelihoods.
This is a chapter of the book Innovation Platforms for Agricultural Development edited by Iddo Dror, Jean-Joseph Cadilhon, Marc Schut, Michael Misiko and Shreya Maheshwari.
The provision of basic market information is a service that aims to increase the efficiency of agricultural markets and contribute towards overcoming basic issues of market failure based on asymmetrical access to information. However, debate on the need for long-term support to a market information system (MIS) continues. A quantitative and qualitative survey was undertaken to provide a measure of accessibility, usefulness and utility of the current MIS, and to access how this type of service may be financed and improved in the future.
The presentation was given at the ILRI Policy, Trade and Value Chains Program (May–November 2014) Seminar, ILRI Nairobi, 21 November 2014. It included the introduction of Dairy Development Forum, background and purpose, literature review, methodology, results and discussions, and conclusions.
As calls for bolstering environmental services on croplands have grown more insistent during the past two decades, the search for ways to foster sustainable, reduced input agriculture has become more urgent. In this context authors re-examine by means of a meta-analysis the argument, first proposed by Robert McC. Netting, that small scale, mixed crop – livestock farming, a common livelihood among poor rural peoples, encourages environmentally sustainable agricultural practices.
Innovations generally arise out of a network of actors and relationships and network structure determines how effective networks are at fostering innovation. This paper (Part II) presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia. The prototype method used is based on social network analysis methodology. This paper concludes with a final section to identify lessons learnt and makes recommendations for future research.