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Statistical analysis of biogenic amines formation process under different levels of selected factors

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dc.title Statistical analysis of biogenic amines formation process under different levels of selected factors en
dc.contributor.author Tláskal, Martin
dc.contributor.author Pleva, Pavel
dc.contributor.author Michálek, Jaroslav
dc.contributor.author Buňková, Leona
dc.contributor.author Buňka, František
dc.relation.ispartof International Journal of Biology and Biomedical Engineering
dc.identifier.issn 1998-4510 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2014
utb.relation.volume 8
dc.citation.spage 197
dc.citation.epage 204
dc.type article
dc.language.iso en
dc.publisher North Atlantic University Union (NAUN)
dc.relation.uri http://www.naun.org/cms.action?id=7620
dc.subject Biogenic amines en
dc.subject Gompertz curve en
dc.subject Growth model en
dc.subject Logistic curve en
dc.description.abstract Some bacterial strains of enterococci are commonly used in food industry and therefore their ability of biogenic amine formation should be investigated. This enables to indicate decarboxylase-positive strains. Within the process of decarboxylation, these strains produce high amount of biogenic amine, which is a toxicologically important compound. Biogenic amines are present in certain foodstuffs (cheese, meat, wine.) and at high concentrations they are considered risk factors for human health. The aim of this contribution was to explore production of eight chosen biogenic amines by Enterococcus faecium (DPE 002) from rabbit meat (Oryctolagus cuniculus f. domesticus) and to evaluate the effect of selected factors on the production. To fit the data subsets involving different conditions of the experiment, appropriate regression models were used. Some of the growth curves such as Gompertz, logistic, and Richards are found to be very useful in many areas. The most suitable models for our data appeared to be Gompertz and logistic. Their three regression parameters, which are of biological interest, are an asymptotic value of concentration, a maximum production rate and a lag time. Model parameters were estimated and tested. The effect of different factor levels on the parameter values is studied. en
utb.faculty Faculty of Technology
dc.identifier.uri http://hdl.handle.net/10563/1004269
utb.identifier.obdid 43873511
utb.identifier.scopus 2-s2.0-84925441679
utb.source j-scopus
dc.date.accessioned 2015-05-22T08:01:39Z
dc.date.available 2015-05-22T08:01:39Z
utb.contributor.internalauthor Pleva, Pavel
utb.contributor.internalauthor Buňková, Leona
utb.contributor.internalauthor Buňka, František
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