Microbial Growth Modelling Under Variable
Temperature Conditions
Author(s)
V. Popov, R. Gospavic, J. Kreyenschmidt & S. Bruckner
Abstract
The application of a Quantitative Microbial Risk Assessment (QMRA) in food
supply chains requires accurate prediction of microbial growth under variable
temperature conditions. A dynamical growth model under variable temperature
conditions was developed using raw data for microbial growth of Pseudomonas
spp. in poultry under aerobic conditions from a food supply chain in Germany.
The primary model was developed using measurement data under a set of fixed
temperatures and constant environmental conditions. The two primary models
used for modelling the growth under constant temperature conditions were:
Baranyi and modified Gompertz. As a secondary model the square root model
was used for maximal growth rate in the Baranyi model and polynomial
interpolation for the modified Gompertz model. In the case of the Baranyi model
the main assumption, that the initial physiological state of the inoculum is
constant and independent of the environmental parameters, is used. The
generated dynamical models are validated by comparing the predictions obtained
by both models with data measured under dynamical temperature conditions.
Two temperature profiles were used for comparison and good agreement has
been found between experimental data and model predictions.
Keywords: microbial growth, predictive microbiology, pseudomonas spp.,
poultry.
Keywords
microbial growth, predictive microbiology, pseudomonas spp.,
poultry
Related Book
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