Predictive food microbiology (PFM) is an emerging multidisciplinary area of food
microbiology. It encompasses such disciplines as mathematics, microbiology, engineering …

The need to ensure the microbiological quality and safety of food products has stimulated
interest in the use of mathematical models for quantifying and predicting microbial …

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 …

Although organic acids have been used to counteract pathogens in food for many years,
there is a glaring need to assess and improve their continued effectiveness and …

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 …

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

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 …

The prediction bias (Bf) and accuracy (Af) factors are the most widely used measures of
performance of predictive models for food pathogens. However, Bf and Af have limitations …

In past years many models describing growth and inactivation of microorganisms have been
developed. This study is a discussion of the growth and inactivation models that can be used …

Three models for one rapid and one slow growing strain of Pseudomonas fragi and one
slow growing strain of P. fluorescens were developed in a meat broth; they were designed to …