Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , |
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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Scientia Agrícola (Online) |
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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 |
_version_ |
1800222792024588288 |