Innovation learning platforms have their roots in the agricultural innovation systems (AIS) approach. AIS emphasizes a systems view of agricultural innovations and conceptualizes an innovation system as all individuals and organizations that keep on interacting in producing and using knowledge and the institutional context of knowledge sharing and learning. Research creates knowledge and technology; but innovation process goes further to include putting that knowledge into use.
This report finds ground for a temperate optimism regarding the future role of smallholder agriculture in helping Asian countries delivering on Agenda 2030. Growth rates of the region’s major economies remain buoyant. Notwithstanding the risks associated with a new global crisis or originating from the instability of financial markets, economic growth is expected to remain strong in the decade to come.
This presentation was given for the SEARCA Forum-workshop on Platforms, Rural Advisory Services, and Knowledge Management: Towards Inclusive and Sustainable Agricultural and Rural Development, Los Banos, 17-19 May 2016. It briefed innovation, innovation systems and multistakeholder processes (innovation platforms and learning alliances).
This paper examines different practical methods for stakeholders to analyse power dynamics in multi-stakeholders processes (MSPs), taking into account the ambiguous and uncertain nature of complex adaptive systems. It reflects on an action learning programme which focused on 12 cases in Africa and Asia put forward by 6 Dutch development non-governmental organizations (NGOs).
A value chain study on sweet potato was conducted in 11 districts of Malawi across all the three regions to analyze and identify bottlenecks and inherent opportunities for possible investments for upgrading and development of the value chain. The study applied both quantitative and qualitative methods to collect primary data from 94 farmers belonging to 7 farmer groups using Focus Group Discussions (FGDs), 14 traders and 16 key informants comprising policy makers, NGO representatives and scientists from both local and international research institutions.
El propósito del análisis presentado en este documento es estudiar algunos elementos en el contexto de unas cadenas (tomate y pepino) y un sector económico (hortalizas) priorizados por el Gobierno de la República de El Salvador. Esto se ha logrado gracias a la aplicación piloto de una herramienta cuantitativa desarrollada por el departamento de Desarrollo Económico y Social (ES) de FAO en Roma. Cabe destacar que este análisis no pretende ser un estudio exhaustivo de la cadena del tomate y pepino en el país sino que un ensayo para demonstrar el potencial de la herramienta.
The International Fund for Agricultural Development (IFAD) financed the second Cordillera Highland Agricultural Resource Management Project (CHARMP2), in areas where poverty is most severe among indigenous peoples in the highlands of the Cordillera Region in northern Philippines. The aim is to reduce poverty and improve the livelihoods of indigenous peoples living in farming communities in the mountainous project area. The indigenous peoples consist of many tribes whose main economic activity is agriculture.
evelopment projects on interventions to reduce postharvest losses (PHL) are often implemented largely independently of the specific context and without sufficient adaptation to the needs of people who are supposed to use them. An approach is needed for the design and implementation of specific, locally owned interventions in development projects. This approach is based on Participatory Development and includes Living Lab and World Cafés. We applied the approach in a case study on reducing PHL in tomato value chains in Nigeria. The approach consists of nine steps.
Soil texture is a key soil property influencing many agronomic practices including fertilization and liming. Therefore, an accurate estimation of soil texture is essential for adopting sustainable soil management practices. In this study, we used different machine learning algorithms trained on vis–NIR spectra from existing soil spectral libraries (ICRAF and LUCAS) to predict soil textural fractions (sand–silt–clay %). In addition, we predicted the soil textural groups (G1: Fine, G2: Medium, and G3: Coarse) using routine chemical characteristics as auxiliary.
This study examines the contributions of IFPRI over the last 10 years to policy development, training, and capacity-strengthening activities with Malawi, focused particularly on addressing the chronic food insecurity and malnutrition that has prevailed for the last 60 years.The paper is divided into five sections.