A novel method is proposed for fitting microbial inactivation models to data on liquid media:
the Most Probable Curve (MPC) method. It is a multilevel model that makes a separation …

The estimation of the concentration of microorganisms in a sample is crucial for food
microbiology. For instance, it is essential for prevalence studies, challenge tests (growth …

Predictive microbiology is an area of applied research in food science that uses
mathematical models to predict the changes in the population of pathogenic or spoilage …

Predictive models for lag phase duration (λ) have been less reliable than specific growth
rate (μ) models due, in part, to the influence of the pre-growth environment on λ. A discrete …

Aims: To evaluate the performances of models predicting the growth rate or the growth
probability of Listeria monocytogenes in food. Methods and Results: Cardinal and square …

Stochastic models, including the variability in extent and probability of microbial growth, are
useful for estimating the risk of foodborne illness (ie Nauta, 2000). Risk assessment typically …

Survival and growth of Listeria monocytogenes isolates during sous vide processing and
storage, and the applicability of predictive modelling in determining the potential for growth …

The growth/no growth response of a mixture of five strains of Listeria monocytogenes in
tryptic soy broth and on tryptic soy agar was monitored in combination treatments of …

Until now, most of the mathematical models used in predictive microbiology are
deterministic, ie their outcome is a point estimate for the microbial load at a certain time …

An alternative predictive model for microbial inactivation and a novel web-based tool for the
application of predictive microbiology are reviewed in this paper. The developed model …