Discrimination of forage pea seed lots by means of multivariate techniques

Multivariate techniques allow to understand the structural dependence contained in the variables, as well as to characterize groups of seed lots according to specific standards. Thus, this study analyzes the efficiency of multi-variate exploratory techniques in discriminating forage pea seed lots as...

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Detalhes bibliográficos
Autores: Machado, Carla Gomes, Martins, Cibele Chalita [UNESP], Da Silva, Givanildo Zildo, Cruz, Simério Carlos Silva, Gama, Gabriela Fernandes, Coelho, Mirelle Vaz
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:Brasil
Recursos:Universidade Estadual Paulista (UNESP)
Repositorio:Repositório Institucional da UNESP
Idioma:inglés
OAI Identifier:oai:repositorio.unesp.br:11449/201450
Acesso em linha:http://dx.doi.org/10.15361/1984-5529.2019v47n3p321-326
http://hdl.handle.net/11449/201450
Access Level:acceso abierto
Palavra-chave:Arvense
Cluster analysis
Germination
Pisum sativum subsp
Principal component analysis
Vigor
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spelling Discrimination of forage pea seed lots by means of multivariate techniquesArvenseCluster analysisGerminationPisum sativum subspPrincipal component analysisVigorMultivariate techniques allow to understand the structural dependence contained in the variables, as well as to characterize groups of seed lots according to specific standards. Thus, this study analyzes the efficiency of multi-variate exploratory techniques in discriminating forage pea seed lots as a function of the physiological potential of seeds. We evaluated ten seed lots of forage pea in a completely randomized design, considering the following variables: thousand seed weight, germination, first germination count, electrical conductivity, and accelerated aging. Moreover, seedling emergence, first count of seedlings in the field, and seedling emergence speed index in the field were added to randomized blocks with four replications per lot. Initially, the data obtained in each test were analyzed separately by means of analysis of variance, and the means of the treatments were compared by the Scott Knott test at 5% probability. Exploratory multivariate statistical techniques were applied by means of Cluster Analysis and Principal Components Analysis to discriminate seed lots with better physiological quality and to characterize the variables responsible for the differentiation between them. Multivariate analysis of principal components is efficient in discriminating vigor and seed germination tests in Pisum sativum subsp. Arvense, which help in identifying lots of superior performance in the field.Universidade Federal de Goiás - UFG Campus JatobáEngenheira Agronoma Prof-Essora Livre-Docente Faculdade de Ciěncias Agrárias e Veterinárias - UNESPEngenheira Agronoma Prof-Essora Livre-Docente Faculdade de Ciěncias Agrárias e Veterinárias - UNESPUniversidade Federal de Goiás (UFG)Universidade Estadual Paulista (Unesp)2020-12-12T02:32:50Z2020-12-12T02:32:50Z2019-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article321-326http://dx.doi.org/10.15361/1984-5529.2019v47n3p321-326Cientifica, v. 47, n. 3, p. 321-326, 2019.1984-5529http://hdl.handle.net/11449/20145010.15361/1984-5529.2019v47n3p321-3262-s2.0-8507752683596698336633254450000-0002-1720-9252Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCientificainfo:eu-repo/semantics/openAccessMachado, Carla GomesMartins, Cibele Chalita [UNESP]Da Silva, Givanildo ZildoCruz, Simério Carlos SilvaGama, Gabriela FernandesCoelho, Mirelle Vaz2024-06-07T13:57:21Zoai:repositorio.unesp.br:11449/201450Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462024-06-07T13:57:21Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Discrimination of forage pea seed lots by means of multivariate techniques
title Discrimination of forage pea seed lots by means of multivariate techniques
spellingShingle Discrimination of forage pea seed lots by means of multivariate techniques
Machado, Carla Gomes
Arvense
Cluster analysis
Germination
Pisum sativum subsp
Principal component analysis
Vigor
title_short Discrimination of forage pea seed lots by means of multivariate techniques
title_full Discrimination of forage pea seed lots by means of multivariate techniques
title_fullStr Discrimination of forage pea seed lots by means of multivariate techniques
title_full_unstemmed Discrimination of forage pea seed lots by means of multivariate techniques
title_sort Discrimination of forage pea seed lots by means of multivariate techniques
dc.creator.none.fl_str_mv Machado, Carla Gomes
Martins, Cibele Chalita [UNESP]
Da Silva, Givanildo Zildo
Cruz, Simério Carlos Silva
Gama, Gabriela Fernandes
Coelho, Mirelle Vaz
author Machado, Carla Gomes
author_facet Machado, Carla Gomes
Martins, Cibele Chalita [UNESP]
Da Silva, Givanildo Zildo
Cruz, Simério Carlos Silva
Gama, Gabriela Fernandes
Coelho, Mirelle Vaz
author_role author
author2 Martins, Cibele Chalita [UNESP]
Da Silva, Givanildo Zildo
Cruz, Simério Carlos Silva
Gama, Gabriela Fernandes
Coelho, Mirelle Vaz
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Federal de Goiás (UFG)
Universidade Estadual Paulista (Unesp)
dc.subject.por.fl_str_mv Arvense
Cluster analysis
Germination
Pisum sativum subsp
Principal component analysis
Vigor
topic Arvense
Cluster analysis
Germination
Pisum sativum subsp
Principal component analysis
Vigor
description Multivariate techniques allow to understand the structural dependence contained in the variables, as well as to characterize groups of seed lots according to specific standards. Thus, this study analyzes the efficiency of multi-variate exploratory techniques in discriminating forage pea seed lots as a function of the physiological potential of seeds. We evaluated ten seed lots of forage pea in a completely randomized design, considering the following variables: thousand seed weight, germination, first germination count, electrical conductivity, and accelerated aging. Moreover, seedling emergence, first count of seedlings in the field, and seedling emergence speed index in the field were added to randomized blocks with four replications per lot. Initially, the data obtained in each test were analyzed separately by means of analysis of variance, and the means of the treatments were compared by the Scott Knott test at 5% probability. Exploratory multivariate statistical techniques were applied by means of Cluster Analysis and Principal Components Analysis to discriminate seed lots with better physiological quality and to characterize the variables responsible for the differentiation between them. Multivariate analysis of principal components is efficient in discriminating vigor and seed germination tests in Pisum sativum subsp. Arvense, which help in identifying lots of superior performance in the field.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
2020-12-12T02:32:50Z
2020-12-12T02:32:50Z
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/10.15361/1984-5529.2019v47n3p321-326
Cientifica, v. 47, n. 3, p. 321-326, 2019.
1984-5529
http://hdl.handle.net/11449/201450
10.15361/1984-5529.2019v47n3p321-326
2-s2.0-85077526835
9669833663325445
0000-0002-1720-9252
url http://dx.doi.org/10.15361/1984-5529.2019v47n3p321-326
http://hdl.handle.net/11449/201450
identifier_str_mv Cientifica, v. 47, n. 3, p. 321-326, 2019.
1984-5529
10.15361/1984-5529.2019v47n3p321-326
2-s2.0-85077526835
9669833663325445
0000-0002-1720-9252
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Cientifica
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 321-326
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 repositoriounesp@unesp.br
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score 15.301603

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