ComBase is an online tool for quantitative food microbiology. Its main pillars are the ComBase database and the ComBase Predictor, which is primarily based on broth-based data in ComBase data. The focus of ComBase is to describe and predict how microorganisms survive and grow under a variety of (primarily food-related) conditions.

ComBase is a useful tool for food companies to develop new products, and to understand the safest way of producing or storing foods. ComBase data and models help food companies reformulate foods, assist regulatory officers in quantitative risk assessment, and help trainers/students demonstrate how food microorganisms respond to food environments, using a simple user interface.

Over 50,000 records have been deposited into ComBase, describing how food processing and storage conditions, such as temperature, pH, and water activity, as well as other factors (e.g. preservatives and atmosphere) affect the growth of foodborne bacteria. Each data record represents how microbial cell concentrations, or the derived maximum specific growth rate, change for a particular combination of environmental factors. Mathematical models (the ComBase Predictor) have been developed on systematically generated data to predict how various organisms grow or survive under various conditions.

ComBase tools help companies minimise the amount of testing they need to do themselves, which can be a lengthy and expensive process. They can also help troubleshoot when problems occur. A recent independent assessment of ComBase’s impact showed that every hour in testing saved by all of Combase’s users is worth £1milion.


ComBase is a collaboration betweeb the University of Tasmania and the USDA Agricultural Research Service (USDA-ARS). The ComBase platform has recently been redeveloped to make it even more accessible. The web interface can now be easily accessed on any platform, including mobile devices, in a user friendly way.

Access ComBase

The ComBase Browser enables you to search thousands of microbial growth and survival curves that have been collated in research establishments and from publications

The ComBase Predictive Models are a collection of software tools based on ComBase data to predict the growth or inactivation of microorganisms

 

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