Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | http://dx.doi.org/10.1590/S0103-90162014000100005 http://www.locus.ufv.br/handle/123456789/17755 |
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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LOCUS Repositório Institucional da UFV |
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2145 |
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Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scalingAllium sativum L.nMDSUPGMAGenetic divergenceMultivariate 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.Scientia Agricola2018-02-21T13:07:38Z2018-02-21T13:07:38Z2013-07-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlepdfapplication/pdf01039016http://dx.doi.org/10.1590/S0103-90162014000100005http://www.locus.ufv.br/handle/123456789/17755engv. 71, n. 1, p. 38-43, January/February 2014Silva, Anderson Rodrigo daCecon, Paulo RobertoDias, Carlos Tadeu dos SantosPuiatti, MárioFinger, Fernando LuizCarneiro, Antônio Policarpo Souzainfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFV2024-07-12T08:10:56Zoai:locus.ufv.br:123456789/17755Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452024-07-12T08:10:56LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)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 Allium sativum L. nMDS UPGMA Genetic divergence |
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 |
dc.subject.por.fl_str_mv |
Allium sativum L. nMDS UPGMA Genetic divergence |
topic |
Allium sativum L. nMDS UPGMA Genetic divergence |
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 |
2013 |
dc.date.none.fl_str_mv |
2013-07-15 2018-02-21T13:07:38Z 2018-02-21T13:07:38Z |
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 |
01039016 http://dx.doi.org/10.1590/S0103-90162014000100005 http://www.locus.ufv.br/handle/123456789/17755 |
identifier_str_mv |
01039016 |
url |
http://dx.doi.org/10.1590/S0103-90162014000100005 http://www.locus.ufv.br/handle/123456789/17755 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
v. 71, n. 1, p. 38-43, January/February 2014 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
pdf application/pdf |
dc.publisher.none.fl_str_mv |
Scientia Agricola |
publisher.none.fl_str_mv |
Scientia Agricola |
dc.source.none.fl_str_mv |
reponame:LOCUS Repositório Institucional da UFV instname:Universidade Federal de Viçosa (UFV) instacron:UFV |
instname_str |
Universidade Federal de Viçosa (UFV) |
instacron_str |
UFV |
institution |
UFV |
reponame_str |
LOCUS Repositório Institucional da UFV |
collection |
LOCUS Repositório Institucional da UFV |
repository.name.fl_str_mv |
LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV) |
repository.mail.fl_str_mv |
fabiojreis@ufv.br |
_version_ |
1817559993955647488 |