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Title: Modelling the individual cell lag phase: effect of temperature and pH on the individual cell lag distribution of Listeria monocytogenes
Authors: Francois, K ×
Devlieghere, F
Smet, K
Standaert, AR
Geeraerd, Annemie
Van Impe, Jan
Debevere, J #
Issue Date: Apr-2005
Publisher: Elsevier Science Publishers
Series Title: International Journal of Food Microbiology vol:100 issue:1-3 pages:41-53
Conference: date:State Univ Ghent, Lab Food Microbiol & Food Preservat, Dept Food Technol & Nutr, B-9000 Ghent, Belgium; Katholieke Univ Leuven, Dept Chem Engn, B-3001 Louvain, Belgium
Abstract: The individual-based approach of the lag phase is gaining interest, especially for pathogens that initially contaminate food products in low amounts. In this paper, the effect of temperature (30, 10, 7, 4 and 2 degrees C) and pH (7.4, 6.1, 5.5, 5.0, 4.7 and 4.4) on the individual cell lag phase of Listeria monocytogenes was examined in a factorial design, using OD measurements. Individual lag phases of about 100 (i)ndividual cells per condition were examined and calculated using a linear extrapolation method. Generation times were calculated out of the slope. The obtained data were analyzed at three different levels: in a first approach, the mean values were calculated for each set of environmental conditions and compared to predictions made by the USDA's Pathogen Modeling Program (PMP) for analogous growth conditions. The PMP predictions of the generation times were in the same order of magnitude as the obtained data, although a persistent underestimation could be observed. The observed individual cell lag data differed from lag phase predictions by PMP. Possible reasons for this discrepancy are discussed. Secondly, histograms of individual lag phase measurements were constructed for the different temperature-pH combinations. In this way, the influence of both factors on the variability of individual lag phases could be estimated. At low stress levels, most individual cells showed a short lag phase resulting in a compression of the histograms at the zero-lag level, while, at high stress levels, the histograms shifted to longer lag phases with a significant increase in variability. Thirdly, 37 different distribution types were fitted to the datasets to reveal the distributions that fitted best the obtained data. The gamma distribution was preferred at moderate stress levels, while the Weibull distribution was chosen for harsher growth conditions. (c) 2004 Elsevier B.V. All rights reserved.
ISSN: 0168-1605
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section
Division of Mechatronics, Biostatistics and Sensors (MeBioS)
× corresponding author
# (joint) last author

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