Articles
MODELLING THE EFFECT OF ENVIRONMENTAL PARAMETERS (TEMPERATURE, PH & AW) ON THE INDIVIDUAL CELL LAG PHASE OF LISTERIA MONOCYTOGENES
Article number
674_3
Pages
39 – 46
Language
English
Abstract
The effect of the environmental factors temperature (2-30°C), pH (4.4-7.4) and aw (0.995-0.947) on the individual cell lag phase of Listeria monocytogenes was investigated.
Individual cells were isolated using a serial dilution protocol in microtiter plates, and subsequent growth was investigated by optical density (OD) measurements.
About 100 replicates were made for each set of environmental conditions.
Individual cell lag phases and subsequent growth rates were calculated using a linear growth model.
The results were discussed as mean values to determine the general trends, but also histograms were made and statistical distributions were fitted to the different data sets.
The best descriptions of the data were obtained with an exponential distribution for low stress levels, a gamma distribution for intermediate stress and a Weibull distribution for severe stress levels.
When only low stress levels were applied, a significant percentage of the cells showed no significant lag.
In those cases better fits are obtained by separating cells with lag and those without lag using a binomial distribution and in a second step, fitting a gamma or a Weibull distribution to the fraction showing significant lag.
Individual cells were isolated using a serial dilution protocol in microtiter plates, and subsequent growth was investigated by optical density (OD) measurements.
About 100 replicates were made for each set of environmental conditions.
Individual cell lag phases and subsequent growth rates were calculated using a linear growth model.
The results were discussed as mean values to determine the general trends, but also histograms were made and statistical distributions were fitted to the different data sets.
The best descriptions of the data were obtained with an exponential distribution for low stress levels, a gamma distribution for intermediate stress and a Weibull distribution for severe stress levels.
When only low stress levels were applied, a significant percentage of the cells showed no significant lag.
In those cases better fits are obtained by separating cells with lag and those without lag using a binomial distribution and in a second step, fitting a gamma or a Weibull distribution to the fraction showing significant lag.
Authors
K. Francois, F. Devlieghere, K. Smet, A.R. Standaert, A.H. Geeraerd, J.F. Van Impe, J. Debevere
Keywords
Individual cell lag phase, Listeria monocytogenes, risk assessment, optical density, predictive modelling
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