How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach

Detalhes bibliográficos
Autor(a) principal: Negrão, Djanira Rodrigues [UNESP]
Data de Publicação: 2021
Outros Autores: Mischan, Martha Maria [UNESP], de Pinho, Sheila Zambello [UNESP], de Carvalho, Lídia Raquel [UNESP], Gomes, Rafaela Lanças [UNESP], de Souza Passos, José Raimundo [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.funbio.2021.05.007
http://hdl.handle.net/11449/207869
Resumo: This study aimed to model mycelial growth in a factorial experiment with two species of white rot fungi growing at five temperatures. The nonlinear models evaluated were logistic, Gompertz, Weibull and von Bertalanffy. The adjustments were performed first by evaluating the fixed and mixed-effects models with random effects, added to the fixed parameters. Then, the best adjusted model was improved by an adequated covariance structure, and dummy variables were added to the parameters asymptote (α) and abscissa of the inflection point (β) in the model in order to verify the effect of the experiment factors, species and temperatures on the regression parameters. The criteria used to compare models were residual variance and Akaike information criterion. Gompertz and von Bertalanffy mixed-effects models were better adjusted. The parameters differed between species. Moreover, the linear and quadratic effects of temperature evaluated in each species were significant. The models were reparametrized in order to consider two parameters of interest: velocity (μ) at the inflection point and lag time (λ). The maximum growth velocity was obtained at 25.4 °C by S. ostrea, while T. villosa was achieved at 30.5 °C; both fungi suffered less lag time by increasing the temperature.
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spelling How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approachDummy variablesGompertzLogisticvon BertalanffyWeibullThis study aimed to model mycelial growth in a factorial experiment with two species of white rot fungi growing at five temperatures. The nonlinear models evaluated were logistic, Gompertz, Weibull and von Bertalanffy. The adjustments were performed first by evaluating the fixed and mixed-effects models with random effects, added to the fixed parameters. Then, the best adjusted model was improved by an adequated covariance structure, and dummy variables were added to the parameters asymptote (α) and abscissa of the inflection point (β) in the model in order to verify the effect of the experiment factors, species and temperatures on the regression parameters. The criteria used to compare models were residual variance and Akaike information criterion. Gompertz and von Bertalanffy mixed-effects models were better adjusted. The parameters differed between species. Moreover, the linear and quadratic effects of temperature evaluated in each species were significant. The models were reparametrized in order to consider two parameters of interest: velocity (μ) at the inflection point and lag time (λ). The maximum growth velocity was obtained at 25.4 °C by S. ostrea, while T. villosa was achieved at 30.5 °C; both fungi suffered less lag time by increasing the temperature.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Plant Protection Department College of Agricultural Sciences (FCA) Lageado Experimental Farm São Paulo State University (UNESP)Bioestatistic Plant Biology Parasitology and Zoology Department Bioscience Institute (IBB) Universidade Estadual Paulista (UNESP)Plant Protection Department College of Agricultural Sciences (FCA) Lageado Experimental Farm São Paulo State University (UNESP)Bioestatistic Plant Biology Parasitology and Zoology Department Bioscience Institute (IBB) Universidade Estadual Paulista (UNESP)FAPESP: 2013/15747–4Universidade Estadual Paulista (Unesp)Negrão, Djanira Rodrigues [UNESP]Mischan, Martha Maria [UNESP]de Pinho, Sheila Zambello [UNESP]de Carvalho, Lídia Raquel [UNESP]Gomes, Rafaela Lanças [UNESP]de Souza Passos, José Raimundo [UNESP]2021-06-25T11:02:25Z2021-06-25T11:02:25Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.funbio.2021.05.007Fungal Biology.1878-6146http://hdl.handle.net/11449/20786910.1016/j.funbio.2021.05.0072-s2.0-85107804252Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengFungal Biologyinfo:eu-repo/semantics/openAccess2024-10-14T19:56:23Zoai:repositorio.unesp.br:11449/207869Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462024-10-14T19:56:23Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach
title How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach
spellingShingle How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach
Negrão, Djanira Rodrigues [UNESP]
Dummy variables
Gompertz
Logistic
von Bertalanffy
Weibull
title_short How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach
title_full How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach
title_fullStr How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach
title_full_unstemmed How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach
title_sort How temperature variation affects white-rot fungi mycelial growth dynamics: A nonlinear mixed models approach
author Negrão, Djanira Rodrigues [UNESP]
author_facet Negrão, Djanira Rodrigues [UNESP]
Mischan, Martha Maria [UNESP]
de Pinho, Sheila Zambello [UNESP]
de Carvalho, Lídia Raquel [UNESP]
Gomes, Rafaela Lanças [UNESP]
de Souza Passos, José Raimundo [UNESP]
author_role author
author2 Mischan, Martha Maria [UNESP]
de Pinho, Sheila Zambello [UNESP]
de Carvalho, Lídia Raquel [UNESP]
Gomes, Rafaela Lanças [UNESP]
de Souza Passos, José Raimundo [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Negrão, Djanira Rodrigues [UNESP]
Mischan, Martha Maria [UNESP]
de Pinho, Sheila Zambello [UNESP]
de Carvalho, Lídia Raquel [UNESP]
Gomes, Rafaela Lanças [UNESP]
de Souza Passos, José Raimundo [UNESP]
dc.subject.por.fl_str_mv Dummy variables
Gompertz
Logistic
von Bertalanffy
Weibull
topic Dummy variables
Gompertz
Logistic
von Bertalanffy
Weibull
description This study aimed to model mycelial growth in a factorial experiment with two species of white rot fungi growing at five temperatures. The nonlinear models evaluated were logistic, Gompertz, Weibull and von Bertalanffy. The adjustments were performed first by evaluating the fixed and mixed-effects models with random effects, added to the fixed parameters. Then, the best adjusted model was improved by an adequated covariance structure, and dummy variables were added to the parameters asymptote (α) and abscissa of the inflection point (β) in the model in order to verify the effect of the experiment factors, species and temperatures on the regression parameters. The criteria used to compare models were residual variance and Akaike information criterion. Gompertz and von Bertalanffy mixed-effects models were better adjusted. The parameters differed between species. Moreover, the linear and quadratic effects of temperature evaluated in each species were significant. The models were reparametrized in order to consider two parameters of interest: velocity (μ) at the inflection point and lag time (λ). The maximum growth velocity was obtained at 25.4 °C by S. ostrea, while T. villosa was achieved at 30.5 °C; both fungi suffered less lag time by increasing the temperature.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-25T11:02:25Z
2021-06-25T11:02:25Z
2021-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.funbio.2021.05.007
Fungal Biology.
1878-6146
http://hdl.handle.net/11449/207869
10.1016/j.funbio.2021.05.007
2-s2.0-85107804252
url http://dx.doi.org/10.1016/j.funbio.2021.05.007
http://hdl.handle.net/11449/207869
identifier_str_mv Fungal Biology.
1878-6146
10.1016/j.funbio.2021.05.007
2-s2.0-85107804252
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Fungal Biology
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv repositoriounesp@unesp.br
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