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Estimation of genetic parameters for BW and body measurements in Brahman cattle

Published online by Cambridge University Press:  07 January 2019

N. Kamprasert ,
N. Duijvesteijn Open the ORCID record for N. Duijvesteijn [Opens in a new window]  and
J. H. J. Van der Werf Open the ORCID record for J. H. J. Van der Werf [Opens in a new window]
N. Kamprasert*
Affiliation:
Bureau of Animal Husbandry and Genetic Improvement, Department of Livestock Development, Bangkok10400, Thailand School of Environmental and Rural Science, University of New England, 2351, Armidale, NSW, Australia
N. Duijvesteijn
Affiliation:
School of Environmental and Rural Science, University of New England, 2351, Armidale, NSW, Australia
J. H. J. Van der Werf
Affiliation:
School of Environmental and Rural Science, University of New England, 2351, Armidale, NSW, Australia
*
†E-mail: [email protected]
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Abstract

Body weight and body measurements are commonly used to represent growth and measured at several growth stages in beef cattle. Those economically important traits should be genetically improved. To achieve breeding programs, genetic parameters are prerequisite, as they are needed for designing and predicting outcomes of breeding programs, as well as estimating of breeding values. (Co)variance components were estimated for BW and body measurements on Brahman cattle born between 1990 and 2016 from 17 research herds across Thailand. The traits measured were BW, heart girth (GR), hip height (HH) and body length (BL) and were measured at birth, 200 days, 400 days and 600 days of age. The number of records varied between traits from 18 890 for birth BW to 876 for GR at 600 days. Estimation of variance components was performed using restricted maximum likelihood using univariate and multivariate animal models. Pre-weaning traits were influenced by genetic and/or permanent environmental effects of the dam, except for BL. Heritability estimates from birth to 600 days of age ranged from 0.28±0.01 to 0.50±0.06 for BW, 0.27±0.01 to 0.43±0.09 for GR, 0.28±0.01 to 0.58±0.08 for HH and 0.34±0.01 to 0.51±0.08 for BL using univariate analysis. Heritability estimates for the traits studied increased with age. A similar trend was observed for the phenotypic and genetic correlations between subsequent BW and body measurements. A positive correlation was observed between different traits measured at a similar age, ranging from 0.22±0.01 to 0.72±0.01 for the phenotypic correlation and 0.25±0.04 to 0.97±0.11 for the genetic correlation. Also, a positive correlation was observed for similar traits across different age classes ranging from 0.07±0.03 to 0.76±0.02 for the phenotypic correlation and 0.24±0.11 to 0.92±0.05 for the genetic correlation. Therefore, all correlations between body measurements at the same age and across age classes were positive. The results show the potential improvement of growth traits in Brahman cattle, and those traits can be improved simultaneously under the same breeding program.

Keywords

beef cattlegrowth traitsvariance componentsheritabilitycorrelation
Type
Research Article
Information
animal , Volume 13 , Issue 8 , August 2019 , pp. 1576 - 1582
Copyright
© The Animal Consortium 2019 

