Genetic parameters for carcass traits and their live animal indicators in Simmental cattle1

2003 ◽  
Vol 81 (6) ◽  
pp. 1427-1433 ◽  
Author(s):  
D. H. Crews ◽  
E. J. Pollak ◽  
R. L. Weaber ◽  
R. L. Quaas ◽  
R. J. Lipsey
1996 ◽  
Vol 1996 ◽  
pp. 113-113 ◽  
Author(s):  
M. Araghi ◽  
M.K. Curran ◽  
G.E. Pollott

In 1989, ten Suffolk breeders co-operated to establish a nucleus flock at Wye College. The group is known as the Wye Suffolk Improvement Group (WSIG). The members each contributed 5-10 pedigree ewes to use as the initial nucleus flock. Eighty-nine ewes were delivered to the College by the various participants. The objective of this study was to obtain estimates of the heritabilities of live animal traits, used to improve carcass traits, and phenotypic and genotypic correlation estimates between them in the Suffolk lambs in the south of England.


1996 ◽  
Vol 1996 ◽  
pp. 113-113
Author(s):  
M. Araghi ◽  
M.K. Curran ◽  
G.E. Pollott

In 1989, ten Suffolk breeders co-operated to establish a nucleus flock at Wye College. The group is known as the Wye Suffolk Improvement Group (WSIG). The members each contributed 5-10 pedigree ewes to use as the initial nucleus flock. Eighty-nine ewes were delivered to the College by the various participants. The objective of this study was to obtain estimates of the heritabilities of live animal traits, used to improve carcass traits, and phenotypic and genotypic correlation estimates between them in the Suffolk lambs in the south of England.


2013 ◽  
Vol 53 (10) ◽  
pp. 1075
Author(s):  
Vinzent Börner ◽  
David J. Johnston ◽  
Hans-Ulrich Graser

Genetic parameters of four ultrasound live-scan traits and five carcass traits of Australian Angus cattle were examined with regard to sex and age of the scanned individuals. Live-scans were subdivided according to whether the observation was obtained from a bull or a heifer. In addition, two age subset (‘young’ and ‘old’) within sex were formed by k-means clustering around two centres within sex according to the age at scanning. REML estimates for heritabilities, genetic, residual and phenotypic correlations for each trait and trait combination were derived from a series of uni-, bi- and tri-variate analysis. Statistically significant age effects could be found for heritablities of scan intra-muscular fat content in heifers and scan fat depth at P8 site and scan rib fat depth in bulls, and for genetic correlations between the scan traits fat depth at P8 site, rib fat depth and eye muscle area. However, differences in heritablities between age sets within sex did not exceed 0.05, and genetic correlations between scan traits of ‘young’ and ‘old’ animals were at least 0.9. Differences between genetic correlations of abattoir carcass traits and ‘young’ and ‘old’ live-scan traits, respectively, were not significant due to high standard errors but up to 0.44. The larger of these differences were found for combinations of scan-traits and non-target carcass traits and not for combination of scan-traits and their actual carcass target traits. Thus, although some results suggest an age effect on the genetic parameters of scan traits, the extent of this effect is of limited impact on breeding value accuracy and genetic gain of scan traits. Furthermore, a possible age effect on correlations to economically important carcass traits need to be underpinned by more carcass traits observations in order to get unambiguous results allowing to draw consequences of scanning younger individuals for accuracy of breeding values and genetic gain in carcass traits.


2006 ◽  
Vol 104 (1-2) ◽  
pp. 46-52 ◽  
Author(s):  
I. Nagy ◽  
N. Ibáñez ◽  
R. Romvári ◽  
W. Mekkawy ◽  
Sz. Metzger ◽  
...  

2002 ◽  
Vol 80 (4) ◽  
pp. 955-962 ◽  
Author(s):  
D. G. Riley ◽  
C. C. Chase ◽  
A. C. Hammond ◽  
R. L. West ◽  
D. D. Johnson ◽  
...  

2016 ◽  
Vol 15 (2) ◽  
Author(s):  
S.L.C. Meirelles ◽  
F.B. Mokry ◽  
A.C. Espasandín ◽  
M.A.D. Dias ◽  
M.M. Baena ◽  
...  

2000 ◽  
Vol 78 (7) ◽  
pp. 1786 ◽  
Author(s):  
A Reverter ◽  
D J Johnston ◽  
H U Graser ◽  
M L Wolcott ◽  
W H Upton

2020 ◽  
Vol 33 (4) ◽  
pp. 525-530 ◽  
Author(s):  
Byoungho Park ◽  
Tae Jeong Choi ◽  
Mi Na Park ◽  
Sang-Hyon Oh

Objective: The purpose of this study was i) to identify the characteristics of carcass traits in Chikso by gender, region, age at slaughter, and coat color using the carcass data collected from the nationwide pedigree information and coat color investigation, and ii) to estimate genetic parameters for breed improvement.Methods: A linear model was used to analyze the environmental effects on the carcass traits and to estimate genetic parameters. Analysis of variance was performed using TYPE III sum of squares for the unbalanced data provided by the general linear model procedure. Variance components for genetic parameters was estimated using REMLF90 of the BLUPF90 family programs.Results: Phenotypic performance of carcass weight (CW), eye muscle area (EMA), and backfat thickness (BF) in Chikso were lower than those of Hanwoo. This is a natural outcome because Hanwoo have undergone significant efforts for improvement at the national level, a phenomenon not observed in Chikso. Another factor influencing the above outcome was the smaller population size of Chikso compared to that of Hanwoo’s. The heritabilities of CW, EMA, BF, and marbling score in Chikso were estimated as 0.50, 0.37, 0.35, and 0.53, respectively, which were was higher than those of Hanwoo.Conclusion: Based on the genetic parameters that were estimated in this study, it is expected that the carcass traits will improve when the livestock research institutes at each province conduct small-scale performance tests and the semen is provided to farmers after selecting proven bulls using the state-of-art selection technique such as genomic selection.


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