Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFRRJ |
Texto Completo: | https://tede.ufrrj.br/jspui/handle/jspui/3240 |
Resumo: | The aim of this study was the morphological characterization of the Labrador Retriever in Brazil by morphometry, and the accreditation of different multivariate techniques in the study of sexual dimorphism of these dogs. Were measured 74 animals, 47 females and 27 males. The dogs met the following requirements: be adult animals, aged two years or more; being breeder or array; being registered at AKC or CBKC; and no noticeable signs of pregnancy or lactation. Were measured 30 quantitative biometric characteristics related to the morphology of the head, trunk and front and hind limbs. The sexual dimorphism was analyzed using multivariate statistical techniques, were they the principal component analysis and discriminant analysis. Both the descriptive data and multivariate analyzes were analyzed using the software Statistica 6.0. The principal component analysis was processed in two ways, using all variables and performing a pre-selection of more correlated variables based on graphic dispersion of the correlation of the 30 original variables with the first three principal components, which together explained 50% of total variation. A discriminant analysis was performed with 30 variables and also with the five variables most correlated with the first component (PC1), in order to classify new individuals. The average height at withers for both sexes were lower than the minimum values of the tracks described as ideal by the AKC, while for CBKC only females were lower than the ideal minimum value according to Student's t-test (p <0 , 05). The principal component analysis with 30 variables was able to identify the sexual dimorphism existent in animals and reduce the 30 original variables to three principal components. When processed with the pre-selected variables, the analysis continued efficient in to demonstrate the sexual dimorphism and was able to improve the reduction to two components. The CP1 was the most representative of the analysis (30 variables and pre-selection), and this component is highly correlated with variables related to the size of the animal. The discriminant analysis of Anderson was able to discriminate the two populations (males and females), both for 30 variables as for the five variables most correlated with the CP1. However, the larger number of variables reduces the misclassification probability. The functions with five variables can be used to classify other dogs of the breed by sex, with an error of about 6.75%. |
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Jangarelli, Marcelo079.758.687-36Jangarelli, MarceloAra?jo, Alexandre Herculano Borges deSilva, Marcos Xavier111.210.997-85http://lattes.cnpq.br/2644806749062673Thuller, Murilo Antonio Oliveira2020-01-16T14:31:07Z2013-07-19THULLER, Murilo Antonio Oliveira. Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada. 2013. 51 f. Disserta??o (Mestrado em Zootecnia, Produ??o e Nutri??o de Monog?stricos) - Instituto de Zootecnia, Universidade Federal Rural do Rio de Janeiro, Serop?dica, 2013.https://tede.ufrrj.br/jspui/handle/jspui/3240The aim of this study was the morphological characterization of the Labrador Retriever in Brazil by morphometry, and the accreditation of different multivariate techniques in the study of sexual dimorphism of these dogs. Were measured 74 animals, 47 females and 27 males. The dogs met the following requirements: be adult animals, aged two years or more; being breeder or array; being registered at AKC or CBKC; and no noticeable signs of pregnancy or lactation. Were measured 30 quantitative biometric characteristics related to the morphology of the head, trunk and front and hind limbs. The sexual dimorphism was analyzed using multivariate statistical techniques, were they the principal component analysis and discriminant analysis. Both the descriptive data and multivariate analyzes were analyzed using the software Statistica 6.0. The principal component analysis was processed in two ways, using all variables and performing a pre-selection of more correlated variables based on graphic dispersion of the