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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 2451 - 2455 of 9579Uncertainty in ecosystem mapping by remote sensing
The classification of remotely sensed images such as aerial photographs or satellite sensor images for deriving ecosystem-related maps (e.g., land cover, land use, vegetation, soil) is generally based on clustering of spatial entities within a spectral space. In most cases, Boolean logic is applied in order to map landscape patterns. One major concern is that this implies an ability to divide the gradual variability of the Earth's surface into a finite number of discrete non-overlapping classes, which are considered to be exhaustively defined and mutually exclusive.
Local-level determinants of wildcat occupancy in Northeast Scotland
We studied the influence of food abundance, land cover and disturbance on European wildcat (Felis silvestris silvestris Schreber, 1777) presence in Scotland. Wildcat records were collected using camera trapping, and prey data were assessed through linear transects and small mammal trapping. Surveys were carried out in three study areas in northeast Scotland. Wildcat occupancy was best predicted by a combination of food and land cover variables.
Rule-based impervious surface mapping using high spatial resolution imagery
Impervious surface mapping has become a recent concern in remote-sensing applications because of worldwide urban growth and the resultant environmental changes. However, many effective impervious surface mapping techniques developed for moderate-resolution imagery are not applicable to high spatial resolution imagery such as that of IKONOS and the Advanced Land Observing Satellite (ALOS) due to their limited number of spectral bands and the lack of middle-infrared bands.
Multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using an object-based support vector machine and a rule-based approach
We have investigated multi-temporal polarimetric synthetic aperture radar (SAR) data for urban land-cover classification using an object-based support vector machine (SVM) in combinations of rules. Six-date RADARSAT-2 high-resolution polarimetric SAR data in both ascending and descending passes were acquired in the rural–urban fringe of the Greater Toronto Area during the summer of 2008.
phylogenetic network of wild Ussurian pears (Pyrus ussuriensis Maxim.) in China revealed by hypervariable regions of chloroplast DNA
In order to understand the genetic diversity of wild Ussurian pears in China, chloroplast DNA (cpDNA) of 186 wild accessions from 12 populations in Inner Mongolia, Heilongjiang and Jilin Provinces and 51 Chinese and European pear cultivars including Pyrus ussuriensis, Pyrus pyrifolia, Pyrus bretschneideri, Pyrus sinkiangensis and Pyrus communis were investigated. Each accession was classified into one of three types (types A, B and C) based on two large deletions in the hypervariable regions between the accD–psaI and rps16–trnQ genes.