The purpose of this report is to provide some of the groundwork in answering the question of how the CGIAR system and other public agricultural research organisations should adapt and respond to an era of transformation framed by the SDGs. It does this by exploring the way in which this transformation agenda reframes agricultural research and innovation.
Este folleto plantea una metodología de evaluación de impactos, y su aplicación para analizar los productos e impactos de los proyectos de investigación, validación y transferencia de tecnología que la Fundación Guanajuato Produce A.C. ha financiado durante el periodo 2005 - 2010.
El presente trabajo se realizó en el 2008 y tuvo como objetivo determinar las necesidades de investigación en la cadena de alfalfa en Hidalgo. Se utilizó el enfoque de cadenas productivas y además se realizaron las siguientes cinco etapas: i) Caracterización de la cadena, ii) Identificación de los factores críticos, iii) Identificación de las demandas de investigación, iv) Identificación de la Oferta de la investigación, e v) Identificación de las necesidades de investigación
Con el objetivo identificar los factores que inciden en la innovación y la eficiencia de las unidades de producción bovinas de doble propósito en el estado de Veracruz, se integró información de 91 ranchos que participaron en un programa de asistencia técnica, se capturó información sobre uso de 17 componentes tecnológicos y sobre producción de leche por vaca, también se integró información de factores socioeconómicos. Se aplicó un análisis de varianza para la identificación de factores.
Agricultural innovation is an essential component in achieving the SDG and accelerating the transition to more sustainable and resilient farming systems across the world. Innovations generally emerge from collective intelligence and action, which requires effective agricultural innovation systems (AIS). An AIS perspective has been widely adopted, but the analysis of AIS, especially at country level, remains a challenge. The need for and potential of a diagnostic tool for AIS analysis is currently receiving attention in the global agricultural policy debate.
Extension and advisory services (EAS) play a key role in facilitating innovation for sustainable agricultural development. To strengthen this role, appropriate investment and conducive policies are needed in EAS, guided by evidence. It is therefore essential to examine EAS characteristics and performance in the context of modern, pluralistic and increasingly digital EAS systems. In response to this need, the Food and Agriculture Organization of the United Nations (FAO) has developed guidelines and instruments for the systematic assessment of national EAS systems.
Extension and advisory services (EAS) play a key role in facilitating innovation processes, empowering marginalized groups through capacity development, and linking farmers with markets. Advisory services are increasingly provided by a range of actors and funded from diverse sources. With the broadened scope of EAS and the growing complexity of the system, the quantitative performance indicators used in the past (e.g. related to investment, staffing or productivity) are not adequate anymore to understand whether the system is well-functioning.