RANDOM REGRESSION MODELS FOR GROWTH TRAIT IN GUZERA CATTLE

Authors

  • Jorge Luis Ferreira Universidade Federal do Tocantins
  • Tiago Bresolin Faculdade de Ciências Agrárias e Veterinárias -Unesp- Campus de Jaboticabal
  • Fernando Brito Lopes Honorary Associate/Fellow University of Wisconsin - Madison
  • José Américo Soares Garcia Universidade de Brasilia
  • Leandro Lopes Nepomuceno Médico Veterinário Autonomo. Universidade Federal do Tocantins
  • Aline Beatriz Schmidt Universidade Federal do Tocantins - Campus de Araguaína
  • Raysildo Barbosa Lobo Associação Nacional de Criadores e Pesquisadores

DOI:

https://doi.org/10.1590/cab18039566

Keywords:

Animal Breeding

Abstract

The aim of this study was to estimate (co)variance components and genetic parameters from birth to yearling weight (550 days of age) in Guzerá cattle, using random regression models. Data set from animals (male and female) born between 1993 and 2011 belonging to ten farms in seven Brazilian States were used. The best-fit model considering direct and maternal genetic effect and permanent environmental animal effect were adjusted by fourth, third, and second order, respectively, using orthogonal polynomials of Legendre. The higher estimated values of direct heritability were observed in birth (0.88) and yearling weight (0.70). The genetic correlations were moderate to high magnitude, remaining up even with the increase in the ages gap. 
Key words: beef cattle; genetic correlations; heritability; orthogonal polynomials of Legendre.

 

Downloads

Download data is not yet available.

Author Biographies

Jorge Luis Ferreira, Universidade Federal do Tocantins

Professor Adjunto IV Campus de Araguaína Universidade Federal do Tocantins

Tiago Bresolin, Faculdade de Ciências Agrárias e Veterinárias -Unesp- Campus de Jaboticabal

Aluno de doutorado do Programa de Pós-graduação em Genética e Melhoramento Animal - Faculdade de Ciências Agrárias e Veterinárias -Unesp- Campus de Jaboticabal

Fernando Brito Lopes, Honorary Associate/Fellow University of Wisconsin - Madison

Honorary Associate/Fellow, Dr. Fernando Brito Lopes
College of Agricultural & Life Sciences
University of Wisconsin - Madison
Animal Science Building
1675 Observatory Dr
Madison, WI 53706 USA
Phone.: (608) 320-3506CV: http://lattes.cnpq.br/1399785191420919 

José Américo Soares Garcia, Universidade de Brasilia

Professor Associado I Universidade de Brasilia

Leandro Lopes Nepomuceno, Médico Veterinário Autonomo. Universidade Federal do Tocantins

Médico Veterinário Autonomo. Universidade Federal do Tocantins

Aline Beatriz Schmidt, Universidade Federal do Tocantins - Campus de Araguaína

Universidade Federal do Tocantins - Campus de Araguaína

Raysildo Barbosa Lobo, Associação Nacional de Criadores e Pesquisadores

Diretor - Presidentes da Associação Nacional de Criadores e Pesquisadores - ANCP

Downloads

Published

2017-03-31

How to Cite

FERREIRA, J. L.; BRESOLIN, T.; LOPES, F. B.; GARCIA, J. A. S.; NEPOMUCENO, L. L.; SCHMIDT, A. B.; LOBO, R. B. RANDOM REGRESSION MODELS FOR GROWTH TRAIT IN GUZERA CATTLE. Brazilian Animal Science/ Ciência Animal Brasileira, Goiânia, v. 18, 2017. DOI: 10.1590/cab18039566. Disponível em: https://revistas.ufg.br/vet/article/view/e-39566. Acesso em: 30 jun. 2024.

Issue

Vol. 18 (2017): Continuous publication

Section

ZOOTECNIA

License

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g. in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).