This paper summarises recent trends in predictive modelling of microbial lag phenomena.
The lag phase is approached from both a qualitative and a quantitative point of view. First, a …

Risk estimates for food‐borne infection will usually depend heavily on numbers of
microorganisms present on the food at the time of consumption. As these data are seldom …

The changes in microbial flora and sensory characteristics of fresh ground meat (beef and
pork) with pH values ranging from 5.34 to 6.13 were monitored at different isothermal …

The first state-of-the-art review of this dynamic field in a decade, Modeling Microbial
Responses in Foods provides the latest information on techniques in mathematical …

The behavior of the natural microflora of Mediterannean gilt-head seabream (Sparus aurata)
was monitored during aerobic storage at different isothermal conditions from 0 to 15° C. The …

The effect of inoculum size on population lag times of Listeria monocytogenes was
investigated using the Bioscreen automated microtitre plate incubator and reader. Under …

Changes in populations of microorganisms in foods over time (ie,“microbial kinetics”) are
governed by storage conditions (“extrinsic” factors) and product characteristics (“intrinsic” …

Growth data for Listeria monocytogenes were collected from the literature and a global
model built with existing secondary models describing independently the effects of …

This chapter is divided into 2 main sections. The first section describes model fitting,
featuring the principles and applications of regression models for data sets in food …

The usefulness of risk assessment is limited by its ability or inability to model and evaluate
risk uncertainty and variability separately. A key factor of variability and uncertainty in …