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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 386 - 390 of 9579Using a Logistic Regression Model to Analyze Alley Farming Adoption Factors in Sierra Leone
Slash-and-burn shifting cultivation is the conventional farming practice in Sierra Leone, where communal land tenure is by far the most common form of land use. Alley farming, the alternative agricultural system, has been introduced as a technical option to increase yield, reduce or eliminate fallow and conserve soil water. This study uses a logistic regression model to determine the factors influencing the adoption of alley farming in Sierra Leone.
Water Resources and Soil Management In Italy
Italy has always had a long dramatic history of extreme events such as landslides, flooding, land degradation and drought. Much has been done in terms of prevention and monitoring but still there is much left to do, in particular introducing innovative alert systems based on the integration of realâtime weather forecasting with national alert and protection systems.
Rural transitions in the Nambucca Valley: Socio-demographic change in a disadvantaged rural locale
Within current rural research, an ongoing challenge has been to conceptualise the overarching dynamics driving rural transitions in affluent societies, while also recognising diversity and complexity in driving forces and trajectories over time and place. While amenity migration may continue to be influential, more recent research has revealed that there are multiple driving forces leading towards diverse multifunctional rural occupance modes and trajectories.
GIS-based forest fire susceptibility mapping in Iran: a comparison between evidential belief function and binary logistic regression models
The aim of this research was to produce forest fire susceptibility maps (FFSM) based on evidential belief function (EBF) and binary logistic regression (BLR) models in the Minudasht Forests, Golestan Province, Iran. At first, 151 forest fire locations were identified from Moderate-Resolution Imaging Spectero Radiometer data, extensive field surveys, and some reports (collected in year 2010). Out of these locations, 106 (70%) were randomly selected as training data and the remaining 45 (30%) cases were used for the validation goals.
Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA
Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado and Wyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies.