Asian-Australasian Journal of Animal Sciences

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Estimation of Relative Economic Weights of Hanwoo Carcass Traits Based on Carcass Market Price

  • Choy, Yun-Ho (Animal Breeding and Genetics Division, National Institute of Animal Science) ;
  • Park, Byoung-Ho (Animal Breeding and Genetics Division, National Institute of Animal Science) ;
  • Choi, Tae-Jung (Animal Breeding and Genetics Division, National Institute of Animal Science) ;
  • Choi, Jae-Gwan (Animal Breeding and Genetics Division, National Institute of Animal Science) ;
  • Cho, Kwang-Hyun (Animal Breeding and Genetics Division, National Institute of Animal Science) ;
  • Lee, Seung-Soo (Animal Breeding and Genetics Division, National Institute of Animal Science) ;
  • Choi, You-Lim (Animal Breeding and Genetics Division, National Institute of Animal Science) ;
  • Koh, Kyung-Chul (Korea Institute for Animal Products Quality Evaluation) ;
  • Kim, Hyo-Sun (Korea Institute for Animal Products Quality Evaluation)
  • Received : 2012.07.04
  • Accepted : 2012.09.04
  • Published : 2012.12.01
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Abstract

The objective of this study was to estimate economic weights of Hanwoo carcass traits that can be used to build economic selection indexes for selection of seedstocks. Data from carcass measures for determining beef yield and quality grades were collected and provided by the Korean Institute for Animal Products Quality Evaluation (KAPE). Out of 1,556,971 records, 476,430 records collected from 13 abattoirs from 2008 to 2010 after deletion of outlying observations were used to estimate relative economic weights of bid price per kg carcass weight on cold carcass weight (CW), eye muscle area (EMA), backfat thickness (BF) and marbling score (MS) and the phenotypic relationships among component traits. Price of carcass tended to increase linearly as yield grades or quality grades, in marginal or in combination, increased. Partial regression coefficients for MS, EMA, BF, and for CW in original scales were +948.5 won/score, +27.3 $won/cm^2$, -95.2 won/mm and +7.3 won/kg when all three sex categories were taken into account. Among four grade determining traits, relative economic weight of MS was the greatest. Variations in partial regression coefficients by sex categories were great but the trends in relative weights for each carcass measures were similar. Relative economic weights of four traits in integer values when standardized measures were fit into covariance model were +4:+1:-1:+1 for MS:EMA:BF:CW. Further research is required to account for the cost of production per unit carcass weight or per unit production under different economic situations.

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References

  1. Baik, D. H., M. A. Hoque, G. H. Park, H. K. Park, K. S. Shim and Y. H. Chung. 2003. Heritabilities and genetic correlation, and sire and environment effects on meat production potential of Hanwoo cattle. Asian-Aust. J. Anim. Sci. 16:1-5. https://doi.org/10.5713/ajas.2003.1
  2. Choy, Y. H., C. W. Lee, H. C. Kim, S. B. Choi, J. K. Choi and J. M. Hwang. 2008. Genetic models for carcass traits with different slaughter endpoints in selected Hanwoo herds I. Linear covariance models. Asian-Aust. J. Anim. Sci. 21:1227-1232. https://doi.org/10.5713/ajas.2008.60001
  3. Choy, Y. H., S. B. Choi, G. J. Jeon, H. C. Kim, H. J. Chung, J. M. Lee, B. Y. Park and S. H. Lee. 2010. Prediction of retail beef yield using parameters based on Korean beef carcass grading standards. Korean J. Food Sci. Anim. Resour. 30:905-909. https://doi.org/10.5851/kosfa.2010.30.6.905
  4. Ibi, T., A. K. Kahi and H. Hirooka. 2006. Effect of carcass price fluctuations on genetic and economic evaluation of carcass traits in Japanese Black cattle. J. Anim. Sci. 84:3204-3211. https://doi.org/10.2527/jas.2005-610
  5. Johnson, R. A. and D. W. Wichern. 1992. Applied multivariate statistical analyses. Prentice-Hall, Inc. Englewood Cliffs, NJ, USA.
  6. Kahi, A. K., T. Oguni, Y. Sumio and H. Hirooka. 2007. Genetic relationships between growth and carcass traits and profitability in Japanese Brown cattle. J. Anim. Sci. 85:348-355. https://doi.org/10.2527/jas.2005-657
  7. Kim, D. J., C. W. Lee, C. Y. Lee and J. B. Kim. 2010. The influence of carcass traits on carcass price in mature Hanwoo cow. J. Anim. Sci. Technol. 52:157-164 (in Korean). https://doi.org/10.5187/JAST.2010.52.2.157
  8. Lee, J. W., S. B. Choi, J. S. Kim, J. F. Keown and L. D. Van Vleck. 2000. Parameter estimates for genetic effects on carcass traits of Korean Native cattle. J. Anim. Sci. 78:1181-1190. https://doi.org/10.2527/2000.7851181x
  9. Moav, R. 1973. Economic evaluation of genetic differences. In: Agricultural Genetics, Selected Topics (Ed. R. Moav). John Wiley and Sons. New York, NY, USA. pp. 319-352.
  10. Perez-Cabal, M. A. and R. Alenda. 2002. Genetic relationships between lifetime profit and type traits in Spanish Holstein cows. J. Dairy Sci. 85:3480-3491. https://doi.org/10.3168/jds.S0022-0302(02)74437-8
  11. Perez-Cabal, M. A. and R. Alenda. 2003. Lifetime profit as an individual trait and prediction of its breeding values in Spanish Holstein cows. J. Dairy Sci. 86:4115-4122. https://doi.org/10.3168/jds.S0022-0302(03)74025-9
  12. $SAS/STAT^{(R)}$ 9.22 User's Guide. 2010. SAS Institute Inc. Cary, NC, USA.
  13. Visscher, P. M. and M. E. Goddard. 1995. Genetic analyses of profit for Australian dairy cattle. Anim. Sci. 61:9-18. https://doi.org/10.1017/S1357729800013461
  14. Weller, J. I. 1994. Economic aspects of animal breeding. Chapman & Hall. London, UK.

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