Development of Algorithm in Analysis of Single Trait Animal Model for Genetic Evaluation of Hanwoo

단형질 개체모형을 이용한 한우 육종가 추정프로그램 개발

  • Koo, Yangmo (Korea Animal Improvement Association) ;
  • Kim, Jungil (Korea Animal Improvement Association) ;
  • Song, Chieun (Korea Animal Improvement Association) ;
  • Lee, Kihwan (Korea Animal Improvement Association) ;
  • Shin, Jaeyoung (Korea Animal Improvement Association) ;
  • Jang, Hyungi (Korea Animal Improvement Association) ;
  • Choi, Taejeong (National Institute of Animal Science, RDA) ;
  • Kim, Sidong (National Institute of Animal Science, RDA) ;
  • Park, Byoungho (National Institute of Animal Science, RDA) ;
  • Cho, Kwanghyun (National Institute of Animal Science, RDA) ;
  • Lee, Seungsoo (National Institute of Animal Science, RDA) ;
  • Choy, Yunho (National Institute of Animal Science, RDA) ;
  • Kim, Byeongwoo (Divison of Applied Life Science.Institute of Agriculture & Life Sciences, GyeongSang National University) ;
  • Lee, Junggyu (Divison of Applied Life Science.Institute of Agriculture & Life Sciences, GyeongSang National University) ;
  • Song, Hoon (HoonSong Enterprises 2305 Fox Crescent)
  • Received : 2013.04.22
  • Accepted : 2013.07.11
  • Published : 2013.10.31


Estimate breeding value can be used as single trait animal model was developed directly using the Fortran language program. The program is based on data computed by using the indirect method repeatedly. The program develops a common algorithm and imprves efficiency. Algorithm efficiency was compared between the two programs. Estimated using the solution is easy to farm and brand the service, pedigree data base was associated with the development of an improved system. The existing program that uses the single trait animal model and the comparative analysis of efficiency is weak because the estimation of the solution and the conventional algorithm programmed through regular formulation involve many repetition; therefore, the newly developed algorithm was conducted to improve speed by reducing the repetition. Single trait animal model was used to analyze Gauss-Seidel iteration method, and the aforesaid two algorithms were compared thorough the mixed model equation which is used the most commonly in estimating the current breeding value by applying the procedures such as the preparation of information necessary for modelling, removal of duplicative data, verifying the parent information of based population in the pedigree data, and assigning sequential numbers, etc. The existing conventional algorithm is the method for reading and recording the data by utilizing the successive repetitive sentences, while new algorithm is the method for directly generating the left hand side for estimation based on effect. Two programs were developed to ensure the accurate evaluation. BLUPF90 and MTDFREML were compared using the estimated solution. In relation to the pearson and spearman correlation, the estimated breeding value correlation coefficients were highest among all traits over 99.5%. Depending on the breeding value of the high correlation in Model I and Model II, accurate evaluation can be found. The number of iteration to convergence was 2,568 in Model I and 1,038 in Model II. The speed of solving was 256.008 seconds in Model I and 235.729 seconds in Model II. Model II had a speed of approximately 10% more than Model I. Therefore, it is considered to be much more effective to analyze large data through the improved algorithm than the existing method. If the corresponding program is systemized and utilized for the consulting of farm and industrial services, it would make contribution to the early selection of individual, shorten the generation, and cultivation of superior groups, and help develop the Hanwoo industry further through the improvement of breeding value based enhancement, ultimately paving the way for the country to evolve into an advanced livestock country.


Single trait animal model;Gauss-Seidel iteration;Indirect method


  1. Boldman, K. G., Kriese, L. A, Van Vleck, L. D. and Kachman, S. D. 1993. A manual for use of MTDFREML USDA-ARS, Clay Center, Nebraska.
  2. Henderson, C. R. 1974. Rapid Method for Computing the Inverse of a Relationship Matrix. J. Dairy Sci. 58:1727-1730.
  3. Koo, Y. M. 2010. Research on the Development of the Genetic Evaluation System on Hanwoo Carcass Traits. Ph. D. thesis, GyeongSang National University.
  4. Misztal, I. 1986. Survey of some computing methods in BLUP sire evaluation. Mixed-model applications and analysis, a workshop on the interface of practice and theory, April 6-8, Irsee, Germany. Inst. Math. Univ. Augsberg, FRG.
  5. Misztal, I., Gianola, D. and Schaeffer, L. R. 1987. Extrapolation and convergence criteria with Jacobi and Gauss-Seidel iteration in animal models. J. Dairy Sci. 70, 2577-2584.
  6. Misztal, I. 2007. BLUPF90 family of programs. University of Georgia. Accessed Jan. 2, 2007.
  7. Misztal, I. 2008. Computational Techniques in Animal Breeding. Course Notes. University of Georgia.
  8. Schaeffer, L. R. and Kennedy, B. W. 1986a. Computing solutions to mixed model equations. proc. Third World Congr. Genet. Appl. Livest. Prod., Lincoln, NE. July 16, 1986, 12:382.
  9. Schaeffer, L. R. and Kennedy, B. W. 1986b. Computing strategies for solving mixed model equations. J. Dairy Sci. 69:575.
  10. Sorensen, D. A. and Kennedy, B. W. 1984. Estimation of Response to Selection Using Least-Squares and Mixed Model Methodology. J. Anim. Sci. 58:1097-1106.
  11. Van Vleck, L. D. and Dwyer, D. J. 1985. Comparison of iterative procedures for solving equations for sire evaluation. J. Dairy Sci. 68:1006.