Czech J. Anim. Sci., 2011, 56(8):365-369 | DOI: 10.17221/2398-CJAS

Stability of estimated breeding values for average daily gain in Pannon White rabbits

I. Nagy1, J. Farkas2, P. Gyovai1, I. Radnai1, Z. Szendrő1
1 Department of Agricultural Product Processing and Qualification, Faculty of Animal Science, Kaposvár University, Kaposvár, Hungary
2 Faculty of Economic Science, Kaposvár University, Kaposvár, Hungary

Stability of estimated breeding values for average daily gain (ADG) between 5 and 10 weeks of age was analysed for 47 242 Pannon White rabbits, reared in 7470 litters and born between 2000 and 2008. The dataset was divided into 5 successive 5-year periods: (1) 2000-2004, (2) 2001-2005, (3) 2002-2006, (4) 2003-2007, and (5) 2004-2008. Then, after selecting the appropriate part of the pedigree for these sub-datasets, genetic parameters and breeding values were estimated for ADG using REML and BLUP methods. In the applied models sex, year-month, animal and random litter effects were considered. Estimated heritabilities for all 5 periods from 1 to 5 were moderate and stable (0.28 ± 0.01, 0.28 ± 0.02, 0.29 ± 0.02, 0.27 ± 0.02, and 0.28 ± 0.02). Magnitudes of random litter effects were low and stable (0.14 ± 0.01, 0.15 ± 0.01, 0.15 ± 0.01, 0.16 ± 0.01, and 0.16 ± 0.01). After breeding value estimation the dataset of period 5 was merged pair-wise with the other periods 4, 3, 2 and 1 using an inner join. Thus only the common records of the datasets representing the periods 5-4, 5-3, 5-2, and 5-1 were included in the merged datasets. In these merged datasets each rabbit had two breeding values for ADG based on two different periods. Spearman's rank correlation coefficients were calculated between the breeding values based on the dataset of period 5 and the other periods. With the successive years the rank correlation coefficients decreased (0.989, 0.979, 0.965 and 0.924). The correlation coefficients between ranks remained moderately high, even when the proportion of the common rabbits in the merged datasets was low. However, a reasonable re-ranking occurred among the top animals. Rank correlations for the top 100 and 1000 animals varied from 0.41 to 0.55 and from 0.37 to 0.54, respectively, which could influence selection efficiency if the rolling base were used for genetic evaluation.

Keywords: sub-datasets; inner join; rank correlation

Published: August 31, 2011  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Nagy I, Farkas J, Gyovai P, Radnai I, Szendrő Z. Stability of estimated breeding values for average daily gain in Pannon White rabbits. Czech J. Anim. Sci. 2011;56(8):365-369. doi: 10.17221/2398-CJAS.
Download citation

References

  1. Baselga M. (2004): Genetic improvement of meat rabbits. Programmes and diffusion. In: Proc. 8th World Rabbit Congr., Puebla, Mexico, 1-13.
  2. Farkas J. (2008): Analysis and comparison of complex breeding values estimation models for the Hungarian Pig breeding bases on the BLUP method. [Ph.D. Thesis.] Kaposvár, Kaposvár University. 191 pp. (in Hungarian)
  3. Garreau H., Szendrő Zs., Larzul C., De Rochambeau H. (2000): Genetic parameters and genetic trends of growth and litter size in the White Pannon breed. In: Proc. 7th World Rabbit Congr., Valencia, Spain, 403-408.
  4. Groeneveld E. (1990): PEST Users' Manual. Institute of Animal Husbandry and Animal Behaviour Federal Research Centre, Neustadt, Germany, 80 pp.
  5. Groeneveld E., Pescovicova D. (1999): Simultaneous estimation of the covariance structure of field and station test in Slovakian pig populations. Czech Journal of Animal Science, 44, 145-150.
  6. Kennedy B.W., Schaeffer L.R., Sorensen D.A. (1988): Genetic properties of animal models. Journal of Dairy Science, Supplement 2, 17-26. Go to original source...
  7. Kovac M., Groeneveld E. (2003): VCE-5 Users' Guide and Reference Manual Version 5.1. University of Ljubljana, Biotechnical Faculty, Department of Animal Science, Domzale, Slovenia, Institute of Animal Science Federal Agricultural Research Centre, Neustadt, Germany, 68 pp.
  8. Leclerc H., Fikse W.F., Ducrocq V. (2005): Principal components and factorial approaches for estimating genetic correlations in international sire evaluation. Journal of Dairy Science, 88, 3306-3315. Go to original source... Go to PubMed...
  9. Nagy I., Ibanez N., Mekkawy W., Metzger Sz., Horn P., Szendrő Zs. (2006): Genetic parameters of growth and in vivo computerized tomography based carcass traits in Pannon White rabbits. Livestock Science, 104, 46-52. Go to original source...
  10. SAS (2002-2003): SAS Statistical Analysis Software Version 9.1. SAS Institute Inc., Cary, NC, USA.
  11. Sorensen D.A., Kennedy B.W. (1988): The use of the relationship matrix to account for genetic drift variance in the analysis of genetic experiments. Theoretical and Applied Genetics, 66, 217-220. Go to original source... Go to PubMed...
  12. Szendrő Zs., Romvári R., Nagy, I. Andrássyné Baka G., Metzger Sz., Radnai I., Biró-Németh E., Szabó A., Vígh Zs., Horn P. (2004): Selection of Pannon White rabbits based on computerised tomograpgy. In: Proc. 8th World Rabbit Congr., Puebla, Mexico, 175-180.
  13. Wolf J., Pescovicova D., Groeneveld E. (2001): Stability of genetic parameter estimates for production traits in pigs. Journal of Animal Breeding and Genetics, 118, 161-172. Go to original source...
  14. Wolf J., ®áková E., Groeneveld E. (2005): Genetic parameters for a joint genetic evaluation of production and reproduction traits in pigs. Czech Journal of Animal Science, 50, 96-103. Go to original source...

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.