Argentine agriculture has undergone significant transformations over the past three decades. After a long period of stagnant production and productivity, starting in the early 1970s, a number of independent but interconnected events fostered a new technological cycle that induced rapid growth in cereals and oilseeds production. Zero tillage and the introduction of genetically modified soybean varieties were key elements of this change. Argentina reached a leading position across agricultural commodity markets.

This methodological guide was initially developed and used in Latin America and the Caribbean-LAC (Honduras, Nicaragua, Colombia, Peru, Venezuela, Dominican Republic), and was later improved during adaptation and use in eastern African (Uganda, Tanzania, Kenya, Ethiopia) through a South-South exchange of expertise and experiences. The aim of the methodological guide is to constitute an initial step in the empowerment of local communities to develop a local soil quality monitoring and decision-making system for better management of soil resources.

This background note for the development of an AIS Investment Sourcebook provides a menu of tools and guidance to invest in agricultural innovation in different contexts. The content is drawn on tested good practice examples and innovative approaches with emphasis on lessons learned, benefits and impacts, implementation issues, and replicability

The aim of this report is to provide a detailed review of documented social learning processes for climate changeand natural resource managementas described in peer-reviewed literature. Particular focus is on identifying (1) lessons and principles, (2) tools and approaches, (3) evaluation of social learning, as well as (4) concrete examples of impacts that social learning has contributed to.

During May 2010 the International Centre for Tropical Agriculture (CIAT) hosted two events related to knowledge management (KM): The Knowledge Share Fair for Latin America and the Caribbean, funded by the Food and Agriculture Organization of the United Nations (FAO), and a regional meeting of the Knowledge Management for Development (KM4Dev) community. The Fair was attended by 200 professionals from more than 70 organizations and 18 countries and showcased more than 40 experiences related to KM in agriculture, development and food security.

In this chapter the authors compute measures of total factor productivity (TFP) growth for developing countries and then contrast TFP growth with technological capital indexes. In developing these indexes, the authors incorporate schooling capital to yield two new indexes: Invention-Innovation Capital and Technology Mastery. They find that TFP performance is strongly related to technological capital and that technological capital is required for TFP and cost reduction growth.

This book examines how agricultural innovation arises in four African countries – Ghana, Kenya, Tanzania, and Uganda – through the lens of agribusiness, public policies, and specific value chains for food staples, high value products, and livestock. Determinants of innovation are not viewed individually but within the context of a complex agricultural innovation system involving many actors and interactions.

The paper aims to identify barriers to the development of Learning and Innovation Networks for sustainable agriculture (LINSA). In such networks, social learning processes take place, and knowledge about sustainable agriculture is co-produced by connecting between the different frames and social worlds of the stakeholders with the help of boundary objects. Studying such processes at the interface between different knowledge spheres of research, policy and practice requires a specific methodology.

This paper discusses a range of approaches and benchmarks that can guide future design of value chain impact evaluations. Twenty studies were reviewed to understand the status and direction of value chain impact evaluations. A majority of the studies focus on evaluating the impact of only a few interventions, at several levels within the value chains. Few impact evaluations are based on well-constructed, well-conceived comparison groups. Most of them rely on use of propensity score matching to construct counterfactual groups and estimate treatment effects.

This note offers a conceptual framework for dealing with 1) institutional and capacity assessment; and 2) capacity development issues, mainly in the public sector areas. This framework will be particularly useful in the in the preparation of support to sector programmes and budget support exercises.