Mathematical Modeling of Microbial Growth: A Review

The use of mathematical modeling of microbiological behavior to predict and evaluate food safety or shelf life is receiving considerable interest. Researchers are attempting to use mathematical equations that incorporate such critical growth factors as pH, a w , and NaCl content to predict microbial growth and/or toxin production in order to replace traditional time‐intensive challenge studies. Predictive equations can be divided into probabilistic, regression, Arrhenius, and square root models. Models vary greatly in theory and complexity. Predictive models are used to monitor processes ranging from temperature during distribution to inventory control. They have been shown to be useful in product development and shelf‐life estimation when safety is not an issue. Most models are generated by regression analysis of data obtained from laboratory experiments. Statistically based models, even when conservatively derived, are not appropriate as the only criterion for evaluating food safety.