This brochure presents the five-year TAP-AIS project (2019-2024) funded by the European Union under the DeSIRA Initiative and implemented by the Food and Agriculture Organization (FAO) of the United Nations. The project has the main objective to strengthen capacities to innovate in national agricultural innovation systems (AIS) in the context of climate-relevant, productive, and sustainable transformation of agriculture and food systems in Africa, Latin America, Asia and the Pacific.
Over the past few decades, some countries in Asia have been more successful than others in addressing poverty and malnutrition. The key question is what policies, strategies, legislation and institutional arrangements have led to a transformed agricultural sector, effectively contributing to poverty alleviation and addressing malnutrition. The great majority of national policymakers within and outside the Asia-Pacific region are keen to understand the causes of agricultural development and transformation in successful countries in Asia.
In Lao People's Democratic Republic (PDR), agricultural innovation has the potential to improve livelihoods of farmers and rural people, improve food and nutrition security, and allow for sustainable management of natural resources. In order to enable innovation, a well-functioning national Agriculture Innovation System (AIS) should encourage better coordination among the different stakeholders, including national organizations and the private sector.
Cambodia’s development is strongly influenced by growth in the agriculture sector. In this context, the modernization of agriculture has been highly regarded by the government as a long-term strategy to transform traditional labour-based agriculture into technology-based and with that to effectively enhance the country’s further regional integration within the Association of Southeast Asian Nations. In support of this strategic vision, a participatory assessment of the Agricultural Innovation Systems (AIS) was conducted in coordination with the General Department of Agriculture (GDA) and su
This report summarizes studies conducted in a framework of TAP-AIS project implemented by FAO’s Research and Extension Unit, and funded by the European Union as a component of the European Union initiative on “Development Smart Innovation through Research in Agriculture” (DeSIRA).
The creation of commercialization opportunities for smallholder farmers has taken primacy on the development agenda of many developing countries. Invariably, most of the smallholders are less productive than commercial farmers and continue to lag in commercialization. Apart from the various multifaceted challenges which smallholder farmers face, limited access to extension services stands as the underlying constraint to their sustainability.
Due to the increasing gap between input costs and the final prices they receive for their produce, Indian farmers have been increasingly affected by the current agrarian crisis. It is within this context that Zero Budget Natural Farming (ZBNF) - a farming method promising low to zero input costs - has been gaining momentum.
This paper contends that the exclusion of millions of poor from agricultural development gains is inexorably linked to the innovation system features that have evolved over time. An oft repeated lament of the Government of India about the inadequacy of reforms in agricultural research and extension, is used to explore the structure and institutions of agricultural innovation. Three main components of the agricultural innovation system, are the agricultural research and extension actors, the farming communities, and policy making agencies.
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.
Structural transformation of agriculture typically involves a gradual increase of mean farm sizes and a reallocation of labor from agriculture to other sectors. Such structural transformation is often fostered through innovations in agriculture and newly emerging opportunities in manufacturing and services. Here, we use panel data from farm households in Indonesia to test and support the hypothesis that the recent oil palm boom contributes to structural transformation. Oil palm is capital-intensive but requires much less labor per hectare than traditional crops.