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Environmental factors influencing the relationship between optical density and cell count for Listeria monocytogenes
Author(s) -
Francois K.,
Devlieghere F.,
Standaert A.R.,
Geeraerd A.H.,
Cools I.,
Van Impe J.F.,
Debevere J.
Publication year - 2005
Publication title -
journal of applied microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.889
H-Index - 156
eISSN - 1365-2672
pISSN - 1364-5072
DOI - 10.1111/j.1365-2672.2005.02727.x
Subject(s) - food safety , library science , food microbiology , food science , computer science , biology , genetics , bacteria
Aims: The effect of temperature (2–30°C), pH (4·8–7·4) and water activity (0·946–0·995) on the relationship between optical density (OD) at 600 nm and the plate count (CFU ml −1 ) was investigated for Listeria monocytogenes . Methods and Results: Calibration curves, relating OD with plate counts, were collected by measuring the OD of consecutive one‐half dilution series, before determining the cell density by classic plate count methods. The calibration curves were observed to be shifting in a parallel way, with increasing stress levels. Especially pH influenced the curve in a great extent, while the other variables were showing more synergetic effects. The reason for the shift was investigated by a microscopic viability test, showing a viability decrease with increasing stress levels, causing the shift of the calibration curve. In a last step a model was made describing the effect of environmental factors on the calibration curve, with different data transformations being tested. A polynomial equation was fitted to the data, taking into account a set of constraints to incorporate microbiological knowledge in the black box model. Hence, illogical interpolation results and overfitting of the data could be avoided. Conclusions: Different stress factors are affecting the relationship between the OD and the cell count of L. monocytogenes by lowering the cell viability. These effects could be modelled using a constrained polynomial model. Significance and Impact of the Study: The observed phenomena are important when calculating growth parameters, like growth rate and lag phase, based on OD data.