Digital technologies are slowly spreading in agriculture sectors globally. But their adoption is hampered by the digital divide which requires significant public investments, improved policy and incentive frameworks to be bridged. Only after that, digital transformation will take place at scale. DAP is meant to assess the country's readiness for this digital transformation by identifying main bottlenecks, opportunities and risks for digital transformation. DAP will thus guide public investment and policy work to accelerate the scaling up of digital transformation.
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Library ResourceRapports et recherchesdécembre, 2021Argentine
Library ResourceArticles et Livresdécembre, 2012Kenya
A study was undertaken along land use gradients in Taita-Taveta district, southeast Kenya to evaluate the occurrence of arbuscular mycorrhizal fungi (AMF) in seven land use types (LUT). The gradient was from indigenous forest (IF) to croplands with coffee (CO), maize (MA), horticulture (HT), napier (NA) and planted forest (PF). A total of 12 AMF morphotypes comprising of 4 Glomus, 1 Claroideoglomus, 5 Acaulosporaceae, 1 Racocetra sp. and 1 Gigaspora were isolated from the study site. Occurrnace of
Library ResourceArticles et Livresdécembre, 1997
Library ResourceArticles et Livresdécembre, 1997Brésil, Amérique centrale, Amérique du Sud
Library ResourceRapports et recherchesdécembre, 2017Kenya, Nigéria, Ouganda, Burundi, Madagascar, Zimbabwe, République-Unie de Tanzanie, Soudan, Ghana, Éthiopie, Malawi, Afrique sub-saharienne, Afrique, Afrique orientale
Our goal is to provide the scientific basis for development investments and policies that promote more productive, profitable agriculture, and healthier diets at no environmental cost. Low-income, smallholder farmers face significant challenges across sub-Saharan Africa (SSA). High population growth is coinciding with migration to the cities as younger populations seek out higher income-earning opportunities. Inadequate infrastructure and few markets for agricultural production in rural areas, for example, are leading to stagnated opportunities for smallholders.
Library Resourcemars, 2019Zimbabwe, Afrique sub-saharienne
Library ResourceRapports et recherchesdécembre, 2017Kenya, Afrique orientale, Afrique
The International Center for Tropical Agriculture (CIAT), in collaboration with our national research partners, has been working in Africa for the last 30 years. Our cutting-edge science helps policy makers, private sector, scientists, civil society, and farmers respond to the most pressing challenges of our time.
Library ResourceRapports et recherchesoctobre, 2018Kenya, Afrique orientale, Afrique
Send a Cow (SAC) is a nongovernmental organization (NGO) that has been working in Kenya since 1996. It focuses on groups of smallholder farmers, providing them with training in sustainable agriculture and improved animal management. SAC is mostly active in western Kenya, one of the country's most populated and poorest region. The population density for this region ranges from 337 to 1,300 inhabitants per km² with an average density of 590 people per km2 (Kenya Ministry of Agriculture and Rural Development, 2001; KNBS, 2010).
Library ResourceArticles et Livresdécembre, 2010
Rice-fish farming: A food security alternative Rice-fish farming is a biological or clean production system that consists of the simultaneous farming of rice and fish on the same land and at the same time; in other words, in the plots flooded for rice cultivation. Rice is the main product and has greater economic importance, whereas the fish is both a source of additional income and a protein supplement that improves the nutritional quality of farmers’ diets.
Library ResourceArticles et Livresdécembre, 1985Colombie, Amérique centrale, Amérique du Sud
The factors influencing the size and shape of exptl. field plots (area of exptl. lot, soil types, trial objective, no. of replicates, and degree of accuracy and homogeneity of the exptl. material) for the execution of field expt. are discussed. The basic principles of the following different methods to determine plot size are described: max. curve method, method of Koch and Rigney, Hatheway's method, and the max. curve method using the multiple linear regression model. Some considerations are presented on the border effect and on plot size in bush and climbing bean trials.
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