While the Agricultural Science and Technology Indicators (ASTI) initiative provides data and analysis of domestic public and private spending on agricultural research and development for a wide range of developing countries, the literature pays little attention, if any, to foreign assistance to agricultural, fishing and forestry research and agricultural extension. The objective of the present study is to fill this gap.
Agricultural innovation in low-income tropical countries contributes to a more effective and sustainable use of natural resources and reduces hunger and poverty through economic development in rural areas. Yet, despite numerous recent public and private initiatives to develop capacities for agricultural innovation, such initiatives are often not well aligned with national efforts to revive existing Agricultural Innovation Systems (AIS).
A paradigm shift is needed to reposition the world’s AFS from being an important driver of environmental degradation to being a key contributor for the global transition to sustainability. Such a transformation can only happen through both generation of new knowledge and enhanced translation of knowledge into use. This achievement requires the generation of new knowledge and enhanced translation of knowledge into use, entailing considerable efforts in terms of research and innovation.
This paper investigates the introduction of Integrated Pest Management (IPM) in Canino's area (Italy), from an agricultural innovation system (AIS) perspective focusing on the roles of the innovation actors and the innovation impact pathway. The IPM research in Canino was conducted with a wide range of actors including research, advisory services, producer cooperatives and the private sector in a favourable policy environment facilitating the fast and wide adoption of IPM.
The paper, prepared for the "High Level Policy Dialogue on Investment in Agricultural Research for Sustainable Development in Asia and the Pacific" (Bangkok Thailand; 8-9 December 2015), presents the Common Framework on Capacity Development for Agricultural Innovation Systems (CDAIS).The framework is a core component of the Action Plan of the TAP, a G20 Initiative, aiming to increase coherence and effectiveness of capacity development for agricultural innovation that lead to sustainable change and impact at scale.
The project Small Farms, Small Food Business and Sustainable Food Security (SALSA) intends to assess the role of small farms and small food business in terms of food production and food security. One important first step in doing this is to test and develop methods and tools able to produce accurate and useful information about small farms.
This deliverable is a report on the main methodological steps implemented in the framework of the Small Farms, Small Food Business and Sustainable Food Security (SALSA) project in task 2.3 of Work Package 2 (WP2) to produce the Output 3, which is a crop type map in small farms context in each reference region (see D.2.4 report pag. 5).
This document presents the small farm typologies developed from SALSA's sample (n=892) and provides a detailed comparative analysis on the key characteristics and livelihood strategies of each of the types, identifying similarities, differences and trends.
This document presents an in-depth comparative assessment of the local and regional food systems analysed in SALSA. Its aim is to improve the understanding of the current and potential role of SF in regional Food and Nutrition Security (FNS). This deliverable is a synthesis report on the main insights gained from the analysis completed for the 30 reference regions.
It is clear that any definition of a small farm needs to be based on national and regional realities. Definitions involving only the criterion of farm size have universal appeal as they are relatively easy to apply and allow simple comparisons across countries and world regions. However, they don't capture all the complexities of farming. Definitions involving additional criteria to farm size are more meaningful, particularly those including indicators of the farm economic output, but data availability is often a limitation (Ruane, 2016).