Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Semina. Ciências Agrárias (Online) |
Texto Completo: | https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/19898 |
Resumo: | A multivariate approach was adopted to evaluate the relationship among traits measured in the performance testing of Morada Nova sheep, verify the efficiency of a ranking method used in these tests and identify the most significant traits for use in future analyses. Data from 150 young rams participating in five versions of the performance tests for the Morada Nova breed were used. Twenty traits were measured in each animal: initial weight (IW), final weight (FW), average daily weight gain (ADG), loin eye area (LEA), scrotal circumference (SC), fat thickness (FT), conformation (C), precocity (Pc), muscularity (M), breed features (BF), legs (L), withers height (WH), chest width (CW), rump height (RH), rump width (RW), rump length (RL), body length (BL), body depth (BD), heart girth (HG) and body condition scoring (BCS). The Pearson’s correlation coefficients ranged from –0.10 to 0.93, with the highest correlations were between body weight variables and morphometric measurements. The three first principal components explained 72.28% of the total variability among all traits. The variables related to animal size defined the first principal component, whereas those related to visual appraisal and suitability for meat production defined the second and third principal components, respectively. The combination of traits from the principal component analysis showed that the ranking method currently used in the performance testing of Morada Nova sheep is efficient for selecting larger rams with better breed features and higher degrees of specialization for meat production. |
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Semina. Ciências Agrárias (Online) |
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Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breedAnálise de componentes principais para avaliação de um método de classificação utilizado nos testes de desempenho em ovinos da raça Morada NovaAdaptabilityMeat sheepSelectionMultivariate analysisWeighting.AdaptabilidadeOvinos de corteSeleçãoAnálise multivariadaPonderação.A multivariate approach was adopted to evaluate the relationship among traits measured in the performance testing of Morada Nova sheep, verify the efficiency of a ranking method used in these tests and identify the most significant traits for use in future analyses. Data from 150 young rams participating in five versions of the performance tests for the Morada Nova breed were used. Twenty traits were measured in each animal: initial weight (IW), final weight (FW), average daily weight gain (ADG), loin eye area (LEA), scrotal circumference (SC), fat thickness (FT), conformation (C), precocity (Pc), muscularity (M), breed features (BF), legs (L), withers height (WH), chest width (CW), rump height (RH), rump width (RW), rump length (RL), body length (BL), body depth (BD), heart girth (HG) and body condition scoring (BCS). The Pearson’s correlation coefficients ranged from –0.10 to 0.93, with the highest correlations were between body weight variables and morphometric measurements. The three first principal components explained 72.28% of the total variability among all traits. The variables related to animal size defined the first principal component, whereas those related to visual appraisal and suitability for meat production defined the second and third principal components, respectively. The combination of traits from the principal component analysis showed that the ranking method currently used in the performance testing of Morada Nova sheep is efficient for selecting larger rams with better breed features and higher degrees of specialization for meat production. Objetivou-se neste trabalho adotar uma abordagem multivariada para avaliar a relação entre as características medidas nos testes de desempenho de ovinos Morada Nova para verificar a eficácia do método de classificação utilizado nestes testes, e identificar as características mais importantes para serem usadas em análises futuras. Foram utilizados dados de 150 carneiros jovens participantes de cinco edições do teste de desempenho da raça Morada Nova. Vinte características foram mensuradas em cada animal: peso inicial (PI), peso final (PF), ganho de peso médio diário (GPMD), área de olho de lombo (AOL), perímetro escrotal (PE), espessura de gordura (EG), conformação (C), precocidade (Pc), musculosidade (M), tipo racial (TP), aprumos (A), altura de cernelha (AC), largura de peito (LP), altura da garupa (AG), largura da garupa (LG), comprimento da garupa (CG), comprimento corporal (CC), profundidade (P), perímetro torácico (PT) e escore de condição corporal (ECC). Os Coeficientes de correlação de Pearson variaram de –0,10 a 0,93, sendo que as maiores correlações foram entre as variáveis de peso corporal e medidas morfométricas. Os três primeiros componentes principais explicaram 72,28% da variabilidade total entre todas as variáveis. As variáveis relacionadas ao porte do animal obtiveram maiores ponderadores no primeiro componente principal, enquanto as características relacionadas à avaliação visual e aptidão para a produção de carne foram mais representativas no segundo e terceiro componentes principais, respectivamente. A combinação das variáveis formadas a partir da análise de