ComBase: A Web Resource for Quantitative and Predictive Food Microbiology

ComBase includes a systematically formatted database of quantified microbial responses to the food environment with more than 65,000 records, and is used for:

• Informing the design of food safety risk management plans
• Producing Food Safety Plans and HACCP plans
• Reducing food waste
• Assessing microbiological risk in foods

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 as a function of environmental factors such as temperature, pH and water activity in broth.

Interested users can also contribute growth or inactivation data via the Donate Data page, which includes instructional videos, data template and sample, and an Excel demo file of data and macros for checking data format and syntax.

• Resource Title: Website Pointer to ComBase.

  File Name: Web Page, url: https://www.combase.cc/index.php/en/

  ComBase is an online tool for quantitative food microbiology. Its main features are the ComBase database and ComBase models, and can be accessed on any web platform, including mobile devices. The focus of ComBase is describing and predicting how microorganisms survive and grow under a variety of primarily food-related conditions. ComBase is a highly useful tool for food companies to understand safer ways of producing and storing foods. This includes developing new food products and reformulating foods, designing challenge test protocols, producing Food Safety plans, and helping public health organizations develop science-based food policies through quantitative risk assessment. Over 60,000 records have been deposited into ComBase, describing how food environments, such as temperature, pH, and water activity, as well as other factors (e.g. preservatives and atmosphere) affect the growth of bacteria. Each data record shows users how bacteria populations change for a particular combination of environmental factors. Mathematical models (the ComBase Predictor and Food models) were developed on systematically generated data to predict how various organisms grow or survive under various conditions.