What is AGRIS?
AGRIS (International System for Agricultural Science and Technology) is a global public database providing access to bibliographic information on agricultural science and technology. The database is maintained by CIARD, and its content is provided by participating institutions from all around the globe that form the network of AGRIS centers (find out more here). One of the main objectives of AGRIS is to improve the access and exchange of information serving the information-related needs of developed and developing countries on a partnership basis.
AGRIS contains over 8 million bibliographic references on agricultural research and technology & links to related data resources on the Web, like DBPedia, World Bank, Nature, FAO Fisheries and FAO Country profiles.
More specifically
AGRIS is at the same time:
A collaborative network of more than 150 institutions from 65 countries, maintained by FAO of the UN, promoting free access to agricultural information.
A multilingual bibliographic database for agricultural science, fuelled by the AGRIS network, containing records largely enhanced with AGROVOC, FAO’s multilingual thesaurus covering all areas of interest to FAO, including food, nutrition, agriculture, fisheries, forestry, environment etc.
A mash-up Web application that links the AGRIS knowledge to related Web resources using the Linked Open Data methodology to provide as much information as possible about a topic within the agricultural domain.
Opening up & enriching information on agricultural research
AGRIS’ mission is to improve the accessibility of agricultural information available on the Web by:
- Maintaining and enhancing AGRIS, a bibliographic repository for repositories related to agricultural research.
- Promoting the exchange of common standards and methodologies for bibliographic information.
- Enriching the AGRIS knowledge by linking it to other relevant resources on the Web.
AGRIS is also part of the CIARD initiative, in which CGIAR, GFAR and FAO collaborate in order to create a community for efficient knowledge sharing in agricultural research and development.
AGRIS covers the wide range of subjects related to agriculture, including forestry, animal husbandry, aquatic sciences and fisheries, human nutrition, and extension. Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more. A growing number (around 20%) of bibliographical records have a corresponding full text document on the Web which can easily be retrieved by Google.
Members:
Resources
Displaying 3016 - 3020 of 9579Indices of atmospheric air-conditioning safety of pollution of land resources
One of the main directions of activity in the sphere of environmental protection is to monitor the negative effects on the environment and, in particular, the emissions of environmental pollution into the atmosphere. The pollution of the atmospheric air, which creates a health risk for the population, is an important ecological and hygienic problem.
Ploughing and grazing alter the spatial patterning of surface soils in a shrub-encroached woodland
Grazing is known to affect the spatial patterning of soil resources through biologically-mediated processes such as the removal of plant biomass and deposition of dung. In dense shrublands, grazing is thought to reinforce the concentration of resources around shrubs (fertile island effect) by enhancing the movement of resources from the interspace to the shrub hummocks. Shrub removal practices such as ploughing, which is commonly used to manage dense shrub patches, has unknown impacts on the distribution of soil properties.
Groundwater modelling for the assessment of water management alternatives
Rise in groundwater level followed by waterlogging and secondary salinisation has become a serious problem in canal irrigated areas located in arid and semi-arid regions of the world. To solve the problem, the groundwater model SGMP was applied in a waterlogged area of Haryana State of India in which about 500,000ha has already waterlogged resulting in reduced crop yield and abandonment of agricultural lands. After successful calibration and validation, several scenario building exercises have been conducted. Error and sensitivity analyses of the model parameters were done.
Connected components labeling for giga-cell multi-categorical rasters
Labeling of connected components in an image or a raster of non-imagery data is a fundamental operation in fields of pattern recognition and machine intelligence. The bulk of effort devoted to designing efficient connected components labeling (CCL) algorithms concentrated on the domain of binary images where labeling is required for a computer to recognize objects.
self-trained semisupervised SVM approach to the remote sensing land cover classification
Support vector machines (SVM) are nowadays receiving increasing attention in remote sensing applications although this technique is very sensitive to the parameters setting and training set definition. Self-training is an effective semisupervised method, which can reduce the effort needed to prepare the training set by training the model with a small number of labeled examples and an additional set of unlabeled examples. In this study, a novel semisupervised SVM model that uses self-training approach is proposed to address the problem of remote sensing land cover classification.