Mathematical modeling of microbial growth in milk

Detalhes bibliográficos
Autor(a) principal: Teleken,Jhony Tiago
Data de Publicação: 2011
Outros Autores: Robazza,Weber da Silva, Gomes,Gilmar de Almeida
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Food Science and Technology (Campinas)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612011000400010
Resumo: A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.
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spelling Mathematical modeling of microbial growth in milkpredictive microbiologydairy productsfood safetyA mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.Sociedade Brasileira de Ciência e Tecnologia de Alimentos2011-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612011000400010Food Science and Technology v.31 n.4 2011reponame:Food Science and Technology (Campinas)instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)instacron:SBCTA10.1590/S0101-20612011000400010info:eu-repo/semantics/openAccessTeleken,Jhony TiagoRobazza,Weber da SilvaGomes,Gilmar de Almeidaeng2012-02-06T00:00:00Zoai:scielo:S0101-20612011000400010Revistahttp://www.scielo.br/ctaONGhttps://old.scielo.br/oai/scielo-oai.php||revista@sbcta.org.br1678-457X0101-2061opendoar:2012-02-06T00:00Food Science and Technology (Campinas) - Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)false
dc.title.none.fl_str_mv Mathematical modeling of microbial growth in milk
title Mathematical modeling of microbial growth in milk
spellingShingle Mathematical modeling of microbial growth in milk
Teleken,Jhony Tiago
predictive microbiology
dairy products
food safety
title_short Mathematical modeling of microbial growth in milk
title_full Mathematical modeling of microbial growth in milk
title_fullStr Mathematical modeling of microbial growth in milk
title_full_unstemmed Mathematical modeling of microbial growth in milk
title_sort Mathematical modeling of microbial growth in milk
author Teleken,Jhony Tiago
author_facet Teleken,Jhony Tiago
Robazza,Weber da Silva
Gomes,Gilmar de Almeida
author_role author
author2 Robazza,Weber da Silva
Gomes,Gilmar de Almeida
author2_role author
author
dc.contributor.author.fl_str_mv Teleken,Jhony Tiago
Robazza,Weber da Silva
Gomes,Gilmar de Almeida
dc.subject.por.fl_str_mv predictive microbiology
dairy products
food safety
topic predictive microbiology
dairy products
food safety
description A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.
publishDate 2011
dc.date.none.fl_str_mv 2011-12-01
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=S0101-20612011000400010
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612011000400010
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0101-20612011000400010
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 Sociedade Brasileira de Ciência e Tecnologia de Alimentos
publisher.none.fl_str_mv Sociedade Brasileira de Ciência e Tecnologia de Alimentos
dc.source.none.fl_str_mv Food Science and Technology v.31 n.4 2011
reponame:Food Science and Technology (Campinas)
instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
instacron:SBCTA
instname_str Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
instacron_str SBCTA
institution SBCTA
reponame_str Food Science and Technology (Campinas)
collection Food Science and Technology (Campinas)
repository.name.fl_str_mv Food Science and Technology (Campinas) - Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
repository.mail.fl_str_mv ||revista@sbcta.org.br
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