Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling

Detalhes bibliográficos
Autor(a) principal: Silva, Anderson Rodrigo da
Data de Publicação: 2014
Outros Autores: Cecon, Paulo Roberto, Dias, Carlos Tadeu dos Santos, Puiatti, Mário, Finger, Fernando Luiz, Carneiro, Antônio Policarpo Souza
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/78535
Resumo: Multivariate techniques have become a useful tool for studying the phenotypic diversity of Germplasm Bank accessions, since they make it possible to combine a variety of different information from these accessions. This study aimed to characterize the phenotypic dispersion of garlic (Allium sativum L.) using two multivariate techniques with different objective functions. Twenty accessions were morphologically characterized for bulb diameter, length, and weight; number of cloves per bulb; number of leaves per plant; and leaf area. Techniques based on generalized quadratic distance of Mahalanobis, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) clustering, and nMDS (nonmetrric MultiDimensional Scaling) were applied and the relative importance of variables quantified. The two multivariate techniques were capable of identifying cultivars with different characteristics, mainly regarding their classification in subgroups of common garlic or noble garlic, according to the number of cloves per bulb. The representation of the phenotypic distance of cultivars by multidimensional scaling was slightly more effective than that with UPGMA clustering.
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spelling Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling Multivariate techniques have become a useful tool for studying the phenotypic diversity of Germplasm Bank accessions, since they make it possible to combine a variety of different information from these accessions. This study aimed to characterize the phenotypic dispersion of garlic (Allium sativum L.) using two multivariate techniques with different objective functions. Twenty accessions were morphologically characterized for bulb diameter, length, and weight; number of cloves per bulb; number of leaves per plant; and leaf area. Techniques based on generalized quadratic distance of Mahalanobis, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) clustering, and nMDS (nonmetrric MultiDimensional Scaling) were applied and the relative importance of variables quantified. The two multivariate techniques were capable of identifying cultivars with different characteristics, mainly regarding their classification in subgroups of common garlic or noble garlic, according to the number of cloves per bulb. The representation of the phenotypic distance of cultivars by multidimensional scaling was slightly more effective than that with UPGMA clustering. Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2014-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/7853510.1590/S0103-90162014000100005Scientia Agricola; v. 71 n. 1 (2014); 38-43Scientia Agricola; Vol. 71 Núm. 1 (2014); 38-43Scientia Agricola; Vol. 71 No. 1 (2014); 38-431678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/78535/82590Copyright (c) 2015 Scientia Agricolainfo:eu-repo/semantics/openAccessSilva, Anderson Rodrigo daCecon, Paulo RobertoDias, Carlos Tadeu dos SantosPuiatti, MárioFinger, Fernando LuizCarneiro, Antônio Policarpo Souza2014-04-02T20:07:56Zoai:revistas.usp.br:article/78535Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2014-04-02T20:07:56Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
title Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
spellingShingle Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
Silva, Anderson Rodrigo da
title_short Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
title_full Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
title_fullStr Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
title_full_unstemmed Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
title_sort Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
author Silva, Anderson Rodrigo da
author_facet Silva, Anderson Rodrigo da
Cecon, Paulo Roberto
Dias, Carlos Tadeu dos Santos
Puiatti, Mário
Finger, Fernando Luiz
Carneiro, Antônio Policarpo Souza
author_role author
author2 Cecon, Paulo Roberto
Dias, Carlos Tadeu dos Santos
Puiatti, Mário
Finger, Fernando Luiz
Carneiro, Antônio Policarpo Souza
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Silva, Anderson Rodrigo da
Cecon, Paulo Roberto
Dias, Carlos Tadeu dos Santos
Puiatti, Mário
Finger, Fernando Luiz
Carneiro, Antônio Policarpo Souza
description Multivariate techniques have become a useful tool for studying the phenotypic diversity of Germplasm Bank accessions, since they make it possible to combine a variety of different information from these accessions. This study aimed to characterize the phenotypic dispersion of garlic (Allium sativum L.) using two multivariate techniques with different objective functions. Twenty accessions were morphologically characterized for bulb diameter, length, and weight; number of cloves per bulb; number of leaves per plant; and leaf area. Techniques based on generalized quadratic distance of Mahalanobis, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) clustering, and nMDS (nonmetrric MultiDimensional Scaling) were applied and the relative importance of variables quantified. The two multivariate techniques were capable of identifying cultivars with different characteristics, mainly regarding their classification in subgroups of common garlic or noble garlic, according to the number of cloves per bulb. The representation of the phenotypic distance of cultivars by multidimensional scaling was slightly more effective than that with UPGMA clustering.
publishDate 2014
dc.date.none.fl_str_mv 2014-02-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/78535
10.1590/S0103-90162014000100005
url https://www.revistas.usp.br/sa/article/view/78535
identifier_str_mv 10.1590/S0103-90162014000100005
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/78535/82590
dc.rights.driver.fl_str_mv Copyright (c) 2015 Scientia Agricola
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 Scientia Agricola
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 71 n. 1 (2014); 38-43
Scientia Agricola; Vol. 71 Núm. 1 (2014); 38-43
Scientia Agricola; Vol. 71 No. 1 (2014); 38-43
1678-992X
0103-9016
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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