correlation of the 30 original variables with the first three principal components, which together explained 50% of total variation. A discriminant analysis was performed with 30 variables and also with the five variables most correlated with the first component (PC1), in order to classify new individuals. The average height at withers for both sexes were lower than the minimum values of the tracks described as ideal by the AKC, while for CBKC only females were lower than the ideal minimum value according to Student's t-test (p <0 , 05). The principal component analysis with 30 variables was able to identify the sexual dimorphism existent in animals and reduce the 30 original variables to three principal components. When processed with the pre-selected variables, the analysis continued efficient in to demonstrate the sexual dimorphism and was able to improve the reduction to two components. The CP1 was the most representative of the analysis (30 variables and pre-selection), and this component is highly correlated with variables related to the size of the animal. The discriminant analysis of Anderson was able to discriminate the two populations (males and females), both for 30 variables as for the five variables most correlated with the CP1. However, the larger number of variables reduces the misclassification probability. The functions with five variables can be used to classify other dogs of the breed by sex, with an error of about 6.75%.Objetivou-se com este trabalho a caracteriza??o morfol?gica da ra?a Labrador Retriever no Brasil por meio da morfometria, al?m do credenciamento de diferentes t?cnicas estat?sticas multivariadas no estudo do dimorfismo sexual desses c?es. Foram mensurados 74 animais, sendo 47 f?meas e 27 machos. Os c?es atendiam os seguintes requisitos: ser animal adulto, com idade m?nima de dois anos; ser reprodutor ou matriz; possuir registro no CBKC ou AKC; e n?o apresentar sinais evidentes de prenhez ou aleitamento. Foram mensuradas 30 caracter?sticas biom?tricas quantitativas, de varia??o cont?nua, relativas ? morfologia da cabe?a, tronco e membros anteriores e posteriores. O dimorfismo sexual foi analisado utilizando t?cnicas de estat?stica multivariada compreendendo a an?lise de componentes principais e a an?lise discriminante. Tanto os dados descritivos quanto as an?lises multivariadas foram analisados utilizando o software Statistica 6.0. A an?lise de componentes principais foi processada de duas formas, utilizando todas as vari?veis e realizando a pr?-sele??o das vari?veis mais correlacionadas, com base na dispers?o gr?fica da correla??o das 30 vari?veis originais com os tr?s primeiros componentes principais que juntos explicaram 50% da varia??o total. A an?lise discriminante foi realizada para as 30 vari?veis e tamb?m para as cinco vari?veis mais correlacionadas com o primeiro componente (CP1), com intuito de classificar novos indiv?duos. As m?dias de altura ? cernelha, para ambos os sexos, foram inferiores aos valores m?nimos das faixas descritas como ideais pela AKC, enquanto que para a CBKC apenas as f?meas foram inferiores ao valor m?nimo ideal segundo o teste de t de student (p<0,05). A an?lise de componentes principais com 30 vari?veis foi capaz de identificar o dimorfismo sexual de tamanho existente nos animais, al?m de reduzir as 30 vari?veis originais a tr?s componentes principais. Quando processada com as vari?veis pr?-selecionadas a an?lise continuou eficaz em demonstrar o dimorfismo e otimizou a redu??o para dois componentes principais. O CP1 foi o mais representativo das an?lises (30 vari?veis e pr?