Accurate estimation of cardinal growth temperatures of Escherichia coli from optimal dynamic experiments
- PMID: 18835500
- DOI: 10.1016/j.ijfoodmicro.2008.07.007
Accurate estimation of cardinal growth temperatures of Escherichia coli from optimal dynamic experiments
Abstract
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 of the microbial evolution ask for correct model structures and reliable parameter values with good statistical quality. Given the widely accepted validity of the Cardinal Temperature Model with Inflection (CTMI) [Rosso, L., Lobry, J. R., Bajard, S. and Flandrois, J. P., 1995. Convenient model to describe the combined effects of temperature and pH on microbial growth, Applied and Environmental Microbiology, 61: 610-616], this paper focuses on the accurate estimation of its four parameters (T(min), T(opt), T(max) and micro(opt)) by applying the technique of optimal experiment design for parameter estimation (OED/PE). This secondary model describes the influence of temperature on the microbial specific growth rate from the minimum to the maximum temperature for growth. Dynamic temperature profiles are optimized within two temperature regions ([15 degrees C, 43 degrees C] and [15 degrees C, 45 degrees C]), focusing on the minimization of the parameter estimation (co)variance (D-optimal design). The optimal temperature profiles are implemented in a computer controlled bioreactor, and the CTMI parameters are identified from the resulting experimental data. Approximately equal CTMI parameter values were derived irrespective of the temperature region, except for T(max). The latter could only be estimated accurately from the optimal experiments within [15 degrees C, 45 degrees C]. This observation underlines the importance of selecting the upper temperature constraint for OED/PE as close as possible to the true T(max). Cardinal temperature estimates resulting from designs within [15 degrees C, 45 degrees C] correspond with values found in literature, are characterized by a small uncertainty error and yield a good result during validation. As compared to estimates from non-optimized dynamic experiments, more reliable CTMI parameter values were obtained from the optimal experiments within [15 degrees C, 45 degrees C].
Similar articles
-
Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.J Theor Biol. 2010 May 21;264(2):347-55. doi: 10.1016/j.jtbi.2010.01.003. Epub 2010 Jan 11. J Theor Biol. 2010. PMID: 20064532
-
Optimal experiment design for cardinal values estimation: guidelines for data collection.Int J Food Microbiol. 2005 Apr 15;100(1-3):153-65. doi: 10.1016/j.ijfoodmicro.2004.10.012. Epub 2005 Jan 6. Int J Food Microbiol. 2005. PMID: 15854701
-
Predicting biodegradable volatile solids degradation profiles in the composting process.Waste Manag. 2009 Feb;29(2):559-69. doi: 10.1016/j.wasman.2008.05.001. Epub 2008 Jun 24. Waste Manag. 2009. PMID: 18572400
-
Cell division theory and individual-based modeling of microbial lag: part I. The theory of cell division.Int J Food Microbiol. 2005 Jun 15;101(3):303-18. doi: 10.1016/j.ijfoodmicro.2004.11.016. Int J Food Microbiol. 2005. PMID: 15925713 Review.
-
Predictive modelling of the microbial lag phase: a review.Int J Food Microbiol. 2004 Jul 15;94(2):137-59. doi: 10.1016/j.ijfoodmicro.2004.01.006. Int J Food Microbiol. 2004. PMID: 15193801 Review.
Cited by
-
Modelling growth of two Listeria monocytogenes strains, persistent and non-persistent: Effect of temperature.Heliyon. 2024 Dec 7;10(24):e40936. doi: 10.1016/j.heliyon.2024.e40936. eCollection 2024 Dec 30. Heliyon. 2024. PMID: 39759359 Free PMC article.
-
The Complex Effect of Food Matrix Fat Content on Thermal Inactivation of Listeria monocytogenes: Case Study in Emulsion and Gelled Emulsion Model Systems.Front Microbiol. 2020 Jan 22;10:3149. doi: 10.3389/fmicb.2019.03149. eCollection 2019. Front Microbiol. 2020. PMID: 32038582 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Research Materials