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Title: Concepts and tools for predictive modeling of microbial dynamics
Authors: Bernaerts, Kristel ×
Dens, Els
Vereecken, Karen
Geeraerd, Annemie
Standaert, Arnout
Devlieghere, Frank
Debevere, Johan
Van Impe, Jan #
Issue Date: Aug-2004
Series Title: Journal of food protection vol:67 issue:9 pages:2041-52
Abstract: Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.
ISSN: 0362-028X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section
Division Soil and Water Management
Division of Mechatronics, Biostatistics and Sensors (MeBioS)
× corresponding author
# (joint) last author

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