Microbial modeling in foods

Abstract

Predictive food microbiology is a field of study that combines elements of microbiology, mathematics, and statistics to develop models that describe and predict the growth or decline of microbes under specified environmental conditions. Models can be thought of as having three levels: primary level models describe changes in microbial numbers with time, secondary level models show how the parameters of the primary model vary with environmental conditions, and the tertiary level combines the first two types of models with user‐friendly application software or expert systems that calculate microbial behavior under the specified conditions. Primary models include time‐to‐growth, Gompertz function, exponential growth rate, and inactivation/survival models. Commonly used secondary models are response surface equations and the square root and Arrhenius relationships. Microbial models are valuable tools in planning Hazard Analysis, Critical Control Point (HACCP) programs and making decisions, as they provide the first estimates of expected changes in microbial populations when exposed to a specific set of conditions. This review describes the models currently being developed for food‐borne microorganisms, particularly pathogens, and discusses their uses.