componentes principais mostrou que, o método de classificação atualmente utilizado nos testes de desempenho de ovinos Morada Nova é eficiente para a seleção de carneiros maiores, com melhor padrão racial e maior grau de especialização para a produção de carne. UEL2015-12-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPesquisa Empírica de Campoapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/1989810.5433/1679-0359.2015v36n6p3909Semina: Ciências Agrárias; Vol. 36 No. 6 (2015); 3909-3922Semina: Ciências Agrárias; v. 36 n. 6 (2015); 3909-39221679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELenghttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/19898/17497http://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessSilva, Michelle Santos daShiotsuki, LucianaLôbo, Raimundo Nonato BragaFacó, Olivardo2022-12-05T11:56:56Zoai:ojs.pkp.sfu.ca:article/19898Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2022-12-05T11:56:56Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false |
dc.title.none.fl_str_mv |
Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed Análise de componentes principais para avaliação de um método de classificação utilizado nos testes de desempenho em ovinos da raça Morada Nova |
title |
Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed |
spellingShingle |
Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed Silva, Michelle Santos da Adaptability Meat sheep Selection Multivariate analysis Weighting. Adaptabilidade Ovinos de corte Seleção Análise multivariada Ponderação. |
title_short |
Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed |
title_full |
Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed |
title_fullStr |
Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed |
title_full_unstemmed |
Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed |
title_sort |
Principal component analysis for evaluating a ranking method used in the performance testing in sheep of Morada Nova breed |
author |
Silva, Michelle Santos da |
author_facet |
Silva, Michelle Santos da Shiotsuki, Luciana Lôbo, Raimundo Nonato Braga Facó, Olivardo |
author_role |
author |
author2 |
Shiotsuki, Luciana Lôbo, Raimundo Nonato Braga Facó, Olivardo |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Silva, Michelle Santos da Shiotsuki, Luciana Lôbo, Raimundo Nonato Braga Facó, Olivardo |
dc.subject.por.fl_str_mv |
Adaptability Meat sheep Selection Multivariate analysis Weighting. Adaptabilidade Ovinos de corte Seleção Análise multivariada Ponderação. |
topic |
Adaptability Meat sheep Selection Multivariate analysis Weighting. Adaptabilidade Ovinos de corte Seleção Análise multivariada Ponderação. |
description |
A multivariate approach was adopted to evaluate the relationship among traits measured in the performance testing of Morada Nova sheep, verify the efficiency of a ranking method used in these tests and identify the most significant traits for use in future analyses. Data from 150 young rams participating in five versions of the performance tests for the Morada Nova breed were used. Twenty traits were measured in each animal: initial weight (IW), final weight (FW), average daily weight gain (ADG), loin eye area (LEA), scrotal circumference (SC), fat thickness (FT), conformation (C), precocity (Pc), muscularity (M), breed features (BF), legs (L), withers height (WH), chest width (CW), rump height (RH), rump width (RW), rump length (RL), body length (BL), body depth (BD), heart girth (HG) and body condition scoring (BCS). The Pearson’s correlation coefficients ranged from –0.10 to 0.93, with the highest correlations were between body weight variables and morphometric measurements. The three first principal components explained 72.28% of the total variability among all traits. The variables related to animal size defined the first principal component, whereas those related to visual appraisal and suitability for meat production defined the second and third principal components, respectively. The combination of traits from the principal component analysis showed that the ranking method currently used in the performance testing of Morada Nova sheep is efficient for selecting larger rams with better breed features and higher degrees of specialization for meat production. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-12-09 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Pesquisa Empírica de Campo |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/19898 10.5433/1679-0359.2015v36n6p3909 |
url |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/19898 |
identifier_str_mv |
10.5433/1679-0359.2015v36n6p3909 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/19898/17497 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
UEL |
publisher.none.fl_str_mv |
UEL |
dc.source.none.fl_str_mv |
Semina: Ciências Agrárias; Vol. 36 No. 6 (2015); 3909-3922 Semina: Ciências Agrárias; v. 36 n. 6 (2015); 3909-3922 1679-0359 1676-546X reponame:Semina. Ciências Agrárias (Online) instname:Universidade Estadual de Londrina (UEL) instacron:UEL |
instname_str |
Universidade Estadual de Londrina (UEL) |
instacron_str |
UEL |
institution |
UEL |
reponame_str |
Semina. Ciências Agrárias (Online) |
collection |
Semina. Ciências Agrárias (Online) |
repository.name.fl_str_mv |
Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL) |
repository.mail.fl_str_mv |
semina.agrarias@uel.br |
_version_ |
1799306072840732672 |