Theoretical basis and computational methods for different test-day genetic evaluation methods

Journal of Dairy Science

Volumn 83, Issue 5, 2000, Pages 1115-1124

  Swalve, H H ^a,b  

^a UNIVERSITY OF GÖTTINGEN   (Germany)

^b Res Intitute Biol Farm A   (Germany)

Author keywords

Computational methods; Genetic evaluation; Test day model

Indexed keywords

ANIMAL; BIOLOGICAL MODEL; CATTLE; ENVIRONMENT; FEMALE; GENETIC VARIABILITY; GENETICS; INFORMATION PROCESSING; LACTATION; REGRESSION ANALYSIS; REVIEW; STATISTICAL MODEL; TIME;

ANIMALS; CATTLE; ENVIRONMENT; FEMALE; LACTATION; MODELS, BIOLOGICAL; MODELS, STATISTICAL; RECORDS; REGRESSION ANALYSIS; TIME FACTORS; VARIATION (GENETICS);

EID: 0034181630     PISSN: 00220302     EISSN: None     Source Type: Journal    
DOI: 10.3168/jds.S0022-0302(00)74977-0     Document Type: Article

References (68)

1. ABC. 1999. AI Bull Census, Animal Breeding Cornell, http:// www.abc.cornell.edu/abc/siretabs/about.html (accessed June 1999).
2. Ali, T. E., and L. R. Schaaeffer. 1987. Accounting for covariances among test day milk yields in dairy cows. Can. J. Anim. Sci. 67:637-644.
3. Arnason, T. 1983. Prediction of breeding values in horses by the BLUP method. 34th Annu. Meeting EAAP, Madrid, Spain. Abstract book.
4. Beard, K. 1983. Prediction of total lactation yield in dairy cows. M.S. thesis, University of Melbourne, Victoria, Australia.
5. Burnside, E. B., and K. Meyer. 1989. Potential impact of bovine somatotropin on dairy sire evaluation. J. Dairy Sci. 71:2210-2219.
6. Colleau, J. J. 1989. Impact of the use of bovine somatotropin (BST) on dairy cattle selection. Genet. Sel. Evol. 21:479-491.
7. Danell, B. 1990. Genetic aspects of different parts of lactation. Proc. 4th World Congr. Genet. Appl. Livest. Prod., Edinburgh, Scotland XIII:114-117.
8. 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.
9. Ducrocq, V. P., and B. Besbes. 1993. Solution of multiple trait animal models with missing data on some traits. J. Anim. Breed. Genet. 110:81-92.
10. Elston, D. A., C. A. Glasbey, and D. R. Neilson. 1989. Nonparametric lactation curves. Anim. Prod. 48:331-339.
11. Everett, R. W., F. Schmitz, and L. H. Wadell. 1994. A test-day model for monitoring management and genetics in dairy cattle (Abstr.). J. Dairy Sci. 77(Suppl. 1):267.
12. Gengler, N., A. Tijani, and G. R. Wiggans. 1999. Iterative solution of random regression models by sequential estimation of regressions and effects on regressions. Pages 93-102 in Proc. Computational Cattle Breeding '99. Tuusula, Finland. Interbull Bull. No. 20, International Bull Evaluation Service, Uppsala, Sweden.
13. Groeneveld, E. 1990. PEST User's manual. FAL, Mariensee, Germany.
14. Grossman, M., and W. J. Koops. 1988. Multiphasic analysis of lactation curves in dairy cattle. J. Dairy Sci. 71:1598-1608.
15. Gruenhagen, E., and H. H. Swalve. 1997. Effect of cell size in test day models. Proc. Interbull Mtg., Vienna, Austria, International Bull Evaluation Service, Uppsala, Sweden, Interbull Bull. No. 16:66-70.
16. Guo, Z. 1998. Modelle zur Beschreibung der Laktationskurve des Milchrindes und ihre Verwendung in Modellen zur Zuchtwertschätzung (Models for the description of lactation curves in dairy cattle and their use in models for genetic evaluation). Ph.D. thesis, University of Goettingen, Germany.
