combase modified by Matthias Filter

Matthias Filter — Sat, 03 May 2014 11:02:55 -0000

--- v1
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 ####Name:####

-
+ComBase
 ####Company / Institution:####

-
+Institute of Food Research, England
 ####Development Partners:####

-
+Institute of Food Research
+UK Food Safety Centre
+University of Tasmania
+AU USDA Agricultural Research Service, US.
 ####Contact person:####

-
+J. Baranyi and D. Marin
 ####Link:####

+http://www.combase.cc
+####Created:####

+2004
 ####Designed for:####

-
+Food business operators
+Researchers
+Government
+Teachers
+Students
 ####Applicable for:####

-
+Database (dissociated from simulation)
+Growth module (simulation and fitting)
+Inactivation module (simulation and fitting)
 ####Media covered:####

+several food matrices
+####Micro-organisms covered:####

-####Microorganisms covered:####
-
-
+Pathogens: 15 species
+Spoilers: 5 species
 ####Growth Factors covered:####

-
+Temperature
+pH
+Water activity
+Lactic acid
+Others organic acids
+CO2
+Interactions between factors
 ####Modeling approach:####

+Deterministic
+####Description:####

-####Description:####
+ComBase is a web-based tool for Predictive Food Microbiology. Its main components are a database
+of observed microbial responses to a variety of food-related environments and a collection of relevant
+predictive models. Using an internet interface, users can narrow down their search results to a dataset
+relevant to their query.
+Alternatively, ComBase customers may be interested in (and most frequently they are content with)
+generating predictions provided by the mathematical models developed from selected records in the
+database. The more than 50,000 records on microbial growth and survival (mostly viable count curves)
+were donated by research establishments or collated from publications. Systematic experimental design
+is in the background of those data, which provide the basis of the predictive models accompanying the
+database. They target the responses of the major food-borne pathogens to environments quantified by
+temperature, pH, humectants, etc.).
+ComBase is a result of collaboration between the Institute of Food Research, UK; the University of
+Tasmania Food Safety Centre (FSC) in Australia; and the USDA Agricultural Research Service (USDAARS)
+in the United States. It provides an electronic repository for food microbiology observations, to
+make the data and the generated predictive tools freely available and accessible to a wide community
+interested in quantitative food microbiology.
+Recently ComBase underwent a major restructure and new features were introduced to make it easier
+to use, especially for risk assessment. Recently ComBase underwent a major restructuring and new
+features were introduced to make it easier to use, especially for risk assessment. These include the
+error estimation of the predicted specific rates, visualising their probability distribution, and separating 
+uncertainty due to lack of information and due to statistical variability when predicting the lag time.
+These indicators can play crucial role when assessing microbial risk, quantified by an appropriate cost
+function and driven by the inevitable error in the generated predictions.

Recent changes to combase

combase modified by Matthias Filter

combase modified by Matthias Filter

Name:

Company / Institution:

Development Partners:

Contact person:

Link:

Designed for:

Applicable for:

Media covered:

Microorganisms covered:

Growth Factors covered:

Modeling approach:

Description: