Comparison of different legendre and B-spline random regression models to estimate variance components for average birth weight per lambing in Mehraban sheep

Document Type : Research Paper

Authors

1 Associate Professor, Department of Animal Science, Bu-Ali Sina University, Hamedan, Iran

2 Former M. Sc. Student, Department of Animal Science, Bu-Ali Sina University, Hamedan, Iran

3 Assistant Professor, Department of Animal Science, Bu-Ali Sina University, Hamedan, Iran

Abstract

The present study was carried out to compare different random regression models to estimate variance components of lamb's average birth weight per lambing (ABWLL) in Mehraban sheep. The data were 5,559 ABWLL records of 2,244 Mehraban ewes. The random regression models consisted of namely, flock-year-season of lambing as fixed effect, a fixed regression to fit average trajectory of the population and two random regressions to fit random additive genetic and permanent environmental effects. The models had linear and quadratic B-Spline or quadratic or cubic Legendre functions, all with heterogeneous residual variances. Variance components were estimated using Average Information algorithm of Restricted Maximum Likelihood (AI-REML). According to Akaike and Bayesian information criteria, the model BS212 with quadratic, linear and quadratic B-Spline functions for fixed regression and random regressions of additive genetic and permanent environment was considered as the best model to fit the data. Using the BS212 model, the highest and lowest heritabilities for ABWLL were estimated for 12 months of age (0.74) and 31 to 66 months of the ewe age (0.03), respectively and coefficients of permanent environment were close to 0 in all ages. The estimated values in middle ages were more accurate than initial or final ages. The results of the present study showed that the records obtained on initial lambings probably could have higher importance for breeding programs.

Keywords

References

  1. Akaike, H. (1974). A new look at the statistical model identification. IRRR Transactions on Automatic Control, 19, 716-723.
  2. Amirabadi Farahani, M. & Zamani, P. (2013). Genetic analysis of number of lambs born per lambing of  in Mehraban breed ewes, using B-spline random regression models. Iranian Journal of Animal Science, 44, 113-120. (In Farsi)
  3. Falaki-Moghaddam, H. (2012). Estimation of variance components for composite reproduction traits in Moghani sheep using repeatability and random regression models. M.Sc. thesis. Faculty of Agriculture. Department of Animal Science. Bu-Ali Sina University. (In Farsi).
  4. Fischer, T. M., Van der Werf, J. H. J., Banks, R. G. & Ball, A. J. (2004). Description of lamb growth using random regression on field data. Livestock Production Science, 89, 175-185.
  5. Lewis, R. M. & Brotherstone, S. (2002). A genetic evaluation of growth in sheep using random regression techniques. Animal Science, 74, 63-70.
  6. Luković, Z., Malovrh, S., Gorjanc, G. & Kovač, M. (2004). A random regression model in analysis of litter size in pigs. South African Journal of Animal Science, 34, 241-248.
  7. Meyer, K. (2005). Estimates of genetic covariance functions for growth of Angus cattle. Journal of Animal Breeding and Genetics, 122, 73-85.
  8. Meyer, K. (2007). Wombat - A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML). Journal of Zhejiang University Science B, 8, 815-821.
  9. Mokhtari, M. S., Rashidi, A. & Esmailizadeh, A. K. (2010). Estimation of phenotypic and genetic parameters for reproductive traits in Kermani sheep. Small Ruminant Research, 88, 27-31.
  10. Mostret, B. E., Theron, H. E., Kanfer, F. H. J. & Van Marle-Koster, E. (2006). Test- day models for South African dairy cattle for participation in international evaluations. South African Journal of Animal Science, 36, 58-70.
  11. Oliveira, K. A. P., Lôbo, R. N. B. & Facó, O. (2010). Genetic evaluation of partial growth trajectory of Santa Inês breed using random regression models. Revista Brasileira de Zootecnia, 39, 1029-1036.
  12. Pezhman, L. & Zamani, P. (2012). Estimation of variance components and genetic parameters for some of reproductive traits in Mehraban sheep, using univariate animal models. Animal Science Researches, 22, 27-35. (In Farsi)
  13. Rosati, A., Mousa, E., Van Vleck, L. D. &Young, L. D. (2002). Genetic parameters of reproductive traits in sheep. Small Ruminant Research, 43, 65-74.
  14. SAS Institute. (2004). User’s Guide Version 9.1: Statistics. SAS Institute. Cary. NC.
  15. Schaeffer, L. R. (2004). Application of random regression models in animal breeding. Livestock Production Science, 86, 35-45.
  16. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464.
  17. Vatankhah, M. (2013). Genetic analysis of ewe body weight in Lori-Bakhtiari sheep using random regression models. Journal of Livestock Science and Technologies, 1, 44-49.
  18. Vatankhah, M., Talebi, M. A. & Edriss, M. A. (2008). Estimation of genetic parameters for reproductive traits in Lori – Bakhtiari sheep. Small Ruminant Research, 74, 216-220.
  19. Veerkamp, R. F., Koenen, E. P. C. & De Jong, G. (2001). Genetic correlations among body condition score, yield and fertility in first-parity cows estimated by random regression models. Journal of Dairy Science, 84, 2327-2335.
  20. Zamani, P., Moradi, M. R., Alipour, D. & Ahmadi, A. (2015). Estimation of variance components for body weight of Moghani sheep using B-Spline random regression models. Iranian Journal of Applied Animal Science. (In press)
Iranian Journal of animal Science
Volume 46, Issue 4 - Serial Number 4
January 2016
Pages 407-415

Files

History

  • Receive Date: 17 February 2015
  • Revise Date: 11 December 2015
  • Accept Date: 12 December 2015

Share

How to cite

Statistics