ComBase in a nutshell

ComBase is the no.1 web-based resource for Quantitative and 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. ComBase is managed by the ComBase Consortium consisting of the Institute of Food Research (IFR) in the United Kingdom, the USDA Agricultural Research Service (USDA-ARS) in the United States, and the University of Tasmania Food Safety Centre (FSC) in Australia. The purpose of ComBase is to provide electronic repository for food microbiology observations and to make such data and the generated predictive tools freely available and accessible to the wide community. 

The success of ComBase is due to effective collaborations among the Consortium partners.  From a historial perspective, the database and its first predictive models, as well as the ComBase web site were developed at IFR. The ComBase Browser making the database accessible online was developed by USDA-ARS. Today, the ComBase website is hosted at IFR while the browser has been enhanced and sustained by the efforts of all ComBase staff located in the IFR, FSC and USDA-ARS.

Anyone interested in the microbial safety and quality of foods can explore ComBase and its associated tools at no cost. Using an internet interface, the user defines criteria that are relevant to their query. The criteria include the type or species of organism, the type or class of food, pH, temperature, water activity (or NaCl concentration), and specific food conditions. Alternatively, ComBase customers may be interested in retrieving data from a specific source (publication, organisation or researcher). The output is a growth or survival rate, or the profiles of the concentration  of microorganisms (both spoilage organisms and pathogens)  as a function of time under given conditions. ComBase comprises tens of thousands of microbial growth and survival curves that have been collated in research establishments and from publications.

They form the basis of predictive models accessible in the Predictive Models collection, a useful set of tools for industry, academia and regulatory agencies. They can be used for developing new food products and technologies whilst maintaining food safety, for teaching and research, for assessing the microbial risk in foods or setting up new guidelines.