Czech J. Anim. Sci., 2008, 53(7):273-283 | DOI: 10.17221/357-CJAS

Comparison of different traits to evaluate the growth of bulls

J. Přibyl1, J. Přibylová1, H. Krejčová1, N. Mielenz2
1 Institute of Animal Science, Prague-Uhříněves, Czech Republic
2 University of Halle-Wittenberg, Halle, Germany

The live weights of 8 243 performance-tested bulls from 100 to 400 days of age were analysed using random regression (RR) and single-trait animal models. Evaluations were done for live weight at 400 days of age and gains from 100 to 400 days of age at various monthly intervals. Estimates of variance components differed depending on the trait definition and model of analysis. Systematic environmental effects explained a higher proportion of variability in the RR for gains than for other definitions of growth. The expected average reliability of estimated breeding values was similar for all methods from 0.42 to 46, but the rankings of animals differed. Determinations (r2) of breeding values between methods ranged from 0.64 to 0.94. Correlations of the breeding values of progeny at performance-test stations with parents were highest for the evaluation of gains in consecutive intervals evaluated by RR. Correlations of the breeding values of sires from their growth at performance-test stations with the breeding values of groups of progeny at progeny-test stations were from 0.26 to 0.38. Correlations were the highest for RR evaluations of gain using consecutive short intervals. Evaluation of the growth of animals according to daily gains in short consecutive intervals was preferred because more animals and more observations per animal were included in the evaluations, and the growth curve was separated into genetic and non-genetic parts. Simple evaluation of growth according to the final weight or daily gain in a long interval is not entirely correct, since environmental compensatory growth can occur.

Keywords: bulls; daily gains; random regression; breeding values; variances

Published: July 31, 2008  Show citation

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Přibyl J, Přibylová J, Krejčová H, Mielenz N. Comparison of different traits to evaluate the growth of bulls. Czech J. Anim. Sci. 2008;53(7):273-283. doi: 10.17221/357-CJAS.
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    References