-sele??o), e este componente ? altamente correlacionado as vari?veis relacionadas ao tamanho do animal. A an?lise discriminante de Anderson foi capaz de discriminar as duas popula??es (machos e f?meas), tanto para 30 vari?veis quanto para as cinco vari?veis mais correlacionadas com o CP1. Entretanto, o maior n?mero de vari?veis reduziu a probabilidade de m? classifica??o. As fun??es com cinco vari?veis podem ser utilizadas para classificar outros c?es da ra?a quanto ao sexo, com um erro de aproximadamente 6,75%.Submitted by Jorge Silva (jorgelmsilva@ufrrj.br) on 2020-01-16T14:31:07Z No. of bitstreams: 1 2013 - Murilo Antonio Oliveira Thuller.pdf: 2711364 bytes, checksum: 2a3429ef2dcba6dc1287543d98e8e775 (MD5)Made available in DSpace on 2020-01-16T14:31:07Z (GMT). No. of bitstreams: 1 2013 - Murilo Antonio Oliveira Thuller.pdf: 2711364 bytes, checksum: 2a3429ef2dcba6dc1287543d98e8e775 (MD5) Previous issue date: 2013-07-19CAPESapplication/pdfhttps://tede.ufrrj.br/retrieve/12279/2013%20-%20Murilo%20Antonio%20Oliveira%20Thuller.pdf.jpghttps://tede.ufrrj.br/retrieve/17240/2013%20-%20Murilo%20Antonio%20Oliveira%20Thuller.pdf.jpghttps://tede.ufrrj.br/retrieve/23552/2013%20-%20Murilo%20Antonio%20Oliveira%20Thuller.pdf.jpghttps://tede.ufrrj.br/retrieve/29930/2013%20-%20Murilo%20Antonio%20Oliveira%20Thuller.pdf.jpghttps://tede.ufrrj.br/retrieve/36304/2013%20-%20Murilo%20Antonio%20Oliveira%20Thuller.pdf.jpghttps://tede.ufrrj.br/retrieve/42698/2013%20-%20Murilo%20Antonio%20Oliveira%20Thuller.pdf.jpghttps://tede.ufrrj.br/retrieve/49078/2013%20-%20Murilo%20Antonio%20Oliveira%20Thuller.pdf.jpghttps://tede.ufrrj.br/retrieve/55524/2013%20-%20Murilo%20Antonio%20Oliveira%20Thuller.pdf.jpgporUniversidade Federal Rural do Rio de JaneiroPrograma de P?s-Gradua??o em ZootecniaUFRRJBrasilInstituto de ZootecniaAn?lise de componentes principaisAn?lise discriminanteMorfometriaPrincipal component analysisDiscriminant analysisMorphometryZootecniaDimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariadaSexual dimorphism of Labrador Retriever breed dogs in Brazil using multivariate statisticsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFRRJinstname:Universidade Federal Rural do Rio de Janeiro (UFRRJ)instacron:UFRRJTHUMBNAIL2013 - Murilo Antonio Oliveira Thuller.pdf.jpg2013 - Murilo Antonio Oliveira Thuller.pdf.jpgimage/jpeg1943http://localhost:8080/tede/bitstream/jspui/3240/18/2013+-+Murilo+Antonio+Oliveira+Thuller.pdf.jpgcc73c4c239a4c332d642ba1e7c7a9fb2MD518TEXT2013 - Murilo Antonio Oliveira Thuller.pdf.txt2013 - Murilo Antonio Oliveira Thuller.pdf.txttext/plain104753http://localhost:8080/tede/bitstream/jspui/3240/17/2013+-+Murilo+Antonio+Oliveira+Thuller.pdf.txt3b090cb13b37c2adb656c8510bb21181MD517ORIGINAL2013 - Murilo Antonio Oliveira Thuller.pdf2013 - Murilo Antonio Oliveira Thuller.pdfapplication/pdf2711364http://localhost:8080/tede/bitstream/jspui/3240/2/2013+-+Murilo+Antonio+Oliveira+Thuller.pdf2a3429ef2dcba6dc1287543d98e8e775MD52LICENSElicense.txtlicense.txttext/plain; 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dc.title.por.fl_str_mv |
Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada |
dc.title.alternative.eng.fl_str_mv |
Sexual dimorphism of Labrador Retriever breed dogs in Brazil using multivariate statistics |
title |
Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada |
spellingShingle |
Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada Thuller, Murilo Antonio Oliveira An?lise de componentes principais An?lise discriminante Morfometria Principal component analysis Discriminant analysis Morphometry Zootecnia |
title_short |
Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada |
title_full |
Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada |
title_fullStr |
Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada |
title_full_unstemmed |
Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada |
title_sort |
Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada |
author |
Thuller, Murilo Antonio Oliveira |
author_facet |
Thuller, Murilo Antonio Oliveira |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Jangarelli, Marcelo |
dc.contributor.advisor1ID.fl_str_mv |
079.758.687-36 |
dc.contributor.referee1.fl_str_mv |
Jangarelli, Marcelo |
dc.contributor.referee2.fl_str_mv |
Ara?jo, Alexandre Herculano Borges de |
dc.contributor.referee3.fl_str_mv |
Silva, Marcos Xavier |
dc.contributor.authorID.fl_str_mv |
111.210.997-85 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/2644806749062673 |
dc.contributor.author.fl_str_mv |
Thuller, Murilo Antonio Oliveira |
contributor_str_mv |
Jangarelli, Marcelo Jangarelli, Marcelo Ara?jo, Alexandre Herculano Borges de Silva, Marcos Xavier |
dc.subject.por.fl_str_mv |
An?lise de componentes principais An?lise discriminante Morfometria |
topic |