17. Guo, Z., and H. H. Swalve. 1995. Modelling of the lactation curve as a sub-model in the evaluation of test day records. Proc. Interbull Mtg. Prague, International Bull Evaluation Service, Uppsala, Sweden. Interbull Bull. No. 11.
18. Guo, Z., and H. H. Swalve. 1997. Modeling the lactation curve with interpolation and B-Splines. Proc. 48th Ann. Mtg. EAAP, Vienna, Austria. Abstract book.
19. Guo, Z., and H. H. Swalve. 1997. Comparison of different lactation curve sub-models in test day models. Interbull Mtg. Vienna, International Bull Evaluation Service, Uppsala, Sweden. Interbull Bull. No. 16:75-79.
20. Henderson, C. R. 1984. Applications of linear models in animal breeding. University of Guelph, Guelph, Ontario, Canada.
21. Henderson, C. R., Jr. 1982. Analysis of covariance in the mixed model: higher level, nonhomgeneous, and random regressions. Biometrics 38:623-640.
22. Jamrozik, J., G. Jansen, L. R. Schaeffer, and Z. Liu. 1998. Analysis of persistency of lactation calculated from a random regression test day model. Proc. Interbull Mtg. Rotorua, International Bull Evaluation Service, Uppsala, Sweden, Interbull Bull. No. 17:64-69.
23. Jamrozik, J., G. J. Kistemaker, J.C.M. Dekkers, and L. R. Schaeffer. 1997. Comparison of possible covariates for use in a random regression model for analysis of test day yields. J. Dairy Sci. 80:2250-2556.
24. Jamrozik, J., and L. R. Schaeffer. 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.
25. Jamrozik, J., L. R. Schaeffer, and J.C.M. Dekkers. 1996. Random regression models for production traits in Canadian Holsteins. Proc. Interbull Mtg. Veldoven, International Bull Evaluation Service, Uppsala, Interbull Bull. No. 14:124-134.
26. Jamrozik, J., L. R. Schaeffer, and J.C.M. Dekkers. 1997. Genetic evaluation of dairy cattle using test day yields and random regression models. J. Dairy Sci. 80:1217-1226.
27. Jamrozik, J., L. R. Schaeffer, Z. Liu, and G. Jansen. 1997. Multiple trait random regression test day model for production traits. Interbull Mtg. Vienna, International Bull Evaluation Service, Uppsala, Sweden. Interbull Bull. No. 16:43-47.
28. Johnson, D. L. 1996. Estimation of lactation yield from repeated measure of test day yields. Proc. N.Z. Soc. Anim. Prod. 56:16-18.
29. Jones, L. P. 1985. Australian breeding values for production characters. Pages 242-247 in Proc. Australian Assoc. Anim. Breed. Genet., 5. Conf., Sydney, Australia.
30. Jones, L. P., and M. E. Goddard. 1990. Five years experience with the animal model for dairy evaluations in Australia. Proc. 4th World Congr. Genet. Appl. Livest. Prod., Edinburgh, Scotland XIII:382-385.
31. Kachman, S. D., and R. W. Everett. 1989. Test day data model with individual herd correction factors. J. Dairy Sci. 72(Suppl. 1):60.(Abstr.)
32. Kettunen, A., E. A. Mäntysaari, I. Strandén, J. Pösö, and M. Lidauer. 1998. Estimation of genetic parameters for first lactation milk production using random regression models. Proc. 6th World Congr. Genet. Appl. Livest. Prod., Armidale, New South Wales, Australia 23:307-310.
33. Kirkpatrick, M., W. G. Hill, and R. Thompson. 1994. Estimating the covariance structure of traits during growth and ageing, illustrated with lactations in dairy cattle. Gent. Res. 64:57-69.
