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Genetic analysis of the temperament of Nellore cattle using linear and threshold models

Published online by Cambridge University Press:  31 October 2014

C. R. S. Lucena ,
H. H. R. Neves ,
R. Carvalheiro ,
J. A. Oliveira  and
S. A. Queiroz
C. R. S. Lucena
Affiliation:
Departamento de Zootecnia, FCAV – Univ Estadual Paulista, Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal, SP 14884-900, Brazil
H. H. R. Neves
Affiliation:
Gensys Consultores Associados S/C Ltda, Rua Juca Quito, 800, Jaboticabal, SP 14870-260, Brazil
R. Carvalheiro
Affiliation:
Departamento de Zootecnia, FCAV – Univ Estadual Paulista, Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal, SP 14884-900, Brazil
J. A. Oliveira
Affiliation:
Departamento de Ciências Exatas, FCAV – Univ Estadual Paulista, Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal, SP 14884-900, Brazil
S. A. Queiroz*
Affiliation:
Departamento de Zootecnia, FCAV – Univ Estadual Paulista, Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal, SP 14884-900, Brazil
*
†E-mail: saquei@fcav.unesp.br
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Abstract

Temperament is an important trait for the management and welfare of animals and for reducing accidents involving people who work with cattle. The present study aimed to estimate the genetic parameters related to the temperament score (T) and weaning weight (WW) of Nellore cattle, reared in a beef cattle breeding program in Brazil. Data were analyzed using two different two-trait statistical models, both considering WW and T: (1) a linear-linear model in which variance components (VCs) were estimated using restricted maximum likelihood; and (2) a linear-threshold model in which VCs were estimated via Bayesian inference. WW was included in the analyses of T to minimize any possible effects of sequential selection and to allow for estimation of the genetic correlation between these two traits. The heritability estimates for T were 0.21±0.003 (model 1) and 0.26 (model 2, with a 95% credibility interval (95% CI) of 0.21 to 0.32). The estimated genetic correlations between WW and T were of a moderate magnitude (−0.33±0.01 (model 1) and −0.34 (95% CI: −0.40, −0.28, model 2). The genetic correlations between the estimated breeding values (EBVs) obtained for the animals based on the two models were high (>0.92). The use of different models had little influence on the classification of animals based on EBVs or the accuracy of the EBVs.

Keywords

beef productioncategorical traitgenetic parameterperformance trait
Type
Research Article
Information
animal , Volume 9 , Issue 3 , March 2015 , pp. 388 - 394
Copyright
© The Animal Consortium 2014 

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References

Adamczyk, K, Pokorska, J, Makulska, J, Earley, B and Mazurek, M 2013. Genetic analysis and evaluation of behavioural traits in cattle. Livestock Science 154, 1–12.CrossRefGoogle Scholar
Barrozo, D, Bukansas, ME, Oliveira, JA, Munari, DP, Neves, HHR and Queiroz, SA 2012. Genetic parameters and environmental effects on temperament score and reproductive traits of Nellore cattle. Animal 6, 36–40.Google Scholar
Burrow, HM 1997. Measurements of temperament and their relationship with performance traits of beef cattle. Animal Breeding Abstracts 65, 477–495.Google Scholar
Burrow, HM 2001. Variance and covariances between productive and adaptative traits and temperament in a composite breed of tropical beef cattle. Livestock Production Science 70, 213 –233.CrossRefGoogle Scholar
CRV Lagoa 2013. Programa de Melhoramento Genético para Bovinos de corte da CRV Lagoa. Retrieved September 10, 2013, from http://www.crvlagoa.com.br/index.asp.Google Scholar
Eler, JP, Van Vleck, LD, Ferraz, JB and Lôbo, RB 1995. Estimation of variances due to direct and maternal effects for growth traits of Nellore cattle. Journal of Animal Science 73, 3253–3258.CrossRefGoogle Scholar
Forkman, B, Boissy, A, Meunier-Salaun, MC, Canali, E and Jones, RB 2007. A critical review of fear tests used on cattle, pigs, sheep, poultry and horses. Physiology & Behavior 92, 340–374.CrossRefGoogle ScholarPubMed
Gauly, M, Mathiak, K, Hoffmann, M, Graus, M and Erhardt, G 2001. Estimating genetic variability in temperamental traits in German Angus and Simmental cattle. Applied Animal Behaviour Science 74, 109–119.Google Scholar
Gelman, A and Rubin, DB 1992. Inference from iterative simulation using multiple sequences. Statistical Science 7, 457–472.CrossRefGoogle Scholar
Gianola, D and Foulley, JL 1983. New techniques of prediction of breeding value for discontinuous traits. Retrieved September 12, 2013, from http://poultryscience.org/docs/pba/1952-2003/1983/1983%20Gianola.pdf.Google Scholar
Gianola, D and Foulley, JL 1990. Variance estimation from integrated likelihood (VEIL). Génetique Sélection Évolution 22, 403–417.Google Scholar
Hoppe, D, Brandt, HR, König, S, Erhardt, G and Gauly, M 2010. Temperament traits of beef calves measured under field conditions and their relationships to performance. Journal of Animal Science 88, 1982–1989.Google Scholar
Kadel, MJ, Johnston, DJ, Burrow, HM, Graser, HU and Ferguson, DM 2006. Genetics of flight time and other measures of temperament and their value as selection criteria for improving meat quality traits in tropically adapted breeds of beef cattle. Australian Journal of Agricultural Research 57, 1029–1035.Google Scholar
Lopes, FB, Magnabosco, CU, Paulini, F, Silva, MC, Miyagi, ES and Lôbo, RB 2013. Genetic analysis of growth traits in polled Nellore cattle raised on pasture in tropical region using Bayesian approaches. PLos One 8, e75423.Google Scholar
Misztal, I 2013. BLUPF90 family of programs. Retrieved October 21, 2013, from http://nce.ads.uga.edu/wiki/doku.php.Google Scholar
Misztal, I and Gianola, D 1989. Computing aspects of a nonlinear method of sire evaluation for categorical data. Retrieved September 12, 2013, from http://dx.doi.org/10.3168/jds.S0022-0302(89)79267-5.CrossRefGoogle Scholar
Muller, R and Von Keyserlingk, MAG 2006. Consistency of flight speed and its correlation to productivity and to personality in Bos taurus beef cattle. Applied Animal Behaviour Science 99, 193–204.Google Scholar
Sant’anna, AC, Paranhos da Costa, MJR, Baldi, F and Albuquerque, LG 2013. Genetic variability for temperament indicators of Nellore cattle. Journal of Animal Science 10, 3427–3432.Google Scholar
Tier, B and Meyer, K 2004. Approximating prediction error covariances among additive genetic effects within animals in multiple-trait and random regression models. Journal of Animal Breeding and Genetics 121, 77–89.Google Scholar
Tulloh, NM 1961. Behaviour of cattle in yards. II. A study of temperament. Animal Behaviour 9, 25–30.Google Scholar
Voisinet, BD, Gradin, T, Tatum, JD, O’Connor, SF and Struthers, JJ 1997. Feedlot cattle with calm temperaments have higher average daily gains than cattle with excitable temperaments. Journal of Animal Science 75, 892–896.Google Scholar