Our ability to predict the lag (λ) prior to growth of foodborne pathogens is limited by our lack
of understanding of the physiological changes taking place in the individual cell during the …

Highlights•Development of stochastic modeling technique for bacterial inactivation is
reviewed.•Variability in survival cell numbers during inactivation process is described as …

Risk assessments of pathogens need to account for the growth of small number of cells
under varying conditions. In order to determine the possible risks that occur when there are …

Aims: A previous model for adaptation and growth of individual bacterial cells was not
dynamic in the lag phase, and could not be used to perform simulations of growth under non …

The objective of food safety microbiology is to eliminate or at least significantly reduce the
concentration of pathogenic microbes in food and to prevent their resuscitation and …

An existing mathematical model for microbial growth and inactivation in dynamically
changing temperature conditions has been modified to explain the experimentally observed …

After a short time interval of length δ t during microbial growth, an individual cell can be
found to be divided with probability Pd (t) δ t, dead with probability Pm (t) δ t, or alive but …

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 …

We investigated a bacterial sample preparation procedure for single-cell studies. In the
present study, we examined whether single bacterial cells obtained via 10-fold dilution …

Traditional predictive microbiology is not suited for cell growth predictions for low-level
contamination, where individual cell heterogeneity becomes apparent. Accordingly, we …