A model describing the relationship between lag time and mild temperature increase duration

Bréand, Sophie; Fardel, G.; Flandrois, Jean-Pierre; Rosso, L.; Tomassone, R.

doi:10.1016/s0168-1605(97)00093-7

Cited by 33 publications

(11 citation statements)

References 23 publications

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“…Bunning et al (1990) and Bréand et al (1997), explain that when the bacteria recover from the duration stress and become exposed to increasing temperatures, they can grow to infective doses. Some of the food samples that were exposed to contaminated surfaces at temperatures above 45°C and did not show presence of viable cells, can nevertheless be a potential risk to consumers in the event that the nonculturable organisms become resuscitated and grow to infective doses following temperature drop or increase.…”

Section: Discussionmentioning

confidence: 99%

Quantification and variability of Escherichia coli and Staphylococcus aureus cross-contamination during serving and consumption of cooked thick porridge in Lungwena rural households, Malawi

et al. 2009

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Section: Discussionmentioning

confidence: 99%

Quantification and variability of Escherichia coli and Staphylococcus aureus cross-contamination during serving and consumption of cooked thick porridge in Lungwena rural households, Malawi

et al. 2009

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“…4), discrepancies between predicted growth regions and observed growth curves were found for initial bacterial concentrations of 10 2 and 10 0 CFU ⅐ ml Ϫ1 . The change from an inoculum of approximately 10 2 CFU ⅐ ml Ϫ1 maintained at 30°C for 14 h to an inoculum of about 1 CFU ⅐ ml Ϫ1 starved for 840 h at 30°C led to an increase in lag time from 32.6 to 66.6 h. The extension of lag phase with physical injury of cells has been frequently reported (14,17,21,22), and models describing the effect of heat injury on subsequent lag period have been published for L. monocytogenes (6,7,23). Albertson et al…”

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confidence: 98%

Significance of Inoculum Size in the Lag Time of Listeria monocytogenes

Augustin

Brouillaud-Delattre

Rosso

et al. 2000

Appl Environ Microbiol

104

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The lag time of Listeria monocytogenes growing under suboptimal conditions (low nutrient concentrations, pH 6, and 6.5°C) was extended when the inoculum was severely stressed by starvation and the inoculum size was very small. Predictive microbiology should deal with bacterial stress and stochastic approaches to improve its value for the agro-food industry.In predictive microbiology, it is commonly assumed that inoculum size has no effect on subsequent microbial growth, and some studies (8, 9, 10) have confirmed this for growth of Listeria monocytogenes. However, Gay et al. (12) observed that inoculum size could have an effect on the duration of the lag phase of L. monocytogenes under particular conditions simulating soft cheese ripening. This observation could challenge the validity of predictive models because growth modelling is usually done with initial concentrations of bacteria higher than 10 3 CFU ⅐ ml Ϫ1 , even though foods are usually contaminated with lower numbers of cells.It has been shown with other bacteria, like Bacillus (19), Achromobacter delmarvae, Micrococcus luteus (see reference 16 for review), and Salmonella (26), that the duration of the lag phase depends inversely on the size of the inoculum. This phenomenon was observed only under a restricted range of conditions, for example, in poor but not in rich media, with starved cells (16), or with heat-injured cells (26). The aim of this work was to study the effect of inoculum size on the lag phase of L. monocytogenes growing in a poor medium, i.e., broth, containing only 1 g of Bacto Peptone (Difco Laboratories, Detroit, Mich.) per liter plus 0.85% sodium chloride (Prolabo, Paris, France) (TS), under suboptimal conditions: pH 6 and 6.5°C and with cells stressed by starvation.L. monocytogenes Scott A maintained on tryptone-soya agar (Oxoid, Unipath, Ltd., Basingstoke, Hampshire, England) at 4°C was subcultured onto tryptone-soya agar (Oxoid) plus 0.6% yeast extract (AES, Combourg, France) (TSYE) at 37°C for 24 h, and five colonies were transferred into TSYE broth and incubated at 30°C for 24 h. This culture was used to inoculate TSYE broth to prepare inocula at 30°C. The change in viable count of L. monocytogenes in TSYE broth at 30°C determined on nonselective TSYE agar and selective Palcam (Oxoid) agar is shown in Fig. 1. The percentage of injured cells was determined by differential counts on selective and nonselective media (24). Inocula were prepared at 30°C for 14, 160, and 840 h to obtain cells in late log phase, early stationary phase after a decrease in cell viability of 96.8% viable cells and 35% injured cells and late stationary phase with a loss of viability of 99.9% and 21% injured cells (Fig.

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“…As natural contaminations of foods occur with very few cells which are occasionally stressed by the food processing and the industry environment, it is essential to improve models by taking into account injuries encountered by the cells before they contaminate the foods and by using a stochastic approach dealing with the variability of the individual behavior of microbial cells. Models have been developed to take the effect of injuries on the bacterial lag times into account (11,12,39). Similarly, the individual response was also tackled by some authors such as Baranyi (6), who showed the relationship between the individual lag time distributions and the lag time of the bacterial population.…”

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Influence of Stress on Individual Lag Time Distributions of Listeria monocytogenes

Guillier

Pardon

Augustin

2005

Appl Environ Microbiol

114

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The effects of nine common food industry stresses on the times to the turbidity (T d ) distribution of Listeria monocytogenes were determined. It was established that the main source of the variability of T d for stressed cells was the variability of individual lag times. The distributions of T d revealed that there was a noticeable difference in response to the stresses encountered by the L. monocytogenes cells. The applied stresses led to significant changes of the shape, the mean, and the variance of the distributions. The variance of T d of wells inoculated with single cells issued from a culture in the exponential growth phase was multiplied by at least 6 and up to 355 for wells inoculated with stressed cells. These results suggest stress-induced variability may be important in determining the reliability of predictive microbiological models.

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A model describing the relationship between lag time and mild temperature increase duration

Cited by 33 publications

References 23 publications

Quantification and variability of Escherichia coli and Staphylococcus aureus cross-contamination during serving and consumption of cooked thick porridge in Lungwena rural households, Malawi

Quantification and variability of Escherichia coli and Staphylococcus aureus cross-contamination during serving and consumption of cooked thick porridge in Lungwena rural households, Malawi

Significance of Inoculum Size in the Lag Time of Listeria monocytogenes

Influence of Stress on Individual Lag Time Distributions of Listeria monocytogenes

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