The overall objective of the technical workshop was to present the guidelines on AIS and EAS assessments, the results at country level and to design and develop a framework of indicators to complement those assessments. Specific objectives were to:
Esta obra está enmarcada en el Plan de Acción 2018-2021 de la Facultad de Ciencias Agrarias, en el reto “Aportar al Sistema Nacional de Innovación Agropecuaria integrando la investigación y la extensión”, el cual tiene como propósito interconectar la investigación, la extensión y la innovación para mejorar el relacionamiento con el sector productivo, fortalecer las alianzas público-privadas nacionales e internacionales y las redes del conocimiento y gestionar la innovación, por medio de la creación del Centro de Innovación Agropecuaria, con el propósito de mejorar los procesos de gestión de
To determine whether a farmer’s accessibility predicts the delivery of extension services, this study used banana Xanthomonas wilt (BXW) disease-management advisory as a typical case with which to collect extension-delivery information from 690 farmers, distinguished by their respective accessibility. Cost–distance analysis was applied to define each farmer’s accessibility. The results revealed that a farmer’s accessibility does not predict extension delivery to that farmer in all forms of the examined extension parameters.
The national assessment of the agricultural innovation system (AIS) in Malawi was conducted using a framework of four types of analyses: functional, structural, capacity and enabling environment analysis. The approach included five case studies that addressed three methods including the use of indigenous methods for fall armyworm (FAW) control in Farmer Field Schools (FFS), livestock transfer programs, and a horticulture marketing innovation platform in Mzimba, Ntchisi, Balaka, and Thyolo districts.
This report introduces the reader to the concept of agricultural innovation systems (AIS) and the TAP-AIS project being implemented by FAO in nine countries, including Lao People's Democratic Republic (Lao PDR). The results of the AIS assessment for Lao PDR are presented, highlighting key barriers and opportunities for agricultural innovation in the country.
Decision support systems (DSS) have long been used in research, service provision and extension. Despite the diversity of technological applications in which past agricultural DSS canvass, there has been relatively little information on either the functional aspects of DSS designed for economic decisions in irrigated cropping, or the human and social factors influencing the adoption of knowledge from such DSS.
This work examined the determinants of the adoption of improved Irish potato technologies by farmers in three divisions of the Western Region of Cameroon. Data were collected from 170 farmers from 14 villages in our study area using a mixed-method approach—structured questionnaires, focus group discussion, key informant interviews, and participatory observations with individual farmers and farmers belonging to cooperative and common initiative groups. The study employed descriptive statistics and regression analysis to assess the adoption status of farmers and its determinants.
This document presents a proposed methodology for public expenditure review and analysis for climate change adaptation and mitigation in the agriculture sector (PERCC) and its application to a case study of Kenya. It starts by explaining the basic methodological concepts, classification and labelling of public expenditures that allow for calculating spending in agriculture related to climate change adaptation and mitigation.
We present a model for research and development (R&D) investment in food innovations based on new plant engineering techniques (NPETs) and traditional hybridization methods. The framework combines uncertain and costly food innovation with consumers' willingness to pay (WTP) for the new food. The framework is applied with elicited WTP of French and US consumers for new improved apples. NPETs may be socially beneficial under full information and when the probability of success under NPETs is relatively high. Otherwise, the traditional hybridization is socially optimal.
The author shares her experience of participating in a training that was organized by the Tropical Agriculture Platform – Agricultural Innovation Systems (TAP-AIS) project, ‘Developing Capacities in Agricultural Innovation Systems: Scaling up the Tropical Agriculture Platform Framework’, implemented by FAO’s Research & Extension Unit, funded by the European Union as a component of the ‘Development Smart Innovation through Research in Agriculture (DeSIRA): Towards Climate-relevant Agricultural and Knowledge Innovation Systems’ initiative.