Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Ceres |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-737X2020000600474 |
Resumo: | ABSTRACT Multidimensional scaling is a multivariate analysis technique that can be used to exploit genetic diversity, aiming at the selection of Capsicum genotypes with desirable characteristics for in-pot ornamental purposes. This work aimed to select genotypes with ornamental potential within F4 populations of ornamental pepper plants. Three F4 families were used (17.18, 30.16, and 56.8). The genotype distance matrices were estimated based on qualitative and quantitative descriptors, separately, combining the standardized distances of Gower and Mahalanobis, respectively. The relation of the distance between genotypes was graphically studied through non-metric multidimensional scaling. Kruskal' Stress was used as the measured misadjustment of the nMDS solution. There is genetic diversity within the analyzed families, allowing to practice selection. The selection in family 17.18 of genotypes 6 and 32 is recommended, as well as in family 30.16 of genotypes 22 and 4, and family 56.8 of genotypes 15 and 36, since they present important characteristics for ornamental purposes. The selection of genotypes is more efficient when using mixed data since it provides a more complete genetic diversity in an improvement program. |
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Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scalingMultivariate analysisgenetic diversityGowerMahalanobis.ABSTRACT Multidimensional scaling is a multivariate analysis technique that can be used to exploit genetic diversity, aiming at the selection of Capsicum genotypes with desirable characteristics for in-pot ornamental purposes. This work aimed to select genotypes with ornamental potential within F4 populations of ornamental pepper plants. Three F4 families were used (17.18, 30.16, and 56.8). The genotype distance matrices were estimated based on qualitative and quantitative descriptors, separately, combining the standardized distances of Gower and Mahalanobis, respectively. The relation of the distance between genotypes was graphically studied through non-metric multidimensional scaling. Kruskal' Stress was used as the measured misadjustment of the nMDS solution. There is genetic diversity within the analyzed families, allowing to practice selection. The selection in family 17.18 of genotypes 6 and 32 is recommended, as well as in family 30.16 of genotypes 22 and 4, and family 56.8 of genotypes 15 and 36, since they present important characteristics for ornamental purposes. The selection of genotypes is more efficient when using mixed data since it provides a more complete genetic diversity in an improvement program.Universidade Federal de Viçosa2020-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-737X2020000600474Revista Ceres v.67 n.6 2020reponame:Revista Ceresinstname:Universidade Federal de Viçosa (UFV)instacron:UFV10.1590/0034-737x202067060007info:eu-repo/semantics/openAccessCosta,Maria do Perpetuo Socorro DamascenoRêgo,Elizanilda Ramalho doBarroso,Priscila AlvesSilva,Anderson Rodrigo daRêgo,Mailson Monteiro doeng2020-11-05T00:00:00ZRevista |
dc.title.none.fl_str_mv |
Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling |
title |
Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling |
spellingShingle |
Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling Costa,Maria do Perpetuo Socorro Damasceno Multivariate analysis genetic diversity Gower Mahalanobis. |
title_short |
Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling |
title_full |
Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling |
title_fullStr |
Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling |
title_full_unstemmed |
Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling |
title_sort |
Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling |
author |
Costa,Maria do Perpetuo Socorro Damasceno |
author_facet |
Costa,Maria do Perpetuo Socorro Damasceno Rêgo,Elizanilda Ramalho do Barroso,Priscila Alves Silva,Anderson Rodrigo da Rêgo,Mailson Monteiro do |
author_role |
author |
author2 |
Rêgo,Elizanilda Ramalho do Barroso,Priscila Alves Silva,Anderson Rodrigo da Rêgo,Mailson Monteiro do |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Costa,Maria do Perpetuo Socorro Damasceno Rêgo,Elizanilda Ramalho do Barroso,Priscila Alves Silva,Anderson Rodrigo da Rêgo,Mailson Monteiro do |
dc.subject.por.fl_str_mv |
Multivariate analysis genetic diversity Gower Mahalanobis. |
topic |
Multivariate analysis genetic diversity Gower Mahalanobis. |
dc.description.none.fl_txt_mv |
ABSTRACT Multidimensional scaling is a multivariate analysis technique that can be used to exploit genetic diversity, aiming at the selection of Capsicum genotypes with desirable characteristics for in-pot ornamental purposes. This work aimed to select genotypes with ornamental potential within F4 populations of ornamental pepper plants. Three F4 families were used (17.18, 30.16, and 56.8). The genotype distance matrices were estimated based on qualitative and quantitative descriptors, separately, combining the standardized distances of Gower and Mahalanobis, respectively. The relation of the distance between genotypes was graphically studied through non-metric multidimensional scaling. Kruskal' Stress was used as the measured misadjustment of the nMDS solution. There is genetic diversity within the analyzed families, allowing to practice selection. The selection in family 17.18 of genotypes 6 and 32 is recommended, as well as in family 30.16 of genotypes 22 and 4, and family 56.8 of genotypes 15 and 36, since they present important characteristics for ornamental purposes. The selection of genotypes is more efficient when using mixed data since it provides a more complete genetic diversity in an improvement program. |
description |
ABSTRACT Multidimensional scaling is a multivariate analysis technique that can be used to exploit genetic diversity, aiming at the selection of Capsicum genotypes with desirable characteristics for in-pot ornamental purposes. This work aimed to select genotypes with ornamental potential within F4 populations of ornamental pepper plants. Three F4 families were used (17.18, 30.16, and 56.8). The genotype distance matrices were estimated based on qualitative and quantitative descriptors, separately, combining the standardized distances of Gower and Mahalanobis, respectively. The relation of the distance between genotypes was graphically studied through non-metric multidimensional scaling. Kruskal' Stress was used as the measured misadjustment of the nMDS solution. There is genetic diversity within the analyzed families, allowing to practice selection. The selection in family 17.18 of genotypes 6 and 32 is recommended, as well as in family 30.16 of genotypes 22 and 4, and family 56.8 of genotypes 15 and 36, since they present important characteristics for ornamental purposes. The selection of genotypes is more efficient when using mixed data since it provides a more complete genetic diversity in an improvement program. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-737X2020000600474 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-737X2020000600474 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0034-737x202067060007 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Universidade Federal de Viçosa |
publisher.none.fl_str_mv |
Universidade Federal de Viçosa |
dc.source.none.fl_str_mv |
Revista Ceres v.67 n.6 2020 reponame:Revista Ceres instname:Universidade Federal de Viçosa (UFV) instacron:UFV |
instname_str |
Universidade Federal de Viçosa (UFV) |
instacron_str |
UFV |
institution |
UFV |
reponame_str |
Revista Ceres |
collection |
Revista Ceres |
repository.name.fl_str_mv |
|
repository.mail.fl_str_mv |
|
_version_ |
1728006783957467136 |