Predictive modeling of the aerobic growth of Staphylococcus aureus 196E using a nonlinear model and response surface analysis

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dc.contributor.authorEifert, Joseph D.en
dc.contributor.committeechairHackney, Cameron Rajen
dc.contributor.committeememberPierson, Merle D.en
dc.contributor.committeememberCarter, Walter Hans Jr.en
dc.contributor.committeememberDuncan, Susan E.en
dc.contributor.committeememberEigel, William N. IIIen
dc.contributor.departmentFood Science and Technologyen
dc.date.accessioned2014-03-14T20:12:48Zen
dc.date.adate2008-06-06en
dc.date.available2014-03-14T20:12:48Zen
dc.date.issued1994-12-15en
dc.date.rdate2013-09-22en
dc.date.sdate2008-06-06en
dc.description.abstractPathogenic bacteria in foods are affected by several factors which may interact to enhance or inhibit microbial growth. <u>Staphylococcus aureus</u> 196E was inoculated into Brain Heart Infusion broth formulated with either 0.5, 4.5 or 8.5% NaCI, adjusted to pH 5.0, 6.0 or 7.0, and incubated aerobically at 12, 20 or 28°C. Mathematical models to predict the growth of <u>S. aureus</u> 196E were developed using a modified Gompertz function and response surface methodology. Each predictive equation required the estimation of only 23 parameters with a biological meaning. These models determined the significance of time, incubation temperature, sodium chloride (NaCI) concentration, and either pH or the logₑ of the undissociated acid concentration and any interactions on growth kinetics. Separate models were developed for the cases where pH was altered with either acetic acid, acetic acid plus sodium hydroxide, lactic acid and hydrochloric acid. All models adequately predicted the log growth of S. aureus 196E. Several interactive relationships between the independent variables upon population growth were significant. Predicted responses to multiple factor interactions were displayed with three-dimensional and contour plots. One model developed from a smaller subset of the growth data demonstrated that models could be produced with much less data collection. Generally, predictions of growth showed that acetic acid was more inhibitory to growth than lactic and hydrochloric acids. Furthermore, predicted and observed growth was slower or reduced when the undissociated acetic acid concentration was elevated at a specific pH. This methodology can provide important information to food scientists about the growth kinetics of microorganisms and prediction ranges or confidence intervals for growth parameters. Consequently, the effects of food formulations and storage conditions on the growth kinetics of foodborne pathogens or spoilage microorganisms could be predicted.en
dc.description.degreePh. D.en
dc.format.extentxvi, 197 leavesen
dc.format.mediumBTDen
dc.format.mimetypeapplication/pdfen
dc.identifier.otheretd-06062008-164508en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06062008-164508/en
dc.identifier.urihttp://hdl.handle.net/10919/27970en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.haspartLD5655.V856_1994.E444.pdfen
dc.relation.isformatofOCLC# 32772162en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V856 1994.E444en
dc.subject.lcshStaphylococcus aureus -- Growth -- Mathematical modelsen
dc.titlePredictive modeling of the aerobic growth of <i>Staphylococcus aureus</i> 196E using a nonlinear model and response surface analysisen
dc.typeDissertationen
dc.type.dcmitypeTexten
thesis.degree.disciplineFood Science and Technologyen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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