34. Kirkpatrick, M., D. Lofsvold, and M. Bulmer. 1990. Analysis of the inheritance, selection, and evolution of growth trajectories. Genetics 124:979-993.
35. Kuhn, M. T., A. E. Freeman, and R. L. Fernando. 1999. Approaches investigated to correct for preferential treatment. J. Dairy Sci. 82:181-190.
36. Lidauer, M., and I. Strandén. 1999. Fast and flexible program for genetic evaluation in dairy cattle. Pages 26-32 in Proc. Computational Cattle Breeding '99. Tuusula. Finland. Interbull Bull. No. 20, International Bull Evaluation Service, Uppsala, Sweden.
37. Liu, Z., J. Jamrozik, and G. Jansen. 1998. A comparison of fixed and random regression models applied to dairy test day production data. Proc. Interbull Mtg. Rotorua, International Bull Evaluation Service, Uppsala, Sweden, Interbull Bull. No. 17:60-63.
38. Masselin, S., D. Sauvant, P. Chapoutot, and D. Milan. 1987. Les modèles d'ajustement des courbes de lactation. Ann. Zootech. 36:171-206.
39. Meyer, K., and W. G. Hill. 1997. Estimation of genetic and phenotypic covariance functions for longitudinal or 'repeated' records by restricted maximum likelihood. Livest. Prod. Sci. 47:185-200.
40. Meyer, K., H.-U. Graser, and S. P. Smith. 1987. Estimation of adjustment factors and variance components for test-day production in Australian Black and White populations. Summary report to ADHIS on analysis of production records conducted by AGBU during 1985-1987. Compiled by H.-U. Graser. AGBU, UNE, Armidale, Australia.
41. Misztal, I. 2000. Strategies for estimating the parameters needed for different test-day models. J. Dairy Sci. 83:1125-1134.
42. Misztal, I., and D. Gianola. 1987. Indirect solution of mixed model equations. J. Dairy Sci. 70:716-723.
43. Misztal, I., D. Gianola, and L. R. Schaeffer. 1987. Extrapolation and convergence criteria with Jacobi and Gauss-Seidel iteration in animal models. J. Dairy Sci. 70:2577-2584.
44. Nicholas, F. W. and C. Smith. 1983. Increased rate of genetic change in dairy cattle by embryo-transfer and splitting. Anim. Prod. 36:341-353.
45. Olori, V. E. 1997. Utilisation of daily milk records in genetic evaluation of dairy cattle. Ph.D. thesis, University of Edinburgh, Edinburgh, Scotland.
46. Pander, B. L., W. G. Hill, and R. Thompson. 1992. Genetic parameters of test day records of British Holstein-Friesian heifers. Anim. Prod. 55:11-21.
47. Ptak, E., and L. R. Schaeffer. 1993. Use of test day yields for genetic evaluation of dairy sires and cows. Livest. Prod. Sci. 34:23-34.
48. Reents, R., J.C.M. Dekkers, and L. R. Schaeffer. 1995. Genetic evaluation for somatic cell score with a multiple lactation test day model. J. Dairy Sci. 78:2858-2870.
49. Reents, R., J. Jamrozik, L. R. Schaeffer, and J.C.M. Dekkers. 1995. Estimation of genetic parameters for test day somatic cell score. J. Dairy Sci. 78:2847-2857.
50. Schaeffer, L. R., and B. W. Kennedy. 1986. Computing strategies for solving mixed model equations. J. Dairy Sci. 69:575-579.
51. Schaeffer, L. R. and J.C.M. Dekkers. 1994. Random regressions in animal models for test-day production in dairy cattle. Proc. 5th World Congr. Genet. Appl. Livest. Prod., Guelph, Ontario, Canada 18:443-446.
52. Stanton, T. L., L. R. Jones, R. W. Everett, and S. D. Kachman. 1992. Estimating milk, fat, and protein lