| dc.contributor.author |
Gonzalez, M |
en |
| dc.contributor.author |
Skandamis, PN |
en |
| dc.contributor.author |
Hanninen, M-L |
en |
| dc.date.accessioned |
2014-06-06T06:49:10Z |
|
| dc.date.available |
2014-06-06T06:49:10Z |
|
| dc.date.issued |
2009 |
en |
| dc.identifier.issn |
01681605 |
en |
| dc.identifier.uri |
http://dx.doi.org/10.1016/j.ijfoodmicro.2009.09.022 |
en |
| dc.identifier.uri |
http://62.217.125.90/xmlui/handle/123456789/4475 |
|
| dc.subject |
Campylobacter jejuni |
en |
| dc.subject |
Chicken meat |
en |
| dc.subject |
Linear model |
en |
| dc.subject |
Modelling |
en |
| dc.subject |
Weibull model |
en |
| dc.subject.other |
antibiotic resistance |
en |
| dc.subject.other |
article |
en |
| dc.subject.other |
bacterial cell |
en |
| dc.subject.other |
bacterial kinetics |
en |
| dc.subject.other |
bacterial strain |
en |
| dc.subject.other |
bacterial survival |
en |
| dc.subject.other |
bacterial viability |
en |
| dc.subject.other |
calculation |
en |
| dc.subject.other |
Campylobacter jejuni |
en |
| dc.subject.other |
cell survival |
en |
| dc.subject.other |
chicken meat |
en |
| dc.subject.other |
controlled study |
en |
| dc.subject.other |
external validity |
en |
| dc.subject.other |
food analysis |
en |
| dc.subject.other |
genetic variability |
en |
| dc.subject.other |
mathematical model |
en |
| dc.subject.other |
nonhuman |
en |
| dc.subject.other |
prediction |
en |
| dc.subject.other |
risk assessment |
en |
| dc.subject.other |
simulation |
en |
| dc.subject.other |
storage temperature |
en |
| dc.subject.other |
temperature stress |
en |
| dc.subject.other |
Weibull model |
en |
| dc.subject.other |
Animals |
en |
| dc.subject.other |
Campylobacter jejuni |
en |
| dc.subject.other |
Chickens |
en |
| dc.subject.other |
Colony Count, Microbial |
en |
| dc.subject.other |
Computer Simulation |
en |
| dc.subject.other |
Food Handling |
en |
| dc.subject.other |
Food Microbiology |
en |
| dc.subject.other |
Meat |
en |
| dc.subject.other |
Microbial Viability |
en |
| dc.subject.other |
Models, Biological |
en |
| dc.subject.other |
Reproducibility of Results |
en |
| dc.subject.other |
Temperature |
en |
| dc.subject.other |
Time Factors |
en |
| dc.subject.other |
Bacteria (microorganisms) |
en |
| dc.subject.other |
Campylobacter |
en |
| dc.subject.other |
Campylobacter jejuni |
en |
| dc.subject.other |
Rattus |
en |
| dc.title |
A modified Weibull model for describing the survival of Campylobacter jejuni in minced chicken meat |
en |
| heal.type |
journalArticle |
en |
| heal.identifier.primary |
10.1016/j.ijfoodmicro.2009.09.022 |
en |
| heal.publicationDate |
2009 |
en |
| heal.abstract |
Campylobacter is one of the leading causes of foodborne bacterial enteritis. Since chicken meat may be an important source of C. jejuni, the aims of this study were (i) to evaluate the survival/inactivation of C. jejuni strain 49/7R and its antimicrobial resistant variants (49/7RAT and 49/7RATCIP32) in minced chicken meat during extended storage at temperatures ranging from - 20 °C to 25 °C and (ii) to test the suitability of the Weibull model for predicting the inactivation of C. jejuni in minced chicken meat in a wide range of temperatures. Minced chicken meat samples were inoculated with C. jejuni and log CFU/g were counted after different storage times at - 20 °C, - 5 °C, 4 °C, 15 °C or 25 °C. The log-linear and the Weibull models were used to fit a total of 15 inactivation curves. The mean value of R2adjusted for the correlation between the surviving bacterial cells observed and predicted by the Weibull model ranged from 0.986 to 0.994, and from 0.895 to 0.925 for the log-linear model, indicating closer agreement between the data and the Weibull model than for the log-linear one. From the Weibull model, p and δ parameters were described in a secondary model as a function of temperature using third-order polynomial fitting curves. Information from the secondary model served to predict survival curves for C. jejuni in minced chicken meat for an independent set of storage temperatures. Additionally, since δ parameter of the Weibull model is related to the D concept it served to determine the time (days) needed for the 1-log reduction of CFU/g; within the above mentioned temperature range. The results revealed that antimicrobial resistant variants survived longer than did the parent strains at all temperatures studied, indicated by the 1-log reduction time estimates. © 2009 Elsevier B.V. All rights reserved. |
en |
| heal.journalName |
International Journal of Food Microbiology |
en |
| dc.identifier.issue |
1 |
en |
| dc.identifier.volume |
136 |
en |
| dc.identifier.doi |
10.1016/j.ijfoodmicro.2009.09.022 |
en |
| dc.identifier.spage |
52 |
en |
| dc.identifier.epage |
58 |
en |