What is the difference between ComBase Browser and ComBase Predictor?

The ComBase Browser searches a database of kinetics of spoilage organisms and pathogens in broth and food. The data come from the scientific literature or were produced by miscellaneous institutions. The ComBase Predictor gives predictions from models based on selected data of the ComBase database as a function of environmental factors such as temperature, pH and water activity in broth.

Are there any costs associated with registration?

There is no cost associated with registering. ComBase is jointly run by the USDA Eastern Regional Research Center and the University of Tasmania Food Safety Centre, Australia.

Why should I register?

We collect registration data for two main purposes: to gain information about the customer base, e.g. which part of the world or which industry or legislative agency are accessing the data; and also so that we can target users with new information, e.g. updates and improvements to ComBase. We do not disclose submitted details to third parties. In due course we intend to introduce a click-button for those who wish to opt out of email from us.

Can you please let me know of any publications available on the topic?

A list of relevant publications can be viewed in the Publications section of this website.

Are you able to download graphs from ComBase?

If you print the screen from the Explorer directly, the result is not very well scaled. However, the ComBase software engineer put a print icon on the on the top right corner of the screen that generates a html page which is more suitable. Users can print this either as pdf or on a paper printer. The “print” icon is available for ComBase Predictor and Perfringens Predictor; it will be soon added to the DMFit web version, too.

Is it possible to include a screen shot of ComBase predictions on teaching powerpoint slides?

You are certainly welcome to use any ComBase related figures or data that you can find on the Net. Our general policy is that ComBase is totally open and free as long as the resource is used for training or research.

I have tried to use ComBase, however it seems that little information is available for spoilage organisms in real food.

Indeed, most of the data are on responses of pathogens observed in laboratory media. The main reason for this is that the vast majority of the data underlying ComBase are from the PMP (Pathogen Modeling Program) and FMM (Food MicroModel) databases and both these databases were primarily aimed at recognised foodborne pathogens. However, data are constantly being added to ComBase including microbial response records for food spoilage organisms. The database is periodically updated and will eventually reflect these new additions.

What mechanism ensure that ComBase does not include poor quality or erroneous data?

The ComBase Partners conduct Quality Assurance on submitted data, with a final review before data are finally published in ComBase. If data have been published in a peer-reviewed journal, those data will be included in ComBase unchanged (except for very obvious mistakes). Therefore ComBase is not different from other electronic publications. Interpretation of the data will be highly individual and the ComBase team assumes no responsibility for how the data are used. We recommend that expert advice should be sought where necessary.

Where can I find help about the ComBase Predictor

ComBase Predictor has its own FAQ’s section which can be found under ‘Help’ once you are logged in.

As a scientist interested in food safety, I am keen for the results of our research to reach a wide audience. Would it be possible for data that we have generated to be included in the ComBase database?

We would be pleased to discuss this matter further to ascertain whether a set of data is suitable for inclusion in ComBase. If it is, we will provide spreadsheets and information describing the format required for appropriate data entry. The real success of ComBase is dependant upon the goodwill of those providing data to further populate the database. In return, the relevant data are attributed to you (or not, as you see fit).

Predictive Microbiology and Risk Assessment News

Risk Assessment of Fungal Spoilage: A Case Study of Aspergillus niger on Yogurt
Modelling the Effect of Combined Antimicrobials: A Base Model for Multiple-Hurdles
Combined Effects of Temperature, pH and Water Activity on Predictive Ability of Microbial Kinetic Inactivation Model
Modelling Biofilm Formation of Salmonella enterica ser Newport as a Function of pH and Water Activity
Growth Kinetics Parameters of Salmonella spp. in the Peel and in the Pulp of Custard Apple (Annona Squamosa)
Aerobic Microbial Inactivation Kinetics of Shrimp Using a Fixed Minimal Ozone Discharge: A Fact or Fib During Iced Storage?