Lactation Persistency as a Component Trait of the Selection Index and Increase in Reliability by Using Single Nucleotide Polymorphism in Net Merit Defined as the First Five Lactation Milk Yields and Herd Life

  • Togashi, K. (Livestock Improvement Association in Japan) ;
  • Hagiya, K. (NARO Hokkaido Agricultural Research Center) ;
  • Osawa, T. (National Livestock Breeding Center) ;
  • Nakanishi, T. (National Livestock Breeding Center) ;
  • Yamazaki, T. (NARO Hokkaido Agricultural Research Center) ;
  • Nagamine, Y. (NARO Hokkaido Agricultural Research Center) ;
  • Lin, C.Y. (Dairy and Swine Research and Development Centre, Agriculture and Agri-Food Canada) ;
  • Matsumoto, S. (Livestock Improvement Association in Japan) ;
  • Aihara, M. (Livestock Improvement Association in Japan) ;
  • Hayasaka, K. (NARO Hokkaido Agricultural Research Center)
  • Received : 2012.01.04
  • Accepted : 2012.05.01
  • Published : 2012.08.01


We first sought to clarify the effects of discounted rate, survival rate, and lactation persistency as a component trait of the selection index on net merit, defined as the first five lactation milks and herd life (HL) weighted by 1 and 0.389 (currently used in Japan), respectively, in units of genetic standard deviation. Survival rate increased the relative economic importance of later lactation traits and the first five lactation milk yields during the first 120 months from the start of the breeding scheme. In contrast, reliabilities of the estimated breeding value (EBV) in later lactation traits are lower than those of earlier lactation traits. We then sought to clarify the effects of applying single nucleotide polymorphism (SNP) on net merit to improve the reliability of EBV of later lactation traits to maximize their increased economic importance due to increase in survival rate. Net merit, selection accuracy, and HL increased by adding lactation persistency to the selection index whose component traits were only milk yields. Lactation persistency of the second and (especially) third parities contributed to increasing HL while maintaining the first five lactation milk yields compared with the selection index whose only component traits were milk yields. A selection index comprising the first three lactation milk yields and persistency accounted for 99.4% of net merit derived from a selection index whose components were identical to those for net merit. We consider that the selection index comprising the first three lactation milk yields and persistency is a practical method for increasing lifetime milk yield in the absence of data regarding HL. Applying SNP to the second- and third-lactation traits and HL increased net merit and HL by maximizing the increased economic importance of later lactation traits, reducing the effect of first-lactation milk yield on HL (genetic correlation ($r_G$) = -0.006), and by augmenting the effects of the second- and third-lactation milk yields on HL ($r_G$ = 0.118 and 0.257, respectively).


