Comparison of methods for selection of castor beans lineages
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.14295/cs.v9i4.2970 http://hdl.handle.net/11449/232928 |
Resumo: | The choice of the most appropriate method is determined by the precision desired by the researcher, by the ease of the analysis, as well as by the way of obtaining the data. In order to select lineages of low size and high productivity this study aimed to evaluate different methods of cluster analysis in the representation of genetic divergence, compared to univariate methods. The analyzed variables were grain yield, plant size and oil yield of 24 lineages of castor beans cultivated in the years 2014 and 2015. The Single and Average methods presented similar results in the formation of groups and different from the Complete. Evaluating the purpose of this research the Complete method and principal components analysis, together with the discriminant analysis, were considered the most appropriate methods to evaluate the genetic divergence of the castor bean crop. Lineages 18, 19 and 20 showed average grain yields above 1555 kg.ha-1, high oil content (above 46.9%), and low size plants (below 116 cm). |
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Repositório Institucional da UNESP |
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Comparison of methods for selection of castor beans lineagesGenetic divergenceGenotypesMultivariate statisticsPlant breedingRicinus communis L.The choice of the most appropriate method is determined by the precision desired by the researcher, by the ease of the analysis, as well as by the way of obtaining the data. In order to select lineages of low size and high productivity this study aimed to evaluate different methods of cluster analysis in the representation of genetic divergence, compared to univariate methods. The analyzed variables were grain yield, plant size and oil yield of 24 lineages of castor beans cultivated in the years 2014 and 2015. The Single and Average methods presented similar results in the formation of groups and different from the Complete. Evaluating the purpose of this research the Complete method and principal components analysis, together with the discriminant analysis, were considered the most appropriate methods to evaluate the genetic divergence of the castor bean crop. Lineages 18, 19 and 20 showed average grain yields above 1555 kg.ha-1, high oil content (above 46.9%), and low size plants (below 116 cm).São Paulo State UniversitySão Paulo State UniversityUniversidade Estadual Paulista (UNESP)Sartori, Maria Márcia Pereira [UNESP]Da Silva, Jackson [UNESP]Zanotto, Mauricio Dutra [UNESP]2022-04-30T20:25:12Z2022-04-30T20:25:12Z2018-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article687-694http://dx.doi.org/10.14295/cs.v9i4.2970Comunicata Scientiae, v. 9, n. 4, p. 687-694, 2018.2176-9079http://hdl.handle.net/11449/23292810.14295/cs.v9i4.29702-s2.0-85074173883Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengComunicata Scientiaeinfo:eu-repo/semantics/openAccess2024-04-30T15:56:54Zoai:repositorio.unesp.br:11449/232928Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:44:42.057184Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Comparison of methods for selection of castor beans lineages |
title |
Comparison of methods for selection of castor beans lineages |
spellingShingle |
Comparison of methods for selection of castor beans lineages Sartori, Maria Márcia Pereira [UNESP] Genetic divergence Genotypes Multivariate statistics Plant breeding Ricinus communis L. |
title_short |
Comparison of methods for selection of castor beans lineages |
title_full |
Comparison of methods for selection of castor beans lineages |
title_fullStr |
Comparison of methods for selection of castor beans lineages |
title_full_unstemmed |
Comparison of methods for selection of castor beans lineages |
title_sort |
Comparison of methods for selection of castor beans lineages |
author |
Sartori, Maria Márcia Pereira [UNESP] |
author_facet |
Sartori, Maria Márcia Pereira [UNESP] Da Silva, Jackson [UNESP] Zanotto, Mauricio Dutra [UNESP] |
author_role |
author |
author2 |
Da Silva, Jackson [UNESP] Zanotto, Mauricio Dutra [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Sartori, Maria Márcia Pereira [UNESP] Da Silva, Jackson [UNESP] Zanotto, Mauricio Dutra [UNESP] |
dc.subject.por.fl_str_mv |
Genetic divergence Genotypes Multivariate statistics Plant breeding Ricinus communis L. |
topic |
Genetic divergence Genotypes Multivariate statistics Plant breeding Ricinus communis L. |
description |
The choice of the most appropriate method is determined by the precision desired by the researcher, by the ease of the analysis, as well as by the way of obtaining the data. In order to select lineages of low size and high productivity this study aimed to evaluate different methods of cluster analysis in the representation of genetic divergence, compared to univariate methods. The analyzed variables were grain yield, plant size and oil yield of 24 lineages of castor beans cultivated in the years 2014 and 2015. The Single and Average methods presented similar results in the formation of groups and different from the Complete. Evaluating the purpose of this research the Complete method and principal components analysis, together with the discriminant analysis, were considered the most appropriate methods to evaluate the genetic divergence of the castor bean crop. Lineages 18, 19 and 20 showed average grain yields above 1555 kg.ha-1, high oil content (above 46.9%), and low size plants (below 116 cm). |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-01 2022-04-30T20:25:12Z 2022-04-30T20:25:12Z |
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 |
http://dx.doi.org/10.14295/cs.v9i4.2970 Comunicata Scientiae, v. 9, n. 4, p. 687-694, 2018. 2176-9079 http://hdl.handle.net/11449/232928 10.14295/cs.v9i4.2970 2-s2.0-85074173883 |
url |
http://dx.doi.org/10.14295/cs.v9i4.2970 http://hdl.handle.net/11449/232928 |
identifier_str_mv |
Comunicata Scientiae, v. 9, n. 4, p. 687-694, 2018. 2176-9079 10.14295/cs.v9i4.2970 2-s2.0-85074173883 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Comunicata Scientiae |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
687-694 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128972510199808 |