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



ComBase users say ...

I find ComBase absolutely essential to my teaching, research and outreach activities. I seldom go for more than a week without consulting it for solving a variety of food safety problems

Donald Schaffner
Distinguished Professor and Extension Specialist

Predictive Microbiology and Risk Assessment News

Designing a Food Matrix Ontology for Supporting a Predictive Microbiology Database
Modeling the Long-Term Kinetics of Salmonella Survival on Dry Pet Food
Development of a Predictive Model for the Growth Kinetics of Aerobic Microbial Population on Pomegranate Marinated Chicken Breast Fillets Under Isothermal and Dynamic Temperature Conditions
Food Factories to Become Safer Thanks to DNA Testing
Risk Assessment of Foodborne Illness Associated With Pathogens From Produce Grown in Fields Amended With Untreated Biological Soil Amendments of Animal Origin
Minimal Inhibitory Concentrations of Undissociated Lactic, Acetic, Citric and Propionic Acid for Listeria monocytogenes Under Conditions Relevant to Cheese