Animal Bioscience

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Genetic parameters and correlations of related feed efficiency, growth, and carcass traits in Hanwoo beef cattle

  • Received : 2020.02.27
  • Accepted : 2020.08.14
  • Published : 2021.05.01
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Abstract

Objective: This study aimed to estimate the genetic parameters and genetic correlations for related feed efficiency, growth, and carcass traits in Hanwoo cattle. Methods: Phenotypic data from 15,279 animals born between 1989 and 2015 were considered. The related feed efficiency traits considered were Kleiber ratio (KR) and relative growth rate (RGR). Carcass traits analyzed were backfat thickness (BT), carcass weight, eye muscle area, and marbling score. Growth traits were assessed by the average daily gain (ADG), metabolic body weight (MBW) at mid-test age from 6 to 24 months, and yearling weight (YW). Variance and covariance components were estimated using restricted maximum likelihood using nine multi-trait animal models. Results: The heritability estimates for related feed efficiency (0.28±0.04 for KR and RGR) and growth traits (0.26±0.02 to 0.33±0.04) were moderate, but the carcass traits tended to be higher (0.38±0.04 to 0.61±0.06). The related feed efficiency traits were positively genetically correlated with all the carcass traits (0.37±0.09 to 0.47±0.07 for KR, and 0.14±0.09 to 0.37±0.09 for RGR), except for BT, which showed null to weak correlation. Conversely, the genetic correlations of RGR with MBW (-0.36±0.08) and YW (-0.30±0.08) were negative, and those of KR with MBW and YW were close to zero, whereas the genetic correlations of ADG with RGR (0.40±0.08) and KR (0.70±0.05) were positive and relatively moderate to high. The genetic (0.92±0.02) correlations between KR and RGR were very high. Conclusion: Sufficient genetic variability and heritability were observed for traits of interest. Moreover, the inclusion of KR and/or RGR in Hanwoo cattle breeding programs could improve the feed efficiency without producing any unfavorable effects on the carcass traits.

