Effects of Number of Incomplete Data in Latest Generation on the Breeding Value Estimated by Random Regression Model

임의회귀 모형 사용시 마지막 세대의 불완전한 기록이 추정육종가에 미치는 효과

  • ;
  • ;
  • ;
  • ;
  • ;
  • ;
  • ;
  • ;
  • Salces, A.J. (National Livestock Research Institute, RDA, Korea) ;
  • 조광현 (축산연구소) ;
  • 나승환 (축산연구소) ;
  • 박병호 (축산연구소) ;
  • 최재관 (축산연구소) ;
  • 서강석 (축산연구소) ;
  • 이영창 (축산연구소) ;
  • 박종대 (축산연구소) ;
  • 손삼규 (축산연구소) ;
  • ;
  • 김시동 (축산연구소)
  • Published : 2006.04.30


The data were collected in the dairy herd improvement program from January 2000 to July 2005. Test data included 825,157 records of first parity and animals with both parents known were included. This study aimed to describe the effect of incomplete lactation records of latest generation to the change in sire's breeding value using Random Regression model (RRM) in genetic evaluation. Estimation of genetic parameter and breeding value for sire used REMLF90 and BLUPF90 program. The phenotypic value on the number of test day records between group TD11, TD8, TD5, TD2 showed no large differences. For all the group heritability of test day milk yield range from 0.30 to 0.36. However TD2 group showed low heritability the least test day recode on the latest generation. The correlation of above 50% between test day and TD11(0.610), TD8(0.616), TD5(0.661) and TD2(0.682) with different records in latest generation. Sire's rank of breeding value varied widely depending on the records on the number of lactation from start to the latest generation. Study showed that change in breeding value ranked if daughter's test recode more so it should have at least 5 test day records. The use of RRM in dairy cattle genetic evaluation would be desirable if complete lactation records for latest generation daughters of young bulls when selection for proven bulls. Random Regression model (RRM) require at least 5 test-day lactation recode.


Random regression model;Breeding value;Test day records


  1. Lee, D. H and Han, K. J. 2004. Genetic relationship between milk production, calving ease and days open at first parity in Holstein cows. Asian-Aust. J. Anim. Sci. Vol. 17, No.2: 153-158
  2. Interbull Bulletin 26. Wiggans, G. R. Issues In defining a genetic evaluation model
  3. Jamrozik and Schaeffer, L. R. 1997. Estimates of Genetic Parameters for a Test Day Model with Random Regressions for Yield Traits of First Lactation Holsteins. J. Dairy Sci. 80: 762-770
  4. Jamrozik Schaeffer, L. R. and Dekkers, J. C. M. 1997. Genetic Evaluation of Dairy Cattle Using Test Day Yields and Random Regression Model. J. Dairy Sci. 80: 1217-1226
  5. Lee, D. H., Jo, J. H. and Han, K. G. 2003. Genetic parameters for milk production and somatic cell score of forst lactation in Holstein cattle with random regression test-day models. Korean J. Anim. Sci. 45(5):739-748
  6. Macciotta, N. P. P., Vicario, D., Pulina, G. and Cappio-Borlino, A. 2002. Test Day and Lactation Yield Predictions in Italian Simmental Cows by ARMA Methods. J. Dairy Sci. 85: 3107-3114
  7. Misztal, I. 2001. BLUPPF90 family pakage.
  8. Miller, R. H., Norman, H. D., Wiggans, G. R. and Wright, J. R. 2004. Relationship of test-day somatic cell score with test-day lactation milk yields. J. Dairy Sci. 87: 2299-2306
  9. Pool, M. H. and Meuwissen. T. H. E. 1999. Prediction of dairy milk yields from a limited number of test days using test day models. J. Dairy Sci. 82:1555-1564
  10. Swalve, H. H. 2000. Theoretical basis and computational methods for different testday genetic evaluation methods. J. Dairy Sci. 83:1115-1124
  11. Schaeffer. L. R. and Dekkers. J. C. M. 1994. Random regressions in animal models for testday production on dairy cattle. Proc. 5th World Congress of Genetics Applied to Livestock Production. Guelph, Ontario, Canada X V III:443-446
  12. Wilmink, J. B. M. 1987. Adjustment of Test-day milk, fat, and protein yield for age, season and stage of lactation. Livest. Prod. Sci. 16, 335-348
  13. Reinhardt, F., Liu, Z., Benger, A., Dopp, L. and Reents, R. 2002. Impact of Application of a Random Regression Test-day Model to Production Trait Genetic Evaluations in Dairy Cattle. INTERBULL Bulletin No.29: 103-107