A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature

Abstract A two-step modeling approach was used for predicting the effect of temperature on the growth of Xanthomonas arboricola pv. pruni, causal agent of bacterial spot disease of stone fruit. The in vitro growth of seven strains was monitored at temperatures from 5 to 35˚C with a Bioscreen C syste...

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Autores: Morales Nicolàs, Gerard, Llorente i Cabratosa, Isidre, Montesinos Seguí, Emilio, Moragrega i Garcia, Concepció
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/14060
Acceso en línea:http://hdl.handle.net/10256/14060
Access Level:acceso abierto
Palabra clave:Arbres fruiters -- Malalties i plagues
Fruit trees -- Diseases and pests
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spelling A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperatureMorales Nicolàs, GerardLlorente i Cabratosa, IsidreMontesinos Seguí, EmilioMoragrega i Garcia, ConcepcióArbres fruiters -- Malalties i plaguesFruit trees -- Diseases and pestsAbstract A two-step modeling approach was used for predicting the effect of temperature on the growth of Xanthomonas arboricola pv. pruni, causal agent of bacterial spot disease of stone fruit. The in vitro growth of seven strains was monitored at temperatures from 5 to 35˚C with a Bioscreen C system, and a calibrating equation was generated for converting optical den- sities to viable counts. In primary modeling, Baranyi, Buchanan, and modified Gompertz equations were fitted to viable count growth curves over the entire temperature range. The modified Gompertz model showed the best fit to the data, and it was selected to estimate the bacterial growth parameters at each temperature. Secondary modeling of maximum specific growth rate as a function of temperature was performed by using the Ratkowsky model and its variations. The modified Ratkowsky model showed the best goodness of fit to maximum specific growth rate estimates, and it was validated successfully for the seven strains at four additional temperatures. The model generated in this work will be used for predicting temperature-based Xanthomonas arboricola pv. pruni growth rate and derived potential daily doublings, and included as the inoculum potential component of a bacterial spot of stone fruit disease forecasterThis research was supported, in part, by grants from the Ministerio de Educación, Ciencia y Deporte (AGL2013-41405-R and from the University of Girona (SING12/13 and MPCUdG2016/085. Gerard Morales was the recipient of predocotoral fellowships from the University of Girona (BR 2013/31) and from MECD (FPU13/04123) from SpainPublic Library of Science (PLoS)Ministerio de Economía y Competitividad (Espanya)2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10256/14060http://hdl.handle.net/10256/14060PLoS One, 2017, vol. 12, núm. 5, p. e0177583Articles publicats (D-EQATA)Morales Nicolás, Gerard Llorente i Cabratosa, Isidre Montesinos Seguí, Emilio Moragrega i Garcia, Concepció 2017 A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature PLoS One 12 5 e0177583reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0177583info:eu-repo/semantics/altIdentifier/eissn/1932-6203info:eu-repo/semantics/altIdentifier/eissn/1932-6203info:eu-repo/grantAgreement/MINECO//AGL2013-41405-RReconeixement 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:recercat.cat:10256/140602026-05-29T05:05:01Z
dc.title.none.fl_str_mv A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature
title A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature
spellingShingle A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature
Morales Nicolàs, Gerard
Arbres fruiters -- Malalties i plagues
Fruit trees -- Diseases and pests
title_short A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature
title_full A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature
title_fullStr A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature
title_full_unstemmed A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature
title_sort A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature
dc.creator.none.fl_str_mv Morales Nicolàs, Gerard
Llorente i Cabratosa, Isidre
Montesinos Seguí, Emilio
Moragrega i Garcia, Concepció
author Morales Nicolàs, Gerard
author_facet Morales Nicolàs, Gerard
Llorente i Cabratosa, Isidre
Montesinos Seguí, Emilio
Moragrega i Garcia, Concepció
author_role author
author2 Llorente i Cabratosa, Isidre
Montesinos Seguí, Emilio
Moragrega i Garcia, Concepció
author2_role author
author
author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (Espanya)
dc.subject.none.fl_str_mv Arbres fruiters -- Malalties i plagues
Fruit trees -- Diseases and pests
topic Arbres fruiters -- Malalties i plagues
Fruit trees -- Diseases and pests
description Abstract A two-step modeling approach was used for predicting the effect of temperature on the growth of Xanthomonas arboricola pv. pruni, causal agent of bacterial spot disease of stone fruit. The in vitro growth of seven strains was monitored at temperatures from 5 to 35˚C with a Bioscreen C system, and a calibrating equation was generated for converting optical den- sities to viable counts. In primary modeling, Baranyi, Buchanan, and modified Gompertz equations were fitted to viable count growth curves over the entire temperature range. The modified Gompertz model showed the best fit to the data, and it was selected to estimate the bacterial growth parameters at each temperature. Secondary modeling of maximum specific growth rate as a function of temperature was performed by using the Ratkowsky model and its variations. The modified Ratkowsky model showed the best goodness of fit to maximum specific growth rate estimates, and it was validated successfully for the seven strains at four additional temperatures. The model generated in this work will be used for predicting temperature-based Xanthomonas arboricola pv. pruni growth rate and derived potential daily doublings, and included as the inoculum potential component of a bacterial spot of stone fruit disease forecaster
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/14060
http://hdl.handle.net/10256/14060
url http://hdl.handle.net/10256/14060
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0177583
info:eu-repo/semantics/altIdentifier/eissn/1932-6203
info:eu-repo/semantics/altIdentifier/eissn/1932-6203
info:eu-repo/grantAgreement/MINECO//AGL2013-41405-R
dc.rights.none.fl_str_mv Reconeixement 4.0 Internacional
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Reconeixement 4.0 Internacional
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Public Library of Science (PLoS)
publisher.none.fl_str_mv Public Library of Science (PLoS)
dc.source.none.fl_str_mv PLoS One, 2017, vol. 12, núm. 5, p. e0177583
Articles publicats (D-EQATA)
Morales Nicolás, Gerard Llorente i Cabratosa, Isidre Montesinos Seguí, Emilio Moragrega i Garcia, Concepció 2017 A model for predicting Xanthomonas arboricola pv. pruni growth as a function of temperature PLoS One 12 5 e0177583
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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