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Genetic Evaluation and Calculating Daughter Yield Deviation of Bulls in Iranian Holstein Cattle for Milk and Fat Yields
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 Title & Authors
Genetic Evaluation and Calculating Daughter Yield Deviation of Bulls in Iranian Holstein Cattle for Milk and Fat Yields
Sheikhloo, M.; Shodja, J.; Pirany, N.; Alijani, S.; Sayadnejad, M.B.;
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 Abstract
This study was aimed at a genetic evaluation of Iranian Holstein cattle for milk and fat yields and calculating daughter yield deviation (DYD) of bulls. The data file that was used in this research included 367,943 first three lactation records of 186,064 Holstein cows which calved between 1983 and 2006 in 11,806 herd-year-season groups. The model included herd-year-season of calving and age at calving as fixed effects and animal and permanent environment as random effects. Mean breeding values of cows for each year were regressed on birth year to estimate genetic trends. Genetic trends in milk and fat yields were greater for cows born after 1997 (59.38 kg/yr and 1.11 kg/yr for milk yield and fat yield, respectively). Animal evaluations were partitioned into contribution from parent average, yield deviation (YD) and progeny. DYD of bulls was calculated as described by VanRaden and Wiggans (1991). DYD provides an indication of the performance of the daughters of a bull without consideration of his parents or sons. Variance of bull DYD was greater than variance of their predicted transmitting ability (PTA). Correlation of bull DYD and PTA was dependent on the number of daughters and when this increased, the correlation of DYD and PTA was increased. Also as lactation number of daughters increased, the correlation of bull DYD and PTA was increased.
 Keywords
Daughter Yield Deviation;Genetic Evaluation;Genetic Trend;Holstein Cows;
 Language
English
 Cited by
 References
1.
Bhatti, A. A., M. S. Khan, Z. Rehman, A. U. Heyder and F. Hassan. 2007. Selection of Sahiwal cattle bulls on pedigree and progeny. Asian-Aust. J. Anim. Sci. 20(1):12-18

2.
Boichard, D., B. Bonaiti, A. Barbat and S. Mattalia. 1995. Three methods to validate the estimation of genetic trend for dairy cattle. J. Dairy Sci. 78:431-437 crossref(new window)

3.
Dadpasand, M. 2002. Estimation of genetic trend for yield traits of Iranian Holstein cattle. MSc Thesis, University of Tehran, Iran

4.
Ducrocq, V., I. Delaunay, D. Boichard and S. Mattalia. 2003. A general approach for international genetic evaluations robust to inconsistencies of genetic trends in national evaluations. Interbull Bulletin 30:101-111

5.
Farhangfar, H. and H. Naeimipoor. 2005. Estimation of genetic and phenotypic parameters for 305-day yield and reproductive traits in Iranian Holsteins. J. Sci. Technol. Agric. Nat. Resour. 11:431-440

6.
Freyer, G., C. Stricker and C. Kuhn. 2002. Comparison of estimated breeding values and daughter yield deviations used in segregation and linkage analyses. Czech J. Anim. Sci. 47:247-252

7.
Johnson, D. L. and R. Thompson. 1995. Restricted maximum likelihood estimation of variance components for univariate animal models using sparse matrix techniques and average information. J. Dairy Sci. 78:449-456 crossref(new window)

8.
Jorjani, H., J. Philipsson and J. Mocquot. 2001. Interbull guidelines for national and international genetic evaluation systems in dairy cattle with focus on production traits. Interbull Centre

9.
Kim, J. J. and M. Georges. 2002. Evaluation of a new finemapping method exploiting linkage disequilibrium: a case study analysing a QTL with major Effect on milk composition on bovine chromosome 14. Asian-Aust. J. Anim. Sci. 15(9):1250-1256

10.
Kim, J. J. 2008. Detection of QTL on bovine X chromosome by exploiting linkage disequilibrium. Asian-Aust. J. Anim. Sci. 21(5):617-623

11.
Kolbehdari, D. 1993. Estimation of genetic trend for milk yield in a herd of Holstein cattle. MSc Thesis, University of Tehran, Iran