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References

  1. Hoque MA, Hosono M, Oikawa T, Suzuki K. Genetic parameters for measures of energetic efficiency of bulls and their relationships with carcass traits of field progeny in Japanese Black cattle. J Anim Sci 2009;87:99-106. https://doi.org/10.2527/jas.2007-0766
  2. Berry DP, Crowley JJ. Cell biology symposium: genetics of feed efficiency in dairy and beef cattle. J Anim Sci 2013;91: 1594-613. https://doi.org/10.2527/jas.2012-5862
  3. Grion AL, Mercadante MEZ, Cyrillo JNSG, Bonilha SFM, Magnani E, Branco RH. Selection for feed efficiency traits and correlated genetic responses in feed intake and weight gain of Nellore cattle. J Anim Sci 2014;92:955-65. https://doi.org/10.2527/jas.2013-6682
  4. Koch RM, Swiger LA, Chambers D, Gregory KE. Efficiency of feed use in beef cattle. J Anim Sci 1963;22:486-94. https://doi.org/10.2527/jas1963.222486x
  5. Brody S. Bioenergetics and growth with special reference to the efficiency complex in domestic animals. New York, NY, USA: Reinhold Publishers; 1945.
  6. Fitzhugh HA, Taylor SC. Genetic analysis of degree of maturity. J Anim Sci 1971;33:717-25. https://doi.org/10.2527/jas1971.334717x
  7. Kleiber M. Body size and metabolic rate. Physiol Rev 1947; 27:511-41. https://doi.org/10.1152/physrev.1947.27.4.511
  8. Bergh L, Scholtz MM, Erasmus GJ. Identification and assessment of the best animals: the Kleiber ratio (growth rate/metabolic mass) as a selection criterion for beef cattle. In: Proceedings of the Australian Association of Animal Breeding and Genetics; 1992. pp. 338-40.
  9. Arthur PF, Renand G, Krauss D. Genetic and phenotypic relationships among different measures of growth and feed efficiency in young Charolais bulls. Livest Prod Sci 2001;68: 131-9. https://doi.org/10.1016/S0301-6226(00)00243-8
  10. Crowley JJ, McGee M, Kenny DA, Crews DH, Evans RD, Berry DP. Phenotypic and genetic parameters for different measures of feed efficiency in different breeds of Irish performance-tested beef bulls. J Anim Sci 2010;88:885-94. https://doi.org/10.2527/jas.2009-1852
  11. Kim JB, Kim DJ, Lee JK, Lee CY. Genetic relationship between carcass traits and carcass price of Korean cattle. Asian-Australas J Anim Sci 2010;23:848-54. https://doi.org/10.5713/ajas.2010.90555
  12. Choi TJ, Alam M, Cho CI, et al. Genetic parameters for yearling weight, carcass traits, and primal-cut yields of Hanwoo cattle. J Anim Sci 2015;93:1511-21. https://doi.org/10.2527/jas.20147953
  13. Bhuiyan MSA, Kim HJ, Lee DH, et al. Genetic parameters of carcass and meat quality traits in different muscles (longissimus dorsi and semimembranosus) of Hanwoo (Korean cattle). J Anim Sci 2017;95:3359-69. https://doi.org/10.2527/jas.2017.1493
  14. Park B, Choi T, Kim S, Oh SH. National genetic evaluation (system) of Hanwoo (Korean native cattle). Asian-Australas J Anim Sci 2013;26:151-6. https://doi.org/10.5713/ajas.2012.12439
  15. Mrode RA. Linear models for the prediction of animal breeding values. 3rd ed. Wallingford, UK: CABI; 2014.
  16. Misztal I, Tsuruta S, Strabel T, Auvray B, Druet T, Lee DH. BLUPF90 and related programs (BGF90). In: Proceedings of the 7th world congress on genetics applied to livestock production; 2002: Montpellier, France. pp. 743-44
  17. Meyer K. WOMBAT-a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML). J Zheijang Univ Sci B 2007;8:815-21. https://doi.org/10.1631/jzus.2007.B0815
  18. Lee SH, Choi BH, Lim D, et al. Genome-wide association study identifies major loci for carcass weight on BTA14 in Hanwoo (Korean cattle). PLoS One 2013;8:e74677. https://doi.org/10.1371/journal.pone.0074677
  19. Riley DG, Chase CC, Hammond AC, et al. Estimated genetic parameters for carcass traits of Brahman cattle. J Anim Sci 2002;80:955-62. https://doi.org/10.2527/2002.804955x
  20. Smith T, Domingue JD, Paschal JC, Franke DE, Bidner TD, Whipple G. Genetic parameters for growth and carcass traits of Brahman steers. J Anim Sci 2007;85:1377-84. https://doi.org/10.2527/jas.2006-653
  21. Takeda M, Uemoto Y, Inoue K, et al. Evaluation of feed efficiency traits for genetic improvement in Japanese Black cattle. J Anim Sci 2018;96:797-805. https://doi.org/10.1093/jas/skx054
  22. Yokoo MJ, Lobo RB, Araujo FRC, Bezerra LAF, Sainz RD, Albuquerque LG. Genetic associations between carcass traits measured by real-time ultrasound and scrotal circumference and growth traits in Nelore cattle. J Anim Sci 2010;88:52-8. https://doi.org/10.2527/jas.2008-1028
  23. Zuin RG, Buzanskas ME, Caetano SL, et al. Genetic analysis on growth and carcass traits in Nelore cattle. Meat Sci 2012; 91:352-7. https://doi.org/10.1016/j.meatsci.2012.02.018
  24. Kemp DJ, Herring WO, Kaiser CJ. Genetic and environmental parameters for steer ultrasound and carcass traits. J Anim Sci 2002;80:1489-96. https://doi.org/10.2527/2002.8061489x
  25. Arthur PF, Archer JA, Johnston DJ, Herd RM, Richardson EC, Parnell PF. Genetic and phenotypic variance and covariance components for feed intake, feed efficiency, and other postweaning traits in Angus cattle. J Anim Sci 2001;79:280511. https://doi.org/10.2527/2001.79112805x
  26. Schenkel FS, Miller SP, Wilton JW. Genetic parameters and breed differences for feed efficiency, growth, and body composition traits of young beef bulls. Can J Anim Sci 2004;84: 177-85. https://doi.org/10.4141/A03-085
  27. Hoque MA, Hiramoto K, Oikawa T. Genetic relationship of feed efficiency traits of bulls with growth and carcass traits of their progeny for Japanese Black (Wagyu) cattle. Anim Sci J 2005;76:107-14. https://doi.org/10.1111/j.1740-0929.2005.00244.x
  28. Oikawa T, Hoque MA, Hitomi T, Suzuki K, Uchida H. Genetic parameters for traits in performance and progeny tests and their genetic relationships in Japanese Black cattle. Asian-Australas J Anim Sci 2006;19:611-6. https://doi.org/10.5713/ajas.2006.611
  29. Ceacero TM, Mercadante MEZ, Cyrillo JNSG, Canesin RC, Bonilha SFM, Albuquerque LG. Phenotypic and genetic correlations of feed efficiency traits with growth and carcass traits in Nellore cattle selected for postweaning weight. PLoS One 2016;11:e0161366. https://doi.org/10.1371/journal.pone.0161366
  30. Coyne JM, Judge MM, Conroy S, Berry DP. Variance component estimation of efficiency, carcass and meat quality traits in beef cattle. In: Proceedings of the World Congress on Genetics Applied to Livestock Production; 2018. pp. 912.
  31. Koots KR, Gibson JP, Smith C, Wilton JW. Analyses of published genetic parameter estimates for beef production traits. 1. Heritability. Anim Breed Abstr 1994;62:309-38.
  32. Do CH, Park BH, Kim SD, et al. Genetic parameter estimates of carcass traits under national scale breeding scheme for beef cattle. Asian-Australas J Anim Sci 2016;29:1083-94. https://doi.org/10.5713/ajas.15.0696
  33. Hwang JM, Cheong JK, Kim SS, et al. Genetic analysis of ultrasound and carcass measurement traits in a regional Hanwoo steer population. Asian-Australas J Anim Sci 2014; 27:457-63. https://doi.org/10.5713/ajas.2013.13543
  34. Mao F, Chen L, Vinsky M, et al. Phenotypic and genetic relationships of feed efficiency with growth performance, ultrasound, and carcass merit traits in Angus and Charolais steers. J Anim Sci 2013;91:2067-76. https://doi.org/10.2527/jas.2012-5470
  35. Kelly AK, McGee M, Crews DH, Sweeney T, Boland TM, Kenny DA. Repeatability of feed efficiency, carcass ultrasound, feeding behavior, and blood metabolic variables in finishing heifers divergently selected for residual feed intake. J Anim Sci 2010;88:3214-25. https://doi.org/10.2527/jas.2009-2700

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