This Practical Guide to Capacity Development in a Sector Context has been compiled to accompany Asian Development Bank (ADB)’s Capacity Development Framework and Action Plan. Its purpose is to provide ADB staff and other development practitioners with a set of tools and instruments that can be used to guide capacity development processes. The range of tools and instruments compiled in this guide starts from a sector-wide perspective (political economy and governance features) then moves down to capture individual stakeholders’ perspective.
Ce document offre un cadre de réflexion sur le renforcement des capacités, établi à partir des principaux enseignements tirés de l’expérience, qu’elle soit positive ou négative.
Iron deficiency is a widespread nutritional problem in developing countries, causing impaired physical activity and cognitive development, as well as maternal mortality. Although food fortification and supplementation programmes have been effective in some countries, their overall success remains limited. Biofortification, that is, breeding crops for higher micronutrient content, is a relatively new approach. We propose a methodology for ex-ante impact assessment of iron biofortification, which builds on disability-adjusted life years (DALYs) and a large household data set.
This paper has been prepared by S. Mohan, Professor of Agricultural Entomology at the TamilNadu Agricultural University (Coimbatore, TamilNadu, India), as a success story that can be shared in Educational Programme for Capacity Development for Agricultural Innovation. The document discusses technologies for timely detection of insects in the stored products and timely control measures.
In the post-harvest area and in agriculture research in general, both in India and internationally, policy attention is returning to the question of how innovation can be encouraged and promoted and thus how impact on the poor can be achieved. This publication assembles several cases from the post-harvest sector. These provide examples of successful innovation that emerged in quite different ways. Its purpose is to illustrate and analyze the diversity and often highly context-specific nature of the processes that lead to and promote innovation.
This paper provides a chronology and overview of events and policy initiatives aimed at addressing irrigation sustainability issues in the San Joaquin River Basin (SJRB) of California. Although the SJRB was selected in this case study, many of the same resource management issues are being played out in arid, agricultural regions around the world.
Within agricultural innovation systems (AIS), various stakeholder groups inevitably interpret ‘innovation’ from their own vantage point of privilege and power. In rural developing areas where small-scale and subsistence farming systems support livelihoods, dominant policy actors often focus heavily on participatory modernization and commercialization initiatives to enhance productivity, access, and quality. However, existing social hierarchies may undermine the potential of such initiatives to promote inclusive and sustainable farmer-driven innovation.
Les Champs-Ecoles des Producteurs (CEP) sont une approche d’apprentissage participatif utilisée dans de nombreux différents contextes à travers le monde. Un CEP rassemble un groupe d'agriculteurs, d'éleveurs ou de pêcheurs, dans le but d’apprendre à s'orienter vers des pratiques de production plus durables. C’est un espace d’apprentissage collectif et concret, qui permet aux populations locales d'améliorer leurs compétences en matière d'analyse critique et de prise de décisions.
CABI’s Plantwise programme runs local plant clinics in 24 countries across Africa, Asia and Latin America where trained ‘plant doctors’ provide on-the-spot diagnosis and advice for farmers who bring samples to the clinics. A database that records each consultation and shares knowledge across clinics and countries continually builds the ability of the programme to respond to farmers’ needs. The programme embodies key principles of an innovation systems approach.
Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the total yield, resulting in a decrease in the farmers' profits. To overcome this problem, many re-searchers have presented different state-of-the-art systems based on Deep Learning and Machine Learningapproaches. However, most of these systems either use millions of training parameters or have low classificationaccuracies.