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KMID : 1025520040460050719
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Journal of Animal Science and Technology
2004 Volume.46 No. 5 p.719 ~ p.728
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Comparison between REML and Bayesian via Gibbs Sampling Algorithm with a Mixed Animal Model to Estimate Genetic Parameters for Carcass Traits in Hanwoo(Korean Native Cattle)
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Roh S. H.
Kim Byung-Woo
Kim H. S.
Min H.-S.
Yoon Ho-Baek
Lee Deuk-Hwan
Jeon Jin-Tae
Lee Jung-Gyu
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Abstract
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The aims of this study were to estimate genetic parameters for carcass traits on Hanwoo(Korean Native Cattle) and to compare two different statistical algorithms for estimating genetic parameters. Data obtained from 1526 steers at Hanwoo Improvement Center and Hanwoo Improvement Complex Area from 1996 to 2001 were used for the analyses. The carcass traits considered in these studies were carcass weight, dressing percent, eye muscle area, backfat thickness, and marbling score. Estimated genetic parameters using EM-REML algorithm were compared to those by Bayesian inference via Gibbs Sampling to find out statistical properties. The estimated heritabilities of carcass traits by REML method were 0.28, 0.25, 0.35, 0.39 and 0.51, respectively and those by Gibbs Sampling method were 0.29, 0.25, 0.40, 0.42 and 0.54, respectively. This estimates were not significantly different, even though the estimated heritabilities by Gibbs Sampling method were higher than ones by REML method.
Since the estimated statistics by REML method and Gibbs Sampling method were not significantly different in this study, it is inferred that both mothods could be efficiently applied for the analysis of carcass traits of cattle. However, further studies are demanded to define an optimal statistical method for handling large scale performance data.
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KEYWORD
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Hanwoo(Korean Native Cattle), Carcass traits, Genetic parameters, REML method, Gibbs Sampling method
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