Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple

Russet on ‘Golden Delicious’ apple (Malus × domestica Borkh.) fruit is a physiological disorder that causes major economic losses to growers. Large variations occur in the severity of russet from one year to another. In Girona (Spain), good correlations were found between the annual severity of russ...

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Detalhes bibliográficos
Autores: Barceló i Vidal, Carles, Bonany, J., Martín Fernández, Josep Antoni, Carbó, J.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2013
País:España
Recursos: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:10256/13741
Acesso em linha:http://hdl.handle.net/10256/13741
Access Level:acceso embargado
Palavra-chave:Anàlisi multivariable
Multivariate analysis
Correlació (Estadística)
Correlation (Statistics)
Pomes -- Malalties i plagues -- Mètodes estadístics
Apples -- Diseases and pests -- Statistical methods
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repository_id_str
spelling Modelling of weather parameters to predict russet on ‘Golden Delicious’ appleBarceló i Vidal, CarlesBonany, J.Martín Fernández, Josep AntoniCarbó, J.Anàlisi multivariableMultivariate analysisCorrelació (Estadística)Correlation (Statistics)Pomes -- Malalties i plagues -- Mètodes estadísticsApples -- Diseases and pests -- Statistical methodsRusset on ‘Golden Delicious’ apple (Malus × domestica Borkh.) fruit is a physiological disorder that causes major economic losses to growers. Large variations occur in the severity of russet from one year to another. In Girona (Spain), good correlations were found between the annual severity of russet at harvest and several weather parameters measured shortly after full bloom. A specific statistical methodology for the analysis of compositional data (CoDa) was used to establish these correlations. The most important factor was the percentage of time at relative humidity values > 55% from 30 – 34 d after full bloom (DAFB), which yielded a high correlation (R = 0.80). The percentage of rainy days from 0 – 34 DAFB was also positively correlated with the severity of russet (R = 0.80). Ordinal logit regression models that included these two climatic variables strongly predicted a low, moderate, or high annual severity of russet. Understanding the effects of weather on russet, and developing predictive models may help to manage the marketing of this apple variety which is prone to russet in some areas of cultivationThis research was supported by the Spanish Ministry of Science and Innovation under Projects MTM2009 13272 and MTM2012-33236, and by the Agència de Gestió d’Ajuts Universitaris i de Recerca of the Generalitat de Catalunya (Ref. 2009SGR424)Taylor & FrancisMinisterio de Ciencia e Innovación (Espanya)Ministerio de Economía y Competitividad (Espanya)infoinfo2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10256/13741http://hdl.handle.net/10256/13741© Journal of Horticultural Science and Biotechnology, 2013, vol. 88, núm. 5, p. 624-630Articles publicats (D-IMA)reponame: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/10.1080/14620316.2013.11513016info:eu-repo/semantics/altIdentifier/issn/1462-0316info:eu-repo/semantics/altIdentifier/eissn/2380-4084info:eu-repo/grantAgreement/MICINN//MTM2009-13272info:eu-repo/grantAgreement/MINECO//MTM2012-33236Tots els drets reservatsinfo:eu-repo/semantics/embargoedAccessoai:recercat.cat:10256/137412026-05-29T05:05:01Z
dc.title.none.fl_str_mv Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple
title Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple
spellingShingle Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple
Barceló i Vidal, Carles
Anàlisi multivariable
Multivariate analysis
Correlació (Estadística)
Correlation (Statistics)
Pomes -- Malalties i plagues -- Mètodes estadístics
Apples -- Diseases and pests -- Statistical methods
title_short Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple
title_full Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple
title_fullStr Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple
title_full_unstemmed Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple
title_sort Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple
dc.creator.none.fl_str_mv Barceló i Vidal, Carles
Bonany, J.
Martín Fernández, Josep Antoni
Carbó, J.
author Barceló i Vidal, Carles
author_facet Barceló i Vidal, Carles
Bonany, J.
Martín Fernández, Josep Antoni
Carbó, J.
author_role author
author2 Bonany, J.
Martín Fernández, Josep Antoni
Carbó, J.
author2_role author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia e Innovación (Espanya)
Ministerio de Economía y Competitividad (Espanya)
dc.subject.none.fl_str_mv Anàlisi multivariable
Multivariate analysis
Correlació (Estadística)
Correlation (Statistics)
Pomes -- Malalties i plagues -- Mètodes estadístics
Apples -- Diseases and pests -- Statistical methods
topic Anàlisi multivariable
Multivariate analysis
Correlació (Estadística)
Correlation (Statistics)
Pomes -- Malalties i plagues -- Mètodes estadístics
Apples -- Diseases and pests -- Statistical methods
description Russet on ‘Golden Delicious’ apple (Malus × domestica Borkh.) fruit is a physiological disorder that causes major economic losses to growers. Large variations occur in the severity of russet from one year to another. In Girona (Spain), good correlations were found between the annual severity of russet at harvest and several weather parameters measured shortly after full bloom. A specific statistical methodology for the analysis of compositional data (CoDa) was used to establish these correlations. The most important factor was the percentage of time at relative humidity values > 55% from 30 – 34 d after full bloom (DAFB), which yielded a high correlation (R = 0.80). The percentage of rainy days from 0 – 34 DAFB was also positively correlated with the severity of russet (R = 0.80). Ordinal logit regression models that included these two climatic variables strongly predicted a low, moderate, or high annual severity of russet. Understanding the effects of weather on russet, and developing predictive models may help to manage the marketing of this apple variety which is prone to russet in some areas of cultivation
publishDate 2013
dc.date.none.fl_str_mv 2013
info
info
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/10256/13741
http://hdl.handle.net/10256/13741
url http://hdl.handle.net/10256/13741
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1080/14620316.2013.11513016
info:eu-repo/semantics/altIdentifier/issn/1462-0316
info:eu-repo/semantics/altIdentifier/eissn/2380-4084
info:eu-repo/grantAgreement/MICINN//MTM2009-13272
info:eu-repo/grantAgreement/MINECO//MTM2012-33236
dc.rights.none.fl_str_mv Tots els drets reservats
info:eu-repo/semantics/embargoedAccess
rights_invalid_str_mv Tots els drets reservats
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv © Journal of Horticultural Science and Biotechnology, 2013, vol. 88, núm. 5, p. 624-630
Articles publicats (D-IMA)
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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score 15.811543

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