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References

Afolayan, R, Pitchford, W, Deland, M and McKiernan, W 2007. Breed variation and genetic parameters for growth and body development in diverse beef cattle genotypes. Animal 1, 13–20.Google Scholar
Bertipaglia, TS, Carreño, LOD, Aspilcueta-Borquis, RR, Boligon, AA, Farah, MM, Gomes, FJ, Machado, CHC, Rey, FSB and da Fonseca, R 2015. Estimates of genetic parameters for growth traits in Brahman cattle using random regression and multitrait models. Journal of Animal Science 93, 3814–3819.Google Scholar
Bruinsma, J 2003. World agriculture: towards 2015/2030: an FAO perspective. Earthscan Publications Ltd. London, UK.Google Scholar
Bureau of Animal Husbandry and Genetic Improvement (BAHGI) 2015. Brahman cattle. Retrieved on 21 March 2016, from http://breeding.dld.go.th/.Google Scholar
Estrada-León, RJ, Magaña-Monforte, JG and Segura-Correa, JC 2014. Estimation of genetic parameters for preweaning growth traits of Brahman cattle in Southeastern Mexico. Tropical Animal Health and Production 46, 771–776.Google Scholar
Gilbert, RP, Bailey, DR and Shannon, NH 1993. Body dimensions and carcass measurements of cattle selected for postweaning gain fed two different diets. Journal of Animal Science 71, 1688–1698.Google Scholar
Gilmour, AR, Gogel, BJ, Cullis, BR, Welham, SJ and Thompson, R 2015. ASReml user guide release 4.1 structural specification. VSN International Ltd., Hemel Hempstead, UK.Google Scholar
Intaratham, W, Koonawootrittriron, S, Sopannarath, P, Graser, HU and Tumwasorn, S 2008. Genetic parameters and annual trends for birth and weaning weights of a Northeastern Thai indigenous cattle line. Asian-Australasian Journal of Animal Sciences 21, 478–483.Google Scholar
Magnabosco, CDU, Ojala, M, De Los Reyes, A, Sainz, RD, Fernandes, A and Famula, TR 2002. Estimates of environmental effects and genetic parameters for body measurements and weight in Brahman cattle raised in Mexico. Journal of Animal Breeding and Genetics 119, 221–228.Google Scholar
Maiwashe, AN, Bradfield, MJ, Theron, HE and van Wyk, JB 2002. Genetic parameter estimates for body measurements and growth traits in South African Bonsmara cattle. Livestock Production Science 75, 293–300.Google Scholar
Osothongs, M, Khemsawat, J, Sarakul, M, Jattawa, D, Suwanasopee, T and Koonawootrittriron, S 2016. Current situation of beef industry in Thailand. In Proceedings of International Symposium: “Dairy Cattle Beef Up Beef Industry in Asia: Improving Productivity and Environmental Sustainability”, 19 August 2016, Bangkok, Thailand, pp. 5–8.Google Scholar
Pico, BA, Neser, FWC and Van Wyk, JB 2004. Genetic parameters for growth traits in South African Brahman cattle. South African Journal of Animal Science 34, 44–46.Google Scholar
RStudio Team 2016. RStudio: integrated development for R. RStudio, Boston, MA, USA.Google Scholar
Simm, G 1998. Genetic improvement of cattle and sheep. Farming Press, Ipswich, England.Google Scholar
Supriyantono, A, Tomiyama, M and Suzuki, K 2012. Estimation of (co)variance components and genetic parameter of withers height, chest girth and body length of Bali cattle using animal model. International Journal of Molecular Zoology 2, 45–50.Google Scholar
Tessema, T, Sopannarath, P, Tumwasorn, S and Raungprim, T 2013. Genetic parameters for weaning weight, weaning hip height and weaning body length of crossbred beef cattle in Thailand. Kasetsart Journal (Natural Science) 47, 85–93.Google Scholar
Toghiani, S 2012. Quantitative genetic application in the selection process for livestock production. In Livestock production (ed. K Javed), pp. 3-32. IntechOpen, Rijeka, Croatio.Google Scholar
Vargas, G, Buzanskas, ME, Guidolin, DGF, Grossi, DdA, Bonifácio, AdS, Lôbo, RB, da Fonseca, R, Oliveira, JAd and Munari, DP 2014. Genetic parameter estimation for pre- and post-weaning traits in Brahman cattle in Brazil. Tropical Animal Health and Production 46, 1271–1278.Google Scholar
Vargas, CA, Elzo, MA, Chase, CC, Chenoweth, PJ and Olson, TA 1998. Estimation of genetic parameters for scrotal circumference, age at puberty in heifers, and hip height in Brahman cattle. Journal of Animal Science 76, 2536–2541.Google Scholar
Vargas, CA, Elzo, MA, Chase, CC and Olson, TA 2000. Genetic parameters and relationships between hip height and weight in Brahman cattle. Journal of Animal Science 78, 3045–3052.Google Scholar
Visscher, PM, Hill, WG and Wray, NR 2008. Heritability in the genomics era – concepts and misconceptions. Nature Reviews Genetics 9, 255–266.Google Scholar