Biometric variability of goat populations revealed by means of principal component analysis
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Genetics and Molecular Biology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572012000500011 |
Resumo: | The aim was to analyze variation in 12 Brazilian and Moroccan goat populations, and, through principal component analysis (PCA), check the importance of body measures and their indices as a means of distinguishing among individuals and populations. The biometric measurements were wither height (WH), brisket height (BH) and ear length (EL). Thorax depth (WH-BH) and the three indices, TD/WH, EL/TD and EL/WH, were also calculated. Of the seven components extracted, the first three principal components were sufficient to explain 99.5% of the total variance of the data. Graphical dispersion by genetic groups revealed that European dairy breeds clustered together. The Moroccan breeds were separated into two groups, one comprising the Drâa and the other the Zagora and Rhâali breeds. Whereas, on the one side, the Anglo-Nubian and undefined breeds were the closest to one another the goats of the Azul were observed to have the highest variation of all the breeds. The Anglo-Nubian and Boer breeds were similar to each other. The Nambi-type goats remained distinct from all the other populations. In general, the use of graphical representation of PCA values allowed to distinguish genetic groups. |
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Genetics and Molecular Biology |
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Biometric variability of goat populations revealed by means of principal component analysisbiometricsgenetic resourcesgoat breedsmorphometricspopulation characterizationThe aim was to analyze variation in 12 Brazilian and Moroccan goat populations, and, through principal component analysis (PCA), check the importance of body measures and their indices as a means of distinguishing among individuals and populations. The biometric measurements were wither height (WH), brisket height (BH) and ear length (EL). Thorax depth (WH-BH) and the three indices, TD/WH, EL/TD and EL/WH, were also calculated. Of the seven components extracted, the first three principal components were sufficient to explain 99.5% of the total variance of the data. Graphical dispersion by genetic groups revealed that European dairy breeds clustered together. The Moroccan breeds were separated into two groups, one comprising the Drâa and the other the Zagora and Rhâali breeds. Whereas, on the one side, the Anglo-Nubian and undefined breeds were the closest to one another the goats of the Azul were observed to have the highest variation of all the breeds. The Anglo-Nubian and Boer breeds were similar to each other. The Nambi-type goats remained distinct from all the other populations. In general, the use of graphical representation of PCA values allowed to distinguish genetic groups.Sociedade Brasileira de Genética2012-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572012000500011Genetics and Molecular Biology v.35 n.4 2012reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/S1415-47572012005000072info:eu-repo/semantics/openAccessPires,Luanna ChácaraMachado,Théa M. MedeirosAraújo,Adriana MelloOlson,Timothy A.Silva,João Batista Lopes daTorres,Robledo AlmeidaCosta,Márcio da Silvaeng2012-12-10T00:00:00Zoai:scielo:S1415-47572012000500011Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2012-12-10T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false |
dc.title.none.fl_str_mv |
Biometric variability of goat populations revealed by means of principal component analysis |
title |
Biometric variability of goat populations revealed by means of principal component analysis |
spellingShingle |
Biometric variability of goat populations revealed by means of principal component analysis Pires,Luanna Chácara biometrics genetic resources goat breeds morphometrics population characterization |
title_short |
Biometric variability of goat populations revealed by means of principal component analysis |
title_full |
Biometric variability of goat populations revealed by means of principal component analysis |
title_fullStr |
Biometric variability of goat populations revealed by means of principal component analysis |
title_full_unstemmed |
Biometric variability of goat populations revealed by means of principal component analysis |
title_sort |
Biometric variability of goat populations revealed by means of principal component analysis |
author |
Pires,Luanna Chácara |
author_facet |
Pires,Luanna Chácara Machado,Théa M. Medeiros Araújo,Adriana Mello Olson,Timothy A. Silva,João Batista Lopes da Torres,Robledo Almeida Costa,Márcio da Silva |
author_role |
author |
author2 |
Machado,Théa M. Medeiros Araújo,Adriana Mello Olson,Timothy A. Silva,João Batista Lopes da Torres,Robledo Almeida Costa,Márcio da Silva |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Pires,Luanna Chácara Machado,Théa M. Medeiros Araújo,Adriana Mello Olson,Timothy A. Silva,João Batista Lopes da Torres,Robledo Almeida Costa,Márcio da Silva |
dc.subject.por.fl_str_mv |
biometrics genetic resources goat breeds morphometrics population characterization |
topic |
biometrics genetic resources goat breeds morphometrics population characterization |
description |
The aim was to analyze variation in 12 Brazilian and Moroccan goat populations, and, through principal component analysis (PCA), check the importance of body measures and their indices as a means of distinguishing among individuals and populations. The biometric measurements were wither height (WH), brisket height (BH) and ear length (EL). Thorax depth (WH-BH) and the three indices, TD/WH, EL/TD and EL/WH, were also calculated. Of the seven components extracted, the first three principal components were sufficient to explain 99.5% of the total variance of the data. Graphical dispersion by genetic groups revealed that European dairy breeds clustered together. The Moroccan breeds were separated into two groups, one comprising the Drâa and the other the Zagora and Rhâali breeds. Whereas, on the one side, the Anglo-Nubian and undefined breeds were the closest to one another the goats of the Azul were observed to have the highest variation of all the breeds. The Anglo-Nubian and Boer breeds were similar to each other. The Nambi-type goats remained distinct from all the other populations. In general, the use of graphical representation of PCA values allowed to distinguish genetic groups. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-01-01 |
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=S1415-47572012000500011 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572012000500011 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1415-47572012005000072 |
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 |
Sociedade Brasileira de Genética |
publisher.none.fl_str_mv |
Sociedade Brasileira de Genética |
dc.source.none.fl_str_mv |
Genetics and Molecular Biology v.35 n.4 2012 reponame:Genetics and Molecular Biology instname:Sociedade Brasileira de Genética (SBG) instacron:SBG |
instname_str |
Sociedade Brasileira de Genética (SBG) |
instacron_str |
SBG |
institution |
SBG |
reponame_str |
Genetics and Molecular Biology |
collection |
Genetics and Molecular Biology |
repository.name.fl_str_mv |
Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG) |
repository.mail.fl_str_mv |
||editor@gmb.org.br |
_version_ |
1752122385347117056 |