Turbidimetric measurement as a rapid method for the determination of the bacteriological quality of minced meat

Jørgensen, H.L.; Schulz, Edgar

doi:10.1016/0168-1605(85)90037-6

Cited by 20 publications

(11 citation statements)

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“…Therefore, only the intercept with y ‐axis is influenced, which is related to the estimation of lag phase. In several studies, a direct linear relationship between OD and viable plate counts is used based on the Lambert–Beer law (Jorgensen and Schulz ; Schulz et al . ; Begot et al .…”

Section: Resultsmentioning

confidence: 99%

Critical Assessment of the Time‐to‐Detection Method for Accurate Estimation of Microbial Growth Parameters

Baka

Noriega

Stamati

et al. 2014

Journal of Food Safety

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The time-to-detection (TTD) method is a rapid and high throughput approach for the estimation of microbial growth parameters (maximum specific growth rate μmax and lag phase duration λ), which relies on optical density (OD) measurements. The performance of this method depends on several factors that are often selected in an arbitrary way. In this work, a sensitivity analysis was performed to assess the effect of several key factors on the resulting output data of this method with Listeria monocytogenes. The factors showing higher influence on the results include (1) the calibration curve relating viable plate counts and OD data; (2) the approach to estimate TTD values; (3) the detection limit of OD measurements; and (4) the range of the initial cell concentrations considered (Ni). In general, lag phase (λ) estimates were more sensitive than maximum specific growth rate (μmax) estimates. The approach to estimate TTD values and the OD detection limit was the most influential factors for the μmax and λ estimation. This work has illustrated that, despite all the advantages of the TTD method, there are crucial steps in experimental design and data processing that significantly influence its output in terms of lag phase duration and maximum specific growth rate. PRACTICAL APPLICATIONSThis study contributes to understanding which are the most influential factors on the output of time-to-detection (TTD) method. These factors can be considered throughout different steps of the method, experimental design, data processing and growth parameter estimation. Guidelines are provided about how the selection of the factors assessed should be made and which variables -i.e., research scope, materials and equipment available for experimental and analytical stepsshould be considered. In addition, some limitations of the method regarding the range and quality of the experimental data when implementing an automated global fitting are described. Overall, the performance of the TTD method and the accuracy of microbial growth parameters estimation will be improved.

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Section: Resultsmentioning

confidence: 99%

Critical Assessment of the Time‐to‐Detection Method for Accurate Estimation of Microbial Growth Parameters

Baka

Noriega

Stamati

et al. 2014

Journal of Food Safety

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“…As already mentioned in the , several methods can be applied to define the relationship between the measured OD and the viable cell count including linear models (e.g. Jorgensen and Schulz 1985; Schulz et al. 1988; Begot et al.…”

Section: Discussionmentioning

confidence: 99%

Environmental factors influencing the relationship between optical density and cell count for Listeria monocytogenes

et al. 2005

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Aims: The effect of temperature (2-30°C), pH (4AE8-7AE4) and water activity (0AE946-0AE995) 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.

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“…However, since bacterial growth is always necessary, it never will be a very rapid technique. For pure cultures, J0r-gensen and Schulz (43) found that the initial numbers of microorganisms in an inoculum could be deduced from growth curve parameters. The authors used the Cobas Bact Centrifugal Analyzer.…”

Section: Turbidimetric Measurementsmentioning

confidence: 99%

Changing perspectives in food microbiology: Implementation of rapid microbiological analyses in modern food processing

Veld

Hartog

Hofstra

1988

Food Reviews International

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This review article summarizes the perspective for the introduction of novel microbiological techniques into modern food manufacturing and processing. Changes are discussed that have occurred recently in the microbiological control of food operations (process microbiology)-for example, the "hazard analysis critical control point" (HACCP) concept, which can be elaborated to a longitudinal integrated chain assessment by monitoring critical control points. In addition, we describe the recent developments in rapid analytical methodology that can be implemented under these concepts. These techniques are based on two major approaches; that is, they are either aimed at estimating the total microbial load as a hygiene parameter, or at detecting and enumerating specific pathogenic or toxigenic microorganisms and their metabolites. We conclude that, at this moment, several of these methods are significant improvements compared with the conventional techniques. However their use in preventive quality assurance by integrated chain assessment, as well as in routine food (end product) control, has been limited to certain areas of the food industries as yet.

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Turbidimetric measurement as a rapid method for the determination of the bacteriological quality of minced meat

Cited by 20 publications

References 1 publication

Critical Assessment of the Time‐to‐Detection Method for Accurate Estimation of Microbial Growth Parameters

Critical Assessment of the Time‐to‐Detection Method for Accurate Estimation of Microbial Growth Parameters

Environmental factors influencing the relationship between optical density and cell count for Listeria monocytogenes

Changing perspectives in food microbiology: Implementation of rapid microbiological analyses in modern food processing

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