An?lise de componentes principais An?lise discriminante Morfometria Principal component analysis Discriminant analysis Morphometry Zootecnia |
dc.subject.eng.fl_str_mv |
Principal component analysis Discriminant analysis Morphometry |
dc.subject.cnpq.fl_str_mv |
Zootecnia |
description |
The aim of this study was the morphological characterization of the Labrador Retriever in Brazil by morphometry, and the accreditation of different multivariate techniques in the study of sexual dimorphism of these dogs. Were measured 74 animals, 47 females and 27 males. The dogs met the following requirements: be adult animals, aged two years or more; being breeder or array; being registered at AKC or CBKC; and no noticeable signs of pregnancy or lactation. Were measured 30 quantitative biometric characteristics related to the morphology of the head, trunk and front and hind limbs. The sexual dimorphism was analyzed using multivariate statistical techniques, were they the principal component analysis and discriminant analysis. Both the descriptive data and multivariate analyzes were analyzed using the software Statistica 6.0. The principal component analysis was processed in two ways, using all variables and performing a pre-selection of more correlated variables based on graphic dispersion of the correlation of the 30 original variables with the first three principal components, which together explained 50% of total variation. A discriminant analysis was performed with 30 variables and also with the five variables most correlated with the first component (PC1), in order to classify new individuals. The average height at withers for both sexes were lower than the minimum values of the tracks described as ideal by the AKC, while for CBKC only females were lower than the ideal minimum value according to Student's t-test (p <0 , 05). The principal component analysis with 30 variables was able to identify the sexual dimorphism existent in animals and reduce the 30 original variables to three principal components. When processed with the pre-selected variables, the analysis continued efficient in to demonstrate the sexual dimorphism and was able to improve the reduction to two components. The CP1 was the most representative of the analysis (30 variables and pre-selection), and this component is highly correlated with variables related to the size of the animal. The discriminant analysis of Anderson was able to discriminate the two populations (males and females), both for 30 variables as for the five variables most correlated with the CP1. However, the larger number of variables reduces the misclassification probability. The functions with five variables can be used to classify other dogs of the breed by sex, with an error of about 6.75%. |
publishDate |
2013 |
dc.date.issued.fl_str_mv |
2013-07-19 |
dc.date.accessioned.fl_str_mv |
2020-01-16T14:31:07Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
THULLER, Murilo Antonio Oliveira. Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada. 2013. 51 f. Disserta??o (Mestrado em Zootecnia, Produ??o e Nutri??o de Monog?stricos) - Instituto de Zootecnia, Universidade Federal Rural do Rio de Janeiro, Serop?dica, 2013. |
dc.identifier.uri.fl_str_mv |
https://tede.ufrrj.br/jspui/handle/jspui/3240 |
identifier_str_mv |
THULLER, Murilo Antonio Oliveira. Dimorfismo sexual de c?es da ra?a Labrador Retriever no Brasil utilizando estat?stica multivariada. 2013. 51 f. Disserta??o (Mestrado em Zootecnia, Produ??o e Nutri??o de Monog?stricos) - Instituto de Zootecnia, Universidade Federal Rural do Rio de Janeiro, Serop?dica, 2013. |
url |
https://tede.ufrrj.br/jspui/handle/jspui/3240 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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dc.publisher.none.fl_str_mv |
Universidade Federal Rural do Rio de Janeiro |
dc.publisher.program.fl_str_mv |
Programa de P?s-Gradua??o em Zootecnia |
dc.publisher.initials.fl_str_mv |
UFRRJ |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Instituto de Zootecnia |
publisher.none.fl_str_mv |
Universidade Federal Rural do Rio de Janeiro |
dc.source.none.fl_str_mv |
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UFRRJ |
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