Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population

Detalhes bibliográficos
Autor(a) principal: Bravo,André Padilha
Data de Publicação: 2021
Outros Autores: Prestes,Alan Miranda, Oliveira,Mauricio Morgado de, Roso,Vanerlei Mozaquatro, Mello,Fernanda Cristina Breda, Rorato,Paulo Roberto Nogara
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência Rural
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001000653
Resumo: ABSTRACT: This research identified the animal model that best describes the genetic and residual variations for tick counts in yearlings from a crossbred Angus-Nellore population of 6,951 animals that are progenies of 382 bulls and 6,198 cows. Genetic values were predicted by the Bayesian inference methodology. The models tested were: Traditional Animal, and Crossbred Animal with and without segregation, considering residual homoscedastic and heteroscedastic variances. The criteria of choice were the number of parameters, deviance information, and predictive order, which indicated the best fitfor the Traditional Animal model and Crossbred Animal model (with segregation), both with residual heteroscedastic Gaussian variance. The mean values of fixed genetic effects were positive and similar in the both models, indicating that animals with higher proportion of the Angus breed had greater infestation, and the Nellore breed was an important addition for resistance to ticks. The estimated genetic variation by the heteroscedastic Gaussian Animal model for the Nellore breed was 4.54-fold higher than that estimated for the Angus breed. The estimates of heritability of the different genetic groups ranged from 0.12 to 0.15 and from 0.01 to 0.35, respectively, for the Traditional Animal model and for the heteroscedastic Gaussian crossbred model. The Spearman’s rank-order correlation for the predicted genetic values was 0.94, considering all sires. However, when considering the top 10%, 20%, and 30% sires, differences in ranking were more evident (0.28 to 0.67). The Crossbred Animal model with segregation and heterogeneous residual variances was the most appropriate for genetic evaluation of tick counts on animals from Angus-Nellore crossings.
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spelling Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore populationheteroscedasticity of variancescrossbred animal modelSpearman’s correlationABSTRACT: This research identified the animal model that best describes the genetic and residual variations for tick counts in yearlings from a crossbred Angus-Nellore population of 6,951 animals that are progenies of 382 bulls and 6,198 cows. Genetic values were predicted by the Bayesian inference methodology. The models tested were: Traditional Animal, and Crossbred Animal with and without segregation, considering residual homoscedastic and heteroscedastic variances. The criteria of choice were the number of parameters, deviance information, and predictive order, which indicated the best fitfor the Traditional Animal model and Crossbred Animal model (with segregation), both with residual heteroscedastic Gaussian variance. The mean values of fixed genetic effects were positive and similar in the both models, indicating that animals with higher proportion of the Angus breed had greater infestation, and the Nellore breed was an important addition for resistance to ticks. The estimated genetic variation by the heteroscedastic Gaussian Animal model for the Nellore breed was 4.54-fold higher than that estimated for the Angus breed. The estimates of heritability of the different genetic groups ranged from 0.12 to 0.15 and from 0.01 to 0.35, respectively, for the Traditional Animal model and for the heteroscedastic Gaussian crossbred model. The Spearman’s rank-order correlation for the predicted genetic values was 0.94, considering all sires. However, when considering the top 10%, 20%, and 30% sires, differences in ranking were more evident (0.28 to 0.67). The Crossbred Animal model with segregation and heterogeneous residual variances was the most appropriate for genetic evaluation of tick counts on animals from Angus-Nellore crossings.Universidade Federal de Santa Maria2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001000653Ciência Rural v.51 n.10 2021reponame:Ciência Ruralinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM10.1590/0103-8478cr20200500info:eu-repo/semantics/openAccessBravo,André PadilhaPrestes,Alan MirandaOliveira,Mauricio Morgado deRoso,Vanerlei MozaquatroMello,Fernanda Cristina BredaRorato,Paulo Roberto Nogaraeng2021-07-15T00:00:00ZRevista
dc.title.none.fl_str_mv Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population
title Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population
spellingShingle Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population
Bravo,André Padilha
heteroscedasticity of variances
crossbred animal model
Spearman’s correlation
title_short Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population
title_full Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population
title_fullStr Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population
title_full_unstemmed Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population
title_sort Genetic evaluation models for resistance to ticks in a crossbred Angus-Nellore population
author Bravo,André Padilha
author_facet Bravo,André Padilha
Prestes,Alan Miranda
Oliveira,Mauricio Morgado de
Roso,Vanerlei Mozaquatro
Mello,Fernanda Cristina Breda
Rorato,Paulo Roberto Nogara
author_role author
author2 Prestes,Alan Miranda
Oliveira,Mauricio Morgado de
Roso,Vanerlei Mozaquatro
Mello,Fernanda Cristina Breda
Rorato,Paulo Roberto Nogara
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Bravo,André Padilha
Prestes,Alan Miranda
Oliveira,Mauricio Morgado de
Roso,Vanerlei Mozaquatro
Mello,Fernanda Cristina Breda
Rorato,Paulo Roberto Nogara
dc.subject.por.fl_str_mv heteroscedasticity of variances
crossbred animal model
Spearman’s correlation
topic heteroscedasticity of variances
crossbred animal model
Spearman’s correlation
description ABSTRACT: This research identified the animal model that best describes the genetic and residual variations for tick counts in yearlings from a crossbred Angus-Nellore population of 6,951 animals that are progenies of 382 bulls and 6,198 cows. Genetic values were predicted by the Bayesian inference methodology. The models tested were: Traditional Animal, and Crossbred Animal with and without segregation, considering residual homoscedastic and heteroscedastic variances. The criteria of choice were the number of parameters, deviance information, and predictive order, which indicated the best fitfor the Traditional Animal model and Crossbred Animal model (with segregation), both with residual heteroscedastic Gaussian variance. The mean values of fixed genetic effects were positive and similar in the both models, indicating that animals with higher proportion of the Angus breed had greater infestation, and the Nellore breed was an important addition for resistance to ticks. The estimated genetic variation by the heteroscedastic Gaussian Animal model for the Nellore breed was 4.54-fold higher than that estimated for the Angus breed. The estimates of heritability of the different genetic groups ranged from 0.12 to 0.15 and from 0.01 to 0.35, respectively, for the Traditional Animal model and for the heteroscedastic Gaussian crossbred model. The Spearman’s rank-order correlation for the predicted genetic values was 0.94, considering all sires. However, when considering the top 10%, 20%, and 30% sires, differences in ranking were more evident (0.28 to 0.67). The Crossbred Animal model with segregation and heterogeneous residual variances was the most appropriate for genetic evaluation of tick counts on animals from Angus-Nellore crossings.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
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=S0103-84782021001000653
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021001000653
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-8478cr20200500
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 Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Rural v.51 n.10 2021
reponame:Ciência Rural
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Rural
collection Ciência Rural
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repository.mail.fl_str_mv
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