  1. Allaire, F. R. and J. P. Gibson. 1992. Genetic value of herd life adjusted for milk production. J. Dairy Sci. 75:1349-1356.
  2. Burnside, E. B., A. E. McClintock and K. Hammond. 1984. Type, production, and longevity in dairy cattle: a review. Anim. Breed. Abstr. 57:711-719.
  3. Dekkers, J. C. M. 1994. Theoretical basis for genetic parameters of herd life and effects on response to selection. J. Dairy Sci. 76:1433-1443.
  4. Dekkers, J. C. M., J. H. Ten Haag and A. Weersink. 1998. Economic aspects of persistency of lactation in dairy cattle. Livest. Prod. Sci. 53:237-252.
  5. Groen, A. F., J. Aumann, V. Ducrocq, N. Gengler, J. Soelkner and E. Strandberg. 1998. Genetic improvement of functional traits in cattle (GIFT)-An intermediate report. Interbull. 17:81-82.
  6. Hagiya, K., T. Oosawa and T. Nakanishi. 2010. The parameter estimation of lactation persistency. The Research Note of the National Livestock Breeding Center. Nishishirakawa Gun, Fukushima, Japan.
  7. Hill,W. G. 1971. Investment appraisal for national breeding programs. Anim. Prod. 13:37-50.
  8. Jakobsen, J. H. 2000. Genetic correlations between the shape of the lactation curve and disease resistance in diary cattle. Ph.D. Thesis, Department of Animal Breeding and Genetics, Danish Institute of Agricultural Science, Research Centre, Foulum, Denmark.
  9. Jagannatha, S., J. F. Keown and L. D. van Vleck. 1998. Estimation of relative economic value for herd life of dairy cattle from profile equations. J. Dairy Sci. 81:1702-1708.
  10. MAFF. 2011. Report of improvement of animals. Tokyo, Japan.
  11. NLBC and LIAJ. 2010. Dairy bull evaluation results 2010-1.Tokyo, Japan.
  12. Rupp, R., F. Beaudeau and D. Boichard. 2000. Relationship between milk somatic cell counts in first lactation and clinical mastitis occurrence in the second lactation of French Holstein cows. Prev. Vet. Med. 46:99-111.
  13. Smith, S. P. and R. L. Quaas. 1984. Productive lifespan of bull progeny groups: failure time analysis. J. Dairy Sci. 72:2999-3007.
  14. Solkner, J. and W. Fuchs. 1987. A comparison of different measures of persistency with special respect to variation of test-day milk yields. Livest. Prod. Sci. 16:305-319.
  15. Togashi, K., C. Y. Lin, Y. Atagi, K. Hagiya, J. Sato and T. Nakanishi. 2008. Genetic characteristics of Japanese Holstein cows based on multiple lactation random regression test-day animal models. Livest. Sci. 114:194-2008.
  16. Togashi, K., C.Y. Lin and T. Yamazaki. 2011. The efficiency of genome-wide selection for genetic improvement of net merit. J. Anim. Sci. 89:2972-2980.
  17. Tsuruta, S., I. Misztal and T. J. Lawlor. 2004. Genetic correlations among production, body size, udder, and productive life traits over time in Holsteins. J. Dairy Sci. 87:1457-1468.
  18. Van Arendonk, J. A. M. 1991. Use of profit equations to determine relative economic value of dairy cattle herd life and production from field data. J. Dairy Sci. 74:1101-1107.
  19. Van Raden, P. M. and G. R.Wiggans. 1995. Productive life evaluations: calculation, accuracy, and economic value. J. Dairy Sci. 78:631-638.
  20. Van Raden, P. M., C. P. Van Tassell, G. R. Wiggans, T. S. Sonstegard, R. D. Schnabel, J. F. Taylor and F. S. Schenkel. 2009. Invited review: Reliability of genomic predictions for North American Holstein bulls. J. Dairy Sci. 92:16-24.
  21. Weigel, D. J., B. G. Cassel and R. E. Pearson. 1995. Adjustment of a net income function for opportunity cost of postponed replacement on a lactation basis. J. Dairy Sci.78:648-654.
  22. Weller, J. I. 1994. Economic Aspects of Animal Breeding. Chapman and Hall, London, UK. p. 244.
  23. Weller, J. I. and M. Ron. 1992. Genetic analysis of fertility traits in Israeli Holsteins by linear and threshold models. J. Dairy Sci. 75:2541-2548.
  24. Weller, J. I., E. Ezra and G. Leitner. 2006. Genetic analysis of persistency in the Israeli Holstein population by the multi-trait animal model. J. Dairy Sci. 89:2738-2746.
  25. Weller, J. I., H. D. Norman and G. R. Wiggans. 1984. Weighting sire evaluations on different parities to estimate overall merit. J. Dairy Sci. 67:1030-1037.
  26. Yamazaki, T., H. Takeda, A. Nishiura and K. Togashi. 2009. Relationship between the lactation curve and udder disease incidence in different lactation stages in first lactation Holstein cows. Anim. Sci. J. 80:636-643.
  27. Zimmermann, E. and H. Sommer. 1973. Zum Laktationsverlauf von Kuhen in Hochleistung-sherden und dessen Beeinflussung durch nichterbliche Faktoren. Zuchtungskunde. 45:75-88.