Modeling the pressure inactivation dynamics of Escherichia coli
Main Author: | |
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Publication Date: | 2005 |
Other Authors: | , , , |
Format: | Article |
Language: | eng |
Source: | Brazilian Journal of Medical and Biological Research |
Download full: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2005000800014 |
Summary: | Escherichia coli, as a model microorganism, was treated in phosphate-buffered saline under high hydrostatic pressure between 100 and 300 MPa, and the inactivation dynamics was investigated from the viewpoint of predictive microbiology. Inactivation data were curve fitted by typical predictive models: logistic, Gompertz and Weibull functions. Weibull function described the inactivation curve the best. Two parameters of Weibull function were calculated for each holding pressure and their dependence on holding pressure was obtained by interpolation. With the interpolated parameters, inactivation curves were simulated and compared with the experimental data sets. |
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Modeling the pressure inactivation dynamics of Escherichia coliPredictive microbiologyPressureEscherichia coliInactivationModelEscherichia coli, as a model microorganism, was treated in phosphate-buffered saline under high hydrostatic pressure between 100 and 300 MPa, and the inactivation dynamics was investigated from the viewpoint of predictive microbiology. Inactivation data were curve fitted by typical predictive models: logistic, Gompertz and Weibull functions. Weibull function described the inactivation curve the best. Two parameters of Weibull function were calculated for each holding pressure and their dependence on holding pressure was obtained by interpolation. With the interpolated parameters, inactivation curves were simulated and compared with the experimental data sets.Associação Brasileira de Divulgação Científica2005-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2005000800014Brazilian Journal of Medical and Biological Research v.38 n.8 2005reponame:Brazilian Journal of Medical and Biological Researchinstname:Associação Brasileira de Divulgação Científica (ABDC)instacron:ABDC10.1590/S0100-879X2005000800014info:eu-repo/semantics/openAccessYamamoto,K.Matsubara,M.Kawasaki,S.Bari,M.L.Kawamoto,S.eng2005-07-30T00:00:00Zoai:scielo:S0100-879X2005000800014Revistahttps://www.bjournal.org/https://old.scielo.br/oai/scielo-oai.phpbjournal@terra.com.br||bjournal@terra.com.br1414-431X0100-879Xopendoar:2005-07-30T00:00Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC)false |
dc.title.none.fl_str_mv |
Modeling the pressure inactivation dynamics of Escherichia coli |
title |
Modeling the pressure inactivation dynamics of Escherichia coli |
spellingShingle |
Modeling the pressure inactivation dynamics of Escherichia coli Yamamoto,K. Predictive microbiology Pressure Escherichia coli Inactivation Model |
title_short |
Modeling the pressure inactivation dynamics of Escherichia coli |
title_full |
Modeling the pressure inactivation dynamics of Escherichia coli |
title_fullStr |
Modeling the pressure inactivation dynamics of Escherichia coli |
title_full_unstemmed |
Modeling the pressure inactivation dynamics of Escherichia coli |
title_sort |
Modeling the pressure inactivation dynamics of Escherichia coli |
author |
Yamamoto,K. |
author_facet |
Yamamoto,K. Matsubara,M. Kawasaki,S. Bari,M.L. Kawamoto,S. |
author_role |
author |
author2 |
Matsubara,M. Kawasaki,S. Bari,M.L. Kawamoto,S. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Yamamoto,K. Matsubara,M. Kawasaki,S. Bari,M.L. Kawamoto,S. |
dc.subject.por.fl_str_mv |
Predictive microbiology Pressure Escherichia coli Inactivation Model |
topic |
Predictive microbiology Pressure Escherichia coli Inactivation Model |
description |
Escherichia coli, as a model microorganism, was treated in phosphate-buffered saline under high hydrostatic pressure between 100 and 300 MPa, and the inactivation dynamics was investigated from the viewpoint of predictive microbiology. Inactivation data were curve fitted by typical predictive models: logistic, Gompertz and Weibull functions. Weibull function described the inactivation curve the best. Two parameters of Weibull function were calculated for each holding pressure and their dependence on holding pressure was obtained by interpolation. With the interpolated parameters, inactivation curves were simulated and compared with the experimental data sets. |
publishDate |
2005 |
dc.date.none.fl_str_mv |
2005-08-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2005000800014 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2005000800014 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0100-879X2005000800014 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Divulgação Científica |
publisher.none.fl_str_mv |
Associação Brasileira de Divulgação Científica |
dc.source.none.fl_str_mv |
Brazilian Journal of Medical and Biological Research v.38 n.8 2005 reponame:Brazilian Journal of Medical and Biological Research instname:Associação Brasileira de Divulgação Científica (ABDC) instacron:ABDC |
instname_str |
Associação Brasileira de Divulgação Científica (ABDC) |
instacron_str |
ABDC |
institution |
ABDC |
reponame_str |
Brazilian Journal of Medical and Biological Research |
collection |
Brazilian Journal of Medical and Biological Research |
repository.name.fl_str_mv |
Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC) |
repository.mail.fl_str_mv |
bjournal@terra.com.br||bjournal@terra.com.br |
_version_ |
1754302933907800064 |