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Title: Optimal experimental design for discriminating between microbial growth models as function of suboptimal temperature: From in silico to in vivo
Authors: Stamati, Ioanna ×
Akkermans, Simen
Logist, Filip
Noriega, Estefanía
Van Impe, Jan #
Issue Date: 2016
Publisher: Published on behalf of the Canadian Institute of Food Science and Technology by Elsevier Applied Science
Series Title: Food Research International vol:89 issue:1 pages:689-700
Abstract: 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 other words, the microbial behavior can be described in a dynamic environment with the use of a primary and secondary model. Two models for describing the effect of temperature on the microbial growth rate are the cardinal temperature model with inflection (CTMI) (Rosso et al., 1993) and its adapted version (aCTMI) (Le Marc et al., 2002). Although Escherichia coli is commonly modeled using CTMI, there are indications that aCTMI may be more appropriate (Van Derlinden and Van Impe, 2012a). For clarifying this, the method of Optimal experiment design for model discrimination (OED/MD) will be used in this work (Donckels et al., 2009; Schwaab et al., 2008). Results from an in silico study point out the required direction. Whereas the results of the in vivo study give a more realistic answer to the research question. Finally, discrimination unravelled the appropriate model for the needed use.
ISSN: 0963-9969
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Sustainable Chemical Process Technology TC, Technology Campus De Nayer Sint-Katelijne-Waver
UC Limburg - miscellaneous
Sustainable Chemical Process Technology TC
Sustainable Chemical Process Technology TC, Technology Campuses Ghent and Aalst
× corresponding author
# (joint) last author

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