Animal Bioscience

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Genetic study of quantitative traits supports the use of Guzera as dual-purpose cattle

  • Received : 2021.10.05
  • Accepted : 2021.11.29
  • Published : 2022.07.01
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Abstract

Objective: The aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle. Methods: The evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365), and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210. Results: The direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative (-0.43 to -0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations. Conclusion: These results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.

Keywords

Acknowledgement

The authors thank the Centro Brasileiro de Melhoramento Genetico do Guzera (CBMG2) and Associacao Brasileira de Criadores de Zebu (ABCZ) for providing the datasets.

References

  1. Bruneli FAT, Peixoto MGCD, Santana Junior ML, et al. National breeding program of guzera cattle for milk: progeny testing, national zootechnical archive and MOET nucleus results. 1st edition. Juiz de Fora: Embrapa Dairy Cattle: Brazilian Agricultural Research Corporation Documents, 251; 2020.
  2. Peixoto MGCD, Carvalho MRS, Egito AA, et al. genetic diversity and population genetic structure of a Guzera (Bos indicus) meta-population. Animals 2021;11:1125. https://doi.org/10.3390/ani11041125
  3. Galue FU, Pena ME, Rincon R, Romero J, Rendon-Ortin M. Management and technology in cattle dual purpose systems (taurus-indicus). Rev Cient la Fac Ciencias Vet la Univ del Zulia 2008;18:715-24.
  4. Albarran-Portillo B, Rebollar-Rebollar S, Garcia-Martinez A, Rojo-Rubio R, Aviles-Nova F, Arriaga-Jordan CM. Socioeconomic and productive characterization of dual-purpose farms oriented to milk production in a subtropical region of Mexico. Trop Anim Health Prod 2015;47:519-23. https://doi.org/10.1007/s11250-014-0753-8
  5. Rangel J, Perea J, De-Pablos-Heredero C, et al. Structural and technological characterization of tropical smallholder farms of dual-purpose cattle in Mexico. Animals 2020;10:86. https://doi.org/10.3390/ani10010086
  6. Wathes DC, Pollott GE, Johnson KF, Richardson H, Cooke JS. Heifer fertility and carry over consequences for life time production in dairy and beef cattle. Animal 2014;8:91-104. https://doi.org/10.1017/S1751731114000755
  7. Carvalho Filho I, Marques DBD, Campos CF, et al. Genetic parameters for fertility traits in Nellore bulls. Reprod Domest Anim 2020;55:38-43. https://doi.org/10.1111/rda.13578
  8. Berry DP, Evans RD. Genetics of reproductive performance in seasonal calving beef cows and its association with performance traits. J Anim Sci 2014;92:1412-22. https://doi.org/10.2527/jas.2013-6723
  9. Claus LAM, Koetz Junior C, Roso VM, Borges MHF, Barcellos JOJ, Ribeiro ELA. Genetic parameters of age at first calving, weight gain, and visual scores in Nelore heifers. Rev Bras Zootec 2017;46:303-8. https://doi.org/10.1590/s1806-92902017000400005
  10. Brito LC, Peixoto MGCD, Carrara ER, et al. Genetic parameters for milk, growth, and reproductive traits in Guzera cattle under tropical conditions. Trop Anim Health Prod 2020;52:2251-7. https://doi.org/10.1007/s11250-020-02255-0
  11. BIF guidelines. In: Cundiff LV, Van Vleck LD, Hohenboken WD, editors. Guidelines for uniform beef improvement programs (Ninth Edition - Revised March, 2018). 9th ed. Beef Improvement Federation; 2018.
  12. SAS Institute. SAS/STAT 15.1 user's guide. Cary, NC, USA: SAS Institute Inc.; 2018.
  13. Misztal I, Tsuruta S, Lourenco D, Aguilar I, Legarra A, Vitezica Z. Manual for BLUPF90 family of programs. Athens, GA, USA: University of Georgia; 2018.
  14. Mrode RA, Thompson R. Linear models for the prediction of animal breeding values. 3rd ed. Wallingford, Oxon, UK: CAB International; 2014.
  15. Terakado APN, Boligon AA, Baldi F, Silva JAIV, Albuquerque LG. Genetic associations between scrotal circumference and female reproductive traits in Nelore cattle. J Anim Sci 2015;93:2706-13. https://doi.org/10.2527/jas.2014-8817
  16. Buzanskas ME, Pires PS, Chud TCS, et al. Parameter estimates for reproductive and carcass traits in Nelore beef cattle. Theriogenology 2017;92:204-9. https://doi.org/10.1016/j.theriogenology.2016.09.057
  17. Santos DJA, Peixoto MGCD, Borquis RRA, Verneque RS, Panetto JCC, Tonhati H. Genetic parameters for test-day milk yield, 305-day milk yield, and lactation length in Guzerat cows. Livest Sci 2013;152:114-9. https://doi.org/10.1016/j.livsci.2012.12.012
  18. Gama MPM, Ventura HT, Alencar Pereira M, El Faro L, Paz CCP. Genetic associations between milk production and growth traits in Guzerat breed. J Anim Sci 2016;94:178. https://doi.org/10.2527/jam2016-0369
  19. Da Silva RPA, Lobo RNB, El Faro L, dos Santos GG, Bruneli FAT, Peixoto MGCD. Genetic parameters for somatic cell count (SCC) and milk production traits of Guzera cows using data normalized by different procedures. Trop Anim Health Prod 2020;52:2513-22. https://doi.org/10.1007/s11250-020-02277-8
  20. Tramonte NC, Grupioni NV, Stafuzza NB, et al. Genetic parameters, genetic trends, and principal component analysis for productive and reproductive traits of Guzera beef cattle. Rev Bras Zootec 2019;48:e20180034. https://doi.org/10.1590/rbz4820180034
  21. Kluska S, Olivieri BF, Bonamy M, et al. Estimates of genetic parameters for growth, reproductive, and carcass traits in Nelore cattle using the single step genomic BLUP procedure. Livest Sci 2018;216:203-9. https://doi.org/10.1016/j.livsci.2018.08.015
  22. Stefani G, Aquaroli DB, Costa Junior JBG, et al. Genetic parameters for dystocia, milk yield and age at first calving in Brazilian Holstein cows. J Appl Anim Res 2021;49:1-5. https://doi.org/10.1080/09712119.2020.1856115
  23. Land RB. The expression of female sex-limited characters in the male. Nature 1973;241:208-9. https://doi.org/10.1038/241208a0
  24. Hull KL, Harvey S. Growth hormone and reproduction: a review of endocrine and autocrine/paracrine interactions. Int J Endocrinol 2014;2014:Article ID 234014. https://doi.org/10.1155/2014/234014
  25. Mazza S, Guzzo N, Sartori C, Mantovani R. Genetic correlations between type and test-day milk yield in small dual-purpose cattle populations: The Aosta Red Pied breed as a case study. J Dairy Sci 2016;99:8127-36. https://doi.org/10.3168/jds.2016-11116
  26. Searle SR. Phenotypic, genetic and environmental correlations. Biometrics 1961;17:474-80. https://doi.org/10.2307/2527838
  27. Peixoto MGCD, Santos DJA, Borquis RRA, Bruneli FAT, Panetto JCC, Tonhati H. Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal legendre polynomials. Pesqui Agropecu Bras 2014;49:373-83. https://doi.org/10.1590/S0100-204X2014000500007