Browse > Article
http://dx.doi.org/10.5713/ajas.2009.80378

Genetic Evaluation and Calculating Daughter Yield Deviation of Bulls in Iranian Holstein Cattle for Milk and Fat Yields  

Sheikhloo, M. (Department of Animal Science, University of Tabriz)
Shodja, J. (Department of Animal Science, University of Tabriz)
Pirany, N. (Department of Animal Science, University of Tabriz)
Alijani, S. (Department of Animal Science, University of Tabriz)
Sayadnejad, M.B. (Animal Breeding Center, Ministry of agriculture)
Publication Information
Asian-Australasian Journal of Animal Sciences / v.22, no.5, 2009 , pp. 611-617 More about this Journal
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;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
Times Cited By Web Of Science : 0  (Related Records In Web of Science)
Times Cited By SCOPUS : 0
연도 인용수 순위
1 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   DOI   ScienceOn
2 Kim, J. J. 2008. Detection of QTL on bovine X chromosome by exploiting linkage disequilibrium. Asian-Aust. J. Anim. Sci. 21(5):617-623
3 Meyer, K. 2006. WOMBAT - Digging deep for quantitative genetic analysis by restricted maximum likelihood. 8th WCGALP, Belo Horizonte, August 13-18, Communication 27
4 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
5 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   DOI   ScienceOn
6 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
7 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
8 VanRaden, P. M. and G. R Wiggans. 1991. Derivation, calculation, and use of national animal model Information. J. Dairy Sci. 74:2737-2746   DOI   ScienceOn
9 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
10 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
11 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   DOI   ScienceOn
12 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
13 Schaeffer, L. R. 1994. Multiple-Country comparison of dairy sires. J. Dairy Sci. 77:2671-2678   DOI   PUBMED   ScienceOn
14 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
15 Weller, J. I. 2001. Quantitative trait loci analysis in animals. CAB International, UK
16 Dadpasand, M. 2002. Estimation of genetic trend for yield traits of Iranian Holstein cattle. MSc Thesis, University of Tehran, Iran
17 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
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 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   DOI   PUBMED   ScienceOn
20 Meyer, K. 2007. WOMBAT, version1.0. UserNotes. Available http://agbu.une.edu.au /~kmeyer/wombat.html
21 Mrode, R. A. 2005. Linear models for the prediction of animal breeding values. CAB International
22 Lee, C. 2000. Methods and techniques for variance component estimation in animal breeding. Asian-Aust. J. Anim. Sci. 13(3):413-422
23 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   DOI
24 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   DOI   ScienceOn
25 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
26 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   DOI   ScienceOn
27 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
28 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
29 Kolbehdari, D. 1993. Estimation of genetic trend for milk yield in a herd of Holstein cattle. MSc Thesis, University of Tehran, Iran