This presentation was realized for the GFAR workshop on "Adoption of ICT Enabled Information Systems for Agricultural Development and Rural Viability" (at IAALD-AFITA-WCCA World Congress, 2008). It presents lessons learned through linking research to extension, including examples from projects in Nigeria, Colombia, Uganda ,Costa Rica, Egypt and Bhutan.

This article starts by describing the evolution of innovation in agricultural research and cooperation for development, including an historical overview of agricultural research for development from green revolution to the re-discover of traditional knowledge. Then the authors analyze participation in innovation processes and make a comparison of innovation systems and platforms targeting the agri-food sector in developing countries. A particular focus is reserved to the European regional networks and to the experience of the USAID Middle East Water and Livelihoods Initiative.

This regional workshop was designed to strengthen the capabilities of representatives of NIFUs for analyzing the situations of their NAIS, and to use their national experiences to identify strengths, weaknesses, and threats/challenges affecting seven key areas influencing development of NAIS, namely: (i) strategy/policy, (ii) institutional aspects, (iii) stakeholders, (iv) content, (v) people, (vi) infrastructure, and (vii) financial aspects. Possible solutions for the key weaknesses and threats /challenges were defined by participants.

These proceedings relate to a regional workshop which was held in Muscat, Oman, in January 2008.

The purpose of this paper is to map some elements that can contribute to an IFAD strategy to stimulate and support pro-poor innovations. It is an initial or exploratory document that hopefully will add to an ongoing and necessary debate, and is not intended as a final position paper. The document is organized as follows.

Agriculture remains a key and sensitive economic sector in Egypt. Given contemporary geo-political concerns that limit access to international markets, it continues to remain responsible for the production of food and
fiber needed for a growing population. Efficacy in agricultural Extension Services (AES), within the broader scope of an agricultural innovation system, has the potential to assist in the government’s mandate, and

Disasters are increasing worldwide, with more devastating effects than ever before. While the absolute number of disasters around the world has almost doubled since the 1980s, the average number of natural disasters in Middle East and North Africa (MNA) has almost tripled over the same period of time. In the MNA, the interplay of natural disasters, rapid urbanization, water scarcity, and climate change has emerged as a serious challenge for policy and planning.

This paper illustrates already practiced models and strategies of high impact innovations around the world with particular respect to India. The shown examples of innovative businesses were selected based on four criteria reflecting their innovative character. Firstly, innovations need to fulfil a value for the life of people which exceeds the mere use of the product. Secondly, it requires good quality products or service for an affordable price even for lower income groups.

This presentation summarizes lessons learned as a result of developing Information and knowledge systems in Egypt in the last years.  The lessons are classified on the main topics discussed in International Consultation on Agricultural Research for Development and Innovation held in December 2009 in ICRISAT. Th

Four FFSs concerning integrated crop–livestock systems were implemented by a R&D project namely “Adaptation to Climate Change in West Asia and North Africa (WANA) Marginal Environments through Sustainable Crop and Livestock Diversification (ACC project)” during the summer season 2013 in three villages namely Village 4, Village 7 and Village 1750 in Sinai Peninsula. This study aimed to do the following: (1) assess the learning impacts of farmer field schools of integrated crop–livestock package and (2) explore the factors that affect the respondents’ learning index.