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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:
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:
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:
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.