12.
Lee, C. 2000. Methods and techniques for variance component estimation in animal breeding. Asian-Aust. J. Anim. Sci. 13(3):413-422

13.
Liu, Z., F. Reinhardt, A. Bunger and R. Reents. 2004. Derivation and calculation of approximate reliabilities and daughter yielddeviations of a random regression test-day model for genetic evaluation of dairy cattle. J. Dairy Sci. 87:1896-1907 crossref(new window)

14.
Meyer, K. 2006. WOMBAT - Digging deep for quantitative genetic analysis by restricted maximum likelihood. 8th WCGALP, Belo Horizonte, August 13-18, Communication 27

15.
Meyer, K. 2007. WOMBAT, version1.0. UserNotes. Available http://agbu.une.edu.au /~kmeyer/wombat.html

16.
Mrode, R. A. and G. J. T. Swanson. 2002. The calculation of cow and daughter yield deviations and partitioning of genetic evaluations when using a random regression model. in Proc. 7 WCGALP, Communication #01-04, Montpellier, France. pp. 51-54

17.
Mrode, R. A. 2005. Linear models for the prediction of animal breeding values. CAB International

18.
Naeimipoor, H. 2004. Estimates of phenotypic and genetic trend for milk yield of Holstein cattles in Khorasan province of Iran. MSc Thesis, University of Zabol, Iran

19.
Nazari, B. M., R. Vaez-Torshizi, M. Moradi-Shahrebabak and M. B. Sayadnejad. 2003. Estimation of genetic parameters of milk production and reproduction traits in Iranian Holsteins. Proceedings of The First Seminar on Genetic and Breeding Applied to Livestock, Poultry and Aquatics, University of Tehran, Iran, pp. 99-105

20.
Safi-Jahanshahi, A., R. Vaez-Torshizi, N. Emam-Jomeh-Kashan and M. B. Sayadnejad. 2003. Estimates of genetic parameters of milk production traits for Iranian Holsteins, Using Different animal models. Proceedings of The First Seminar on Genetic and Breeding Applied to Livestock, Poultry and Aquatics, University of Tehran, Iran, pp. 40-46

21.
Schaeffer, L. R. 1994. Multiple-Country comparison of dairy sires. J. Dairy Sci. 77:2671-2678 crossref(new window)

22.
Shadparvar, A. A. and M. S. Yazdanshenas. 2005. Genetic parameters of milk yield and milk fat percentage test day records of Iranian Holstein cows. Asian-Aust. J. Anim. Sci. 18(9):1231-1236

23.
Szyda, J., Z. Liu, R. Maschka, F. Reinhardt and R. Reents. 2002. Computer system for routine QTL detection and genetic evaluation under a mixed inheritance model in dairy cattle. in Proc. 7 WCGALP, Communication #28-10, Montpellier, France. pp. 749-750

24.
VanRaden, P. M. and G. R Wiggans. 1991. Derivation, calculation, and use of national animal model Information. J. Dairy Sci. 74:2737-2746 crossref(new window)

25.
Vierhout, C. N., B. G. Cassell and R. E. Pearson. 1998. Influences of progeny test programs on genetic evaluations of young sires. J. Dairy Sci. 81:2524-2532 crossref(new window)

26.
Visscher, P. M. and R. Thompson. 1992. Univariate and multivariate parameter estimates for milk production traits using an animal model. I. Description and results of REML analyses. Genet. Sel. Evol. 24:415-430 crossref(new window)

27.
Weigel, K. A., R. Rekaya, N. R. Zwald and W. F. Fikse. 2001. International genetic evaluation of dairy sires using a multipletrait model with individual animal performance records. J. Dairy Sci. 84:2789-2795 crossref(new window)

28.
Weller, J. I., Y. Kashi and M. Soller. 1990. Power of daughter and granddaughter designs for determining linkage between marker loci and quantitative trait loci in dairy cattle. J. Dairy Sci. 73:2525-2537

29.
Weller, J. I. 2001. Quantitative trait loci analysis in animals. CAB International, UK