Fall Armyworm (Spodoptera frugiperda), or FAW, is an insect native to tropical and subtropical regions of the Americas. In the absence of natural controls or good management, it can cause significant damage to crops. It prefers maize, although it can feed on more than 80 additional species of crops including rice, sorghum, millet, sugarcane, vegetable crops and cotton.
In Asia and the Pacific, the UN’s Food and Agriculture Organization (FAO) is working with member countries to leverage breakthroughs in information and communication technologies (ICT) to fight hunger, improve nutrition and counter the effects of climate change and extreme weather events that can devastate farmers and their crops. In the Philippines, a country prone to typhoons, aerial drones are taking to the sky to map out at-risk areas of agricultural land to mitigate risk. This innovative practice is also able to quickly assess damages when a disaster strikes.
The question of how agricultural research can best be used for developmental purposes is a topic of some debate in developmental circles. The idea that this is simply a question of better transfer of ideas from research to farmers has been largely discredited. Agricultural innovation is a process that takes a multitude of different forms, and, within this process, agricultural research and expertise are mobilised at different points in time for different purposes. This paper uses two key analytical principles in order to find how research is actually put into use.
Rural Advisory Services (RAS) are increasingly recognised as critical to agricultural and rural development. They provide rural communities with wide range of skills and knowledge and facilitate their interactions among the different actors to help them access support and services required for improving their livelihoods. Family Farmers are one of the important clients of RAS as they are the most predominant type of farmers worldwide.
African agriculture is currently at a crossroads, at which persistent food shortages are compounded by threats from climate change. But, as this book argues, Africa can feed itself in a generation and help contribute to global food security. To achieve this Africa has to define agriculture as a force in economic growth by: advancing scientific and technological research; investing in infrastructure; fostering higher technical training; and creating regional markets.
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.
Cette publication offre de nombreux exemples concrets détaillant différentes manières de réengager les jeunes dans le secteur agricole. Elle montre à quel point des programmes éducationnels sur mesure peuvent offrir aux jeunes les compétences et la perspicacité nécessaires pour se lancer en agriculture et adopter des méthodes de production respectueuses de l’environnement. Beaucoup des approches ou des initiatives décrites dans cette publication sont issues des jeunes eux-mêmes.
Public institutions involved in research that aims to strengthen the productivity, profitability and adaptiveness of industries face a multiplicity of challenges when managing for the emergence of cost effective solutions to problems. We reflect upon the learnings of a Government sponsored Visiting Fellow’s programme that we describe as a knowledge management (KM) intervention within Australia’s primary industries Research, Development and Extension (R, D and E) system.
Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions.
The impact of the COVID-19 pandemic will vary for different groups of rural population, with the highest impact expected to be on farmers and other vulnerable groups, especially women and youth. Targeted support is feasible only by activating a network of actors or organizations within agricultural innovation systems (AIS) and promoting customized technologies and practices suitable for location specific contexts.