    1. Albuquerque L.G., Meyer K. (2001): Estimates of direct and maternal genetic effects for weights from birth to 600 days of age in Nelore cattle. J. Anim. Breed. Genet., 118, 83-92. Go to original source...
    2. Bartoň L., Kudrna V., Bureš D., Zahrádková R., Teslík V. (2007): Performance and carcass quality of Czech Fleckvieh, Charolais and Charolais × Czech Fleckvieh bulls fed diets based on different types of silages. Czech J. Anim. Sci., 52, 269-276. Go to original source...
    3. Bohmanová J., Misztal I., Bertrand J.K. (2005): Studies on multiple trait and random regression models for genetic evaluation of beef cattle for growth. J. Anim. Sci., 83, 62-67. Go to original source... Go to PubMed...
    4. Bouška J., Štípková M., Frelich J., Zedníková J., Bartoň L. (2003): Genetic parameters of the traits recorded in the performance test of dual-purpose bulls. Czech J. Anim. Sci., 48, 413-418.
    5. Cantet R.J.C., Birchmeier A.N., Canaza Cayo A.W., Fioretti C. (2005): Semiparametric animal models via penalized splines as alternatives to models with contemporary groups. J. Anim. Sci., 83, 2482-2494. Go to original source... Go to PubMed...
    6. Hyánek J., Hyánková L. (1995): Multiphasic growth curves. Živoč. Výr., 40, 283-286. (in Czech)
    7. Kirkpatrick M., Lofsvold D., Bulmer M. (1990): Analysis of the inheritance, selection and evolution of growth trajectories. Genetics, 124, 979-993. Go to original source... Go to PubMed...
    8. Konstantinov K.V., Váchal J. (1985): Discussion on different linear models for BLUP evaluation of performance-tested dairy bulls. Sci. Agric. Bohem., 17, 131-135.
    9. Krejčová H., Mielenz N., Přibyl J., Schüler L. (2007a): Estimation of genetic parameters for daily gains of bulls with Multi-Trait and Random Regression models. Arch. Tierzucht. 50, 37-46. Go to original source...
    10. Krejčová H., Mielenz N., Přibyl J., Schüler L. (2007b): Comparison of breeding values for daily gains of bulls estimated with Multi-Trait and Random Regression models, Arch. Tierzucht., 50, 147-154. Go to original source...
    11. Krejčová H., Přibyl J., Přibylová J., Štípková M., Mielenz N. (2008): Genetic evaluation of daily gains of dualpurpose bulls using random regression model. Czech J. Anim. Sci., 53, 227-237. Go to original source...
    12. Legarra A., Misztal I., Bertrand J.K. (2004): Construction of covariance functions for random regression models for growth in Gelbvieh beef cattle. J. Anim. Sci., 82, 1564-1571. Go to original source... Go to PubMed...
    13. Maxa J., Norberg E., Berg P., Milerski M. (2007): Genetic parameters for body weight, longissimus muscle depth and fat depth for Suffolk sheep in the Czech Republic. Small Rumin. Res., 72, 87-91. Go to original source...
    14. Meyer K. (2001): Estimates of direct and maternal covariance function for growth of Australian beef calves from birth to weaning. Genet. Sel. Evol., 33, 487-514. Go to original source... Go to PubMed...
    15. Meyer K. (2005): Advances in methodology for random regression analysis. Aust. J. Exp. Agric., 45, 847-858. Go to original source...
    16. Mielenz N., Krejčová H., Přibyl J., Schüler L. (2007): Anpassung eines Fixet Regression Model für die tägliche Zunahme von Fleckviehbullen mit Hilfe von Informationskriterien. Arch. Tierzucht., 50, 47-58. Go to original source...
    17. Miglior F., Van Doormaal B.J. (2000): Impact of second country proofs on genetic evaluations. Interbull Bull., 25, 57-59.
    18. Misztal I., Tsuruta S., Strabel T., Auvray B., Druet T., Lee D.H. (2002): BLUPF90 and related programs (BGF90). In: 7th WCGALP, August 19-23, Montpellier, France, 28-07.
    19. Nešetřilová H. (2005): Multiphasic growth models for cattle. Czech J. Anim. Sci., 50, 347-354. Go to original source...
    20. Nobre P.R.C., Misztal I., Tsuruta S., Bertrand J.K., Silva L.O.C., Lopez P.S. (2003): Genetic evaluation of growth in Nelore cattle by multi-trait and random regression model. J. Anim.Sci., 81, 927-932. Go to original source... Go to PubMed...
    21. Přibyl J., Misztal I., Přibylová J., Šeba K. (2003): Multiplebreed, multiple-traits evaluation of beef cattle in the Czech Republic. Czech J. Anim. Sci., 48, 519-532.
    22. Přibyl J., Krejčová H., Přibylová J., Misztal I., Bohmanová J., Štípková M. (2007): Trajectory of body weight of performance tested dual-purpose bulls. Czech J. Anim. Sci., 52, 315-324. Go to original source...
    23. Přibyl J., Krejčová H., Přibylová J., Misztal I., Tsuruta S., Mielenz N. (2008): Models for evaluation of growth of performance tested bulls. Czech J. Anim. Sci., 53, 45-54. Go to original source...
    24. Pulkrábek J., Šiler R., Nešetřilová H., Mejsnar J. (1983): Heritability of fattening traits for Czech Fleckvieh. Živoč. Výr., 28, 81-86. (in Czech)
    25. SAS (2005): SAS/STAT User's Guide, Version 9.1., SAS Institute, Inc., Cary, North Carolina, USA.
    26. Schaeffer L.R., Reents R., Jamrozik J. (1996): Factors influencing international comparison of dairy sires. J. Dairy Sci., 79, 1108-1116. Go to original source... Go to PubMed...
    27. Vuori K., Stranden I., Sevon-Aimonen M.L., Mäntysaari E.A. (2006): Estimation of non-linear growth models by linearization: a simulation study using a Gompertz function. Genet. Sel. Evol., 38, 343-358. Go to original source... Go to PubMed...
    28. Wolf J., Žáková E., Groenveld E. (2005): Genetic parameters for a joint genetic evaluation of production and reproduction traits in pigs. Czech J. Anim. Sci., 50, 96-103. Go to original source...

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