Temperature is an important food preservation factor, affecting microbial growth. Secondary
predictive models can be used for describing the impact of this factor on microbial growth. In …

Prediction of the microbial growth rate as a response to changing temperatures is an
important aspect in the control of food safety and food spoilage. Accurate model predictions …

In predictive food microbiology, cardinal parameter models are often applied to describe the
effect of temperature, pH and/or water activity on the microbial growth rate. To identify the …

A previous implementation of optimal dynamic experiments for the identification of the
Cardinal Temperature Model with Inflection, which describes the temperature effect on the …

In the field of predictive microbiology, mathematical models play an important role for
describing microbial growth, survival and inactivation. Often different models are available …

Secondary models, describing the microbial growth rate as a function of temperature, are
evaluated with focus on model performance in the suboptimal temperature region …

Optimal experimental design for parameter estimation (OED/PE) is a promising method to
improve parameter estimation accuracy and minimise experimental effort in the field of …

In this study, predictive microbiology and food engineering were combined in order to
develop a new analytical model predicting the bacterial growth under dynamic temperature …

In predictive microbiology, the model parameters have been estimated using the sequential
two-step modeling (TSM) approach, in which primary models are fitted to the microbial …

Efficient modelling of the microbial growth rate can be performed by combining the effects of
individual conditions in a multiplicative way, known as the gamma concept. However …