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Found 27 result(s)
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FooDB is the world’s largest and most comprehensive resource on food constituents, chemistry and biology. It provides information on both macronutrients and micronutrients, including many of the constituents that give foods their flavor, color, taste, texture and aroma.
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>>>>!!<<<< As stated 2017-11-23 the database is not available anymore >>>>!!<<<< ACEpepDB is a database ran by the Central Food Technological Research Institute. It contains records of about 865 peptides. Each record provides information on the food source, preparation, purification and any other additional information. Each record includes the reference(s). The database provides a search and browsing option for a more personalized research experience.
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The Alberta Food Composition Database (AFCDB) is the first comprehensive resource on food constituents, chemistry and biology dedicated to major Alberta-grown produce. It provides information on both macronutrients and micronutrients, including many of the constituents that give foods their flavor, color, taste, texture and aroma. Users can view the contents of the AFCDB from the “FoodView” (listing foods by their chemical composition) or the “ChemView” (listing chemicals by their food sources).
Using a combination of remote sensing data and ground observations as inputs, CHG scientists have developed rainfall and other models that reliably predict crop performance in parts of the world vulnerable to crop failure. Policy makers within governments and at non-governmental organizations rely on CHG decision-support products for making critical resource allocation decisions. The CHG's scientific focus is "geospatial hydroclimatology", with an emphasis on the early detection and forecasting of hydroclimatic hazards related to food security droughts and floods. Basic research seeks an improved understanding of the climatic processes that govern drought and flood hazards in FEWS.NET countries. We develop better techniques, algorithms, and modeling applications to use remote sensing and other geospatial data for hazard early warning.
INRA is Europe’s top agricultural research institute and the world’s number two centre for the agricultural sciences. Data Inra is offered by INRA as part of its mission to open the results of its research. Data Inra will share research data in relation with food, nutrition, agriculture and environment. It includes experimental, simulation and observation data, omic data, survey and text data. Only data produced by or in collaboration with INRA will be hosted in the repository, but anyone can access the metadata and the open data.
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.
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The Global Agricultural Trial Repository (AgTrials) provides access to a database on the performance of agricultural technologies at sites across the developing world. It builds on decades of evaluation trials, mostly of varieties, but includes any agricultural technology for developing world farmers. It aims to facilitate the subsequent analysis on the performance of agricultural technologies under a changing climate and to form the basis for improving models of agricultural production under current and future conditions, and for evaluating the efficacy of trialed materials for adaptation.
The CMU Multi-Modal Activity Database (CMU-MMAC) database contains multimodal measures of the human activity of subjects performing the tasks involved in cooking and food preparation. The CMU-MMAC database was collected in Carnegie Mellon's Motion Capture Lab. A kitchen was built and to date twenty-five subjects have been recorded cooking five different recipes: brownies, pizza, sandwich, salad, and scrambled eggs.
RADAR service offers the ability to search for research data descriptions of the Natural Resources Institute Finland (Luke). The service includes descriptions of research data for agriculture, forestry and food sectors, game management, fisheries and environment. The public web service aims to facilitate discovering subjects of natural resources studies. In addition to Luke's research data descriptions one can search metadata of the Finnish Environment Institute (SYKE). The interface between Luke and SYKE metadata services combines Luke's research data descriptions and SYKE's descriptions of spatial datasets and data systems into a unified search service.
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The Centre conducts real-time data collection on all ongoing and incoming General and Assembly Elections, and diffuses data-driven analysis through print and electronic media. The coverage includes the analysis, contextualization, and visualisation of results and the profiling of main parties candidates. For each election, we assemble a team of field researchers and scholars to complete and expand existing data. Besides the ECI results data, we collect information on the socio-demographic profile of main parties’ candidates and on the sociological profile of constituencies.
A national study on socioeconomics and family health over lifetimes and across generations funded by National Science Foundation (NSF). It is the longest running longitudinal household survey in the world, started in 1968 with a nationally representative sample of over 18,000 individuals living in 5,000 families in the United States. It is recognizing the importance of the socioeconomic data, available on this website without cost to researchers and analysts.
WFCC-MIRCEN World Data Centre for Microorganisms (WDCM) provides a comprehensive directory of culture collections, databases on microbes and cell lines, and the gateway to biodiversity, molecular biology and genome projects.The WFCC is a Multidisciplinary Commission of the International Union of Biological Sciences (IUBS) and a Federation within the International Union of Microbiological Societies (IUMS). The WFCC is concerned with the collection, authentication, maintenance and distribution of cultures of microorganisms and cultured cells. Its aim is to promote and support the establishment of culture collections and related services, to provide liaison and set up an information network between the collections and their users, to organise workshops and conferences, publications and newsletters and work to ensure the long term perpetuation of important collections.
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The Toxin and Toxin Target Database is a unique bioinformatics resource that combines detailed toxin data with comprehensive toxin target information. The focus of the T3DB is on providing mechanisms of toxicity and target proteins for each toxin. This dual nature of the T3DB, in which toxin and toxin target records are interactively linked in both directions, makes it unique from existing databases.
ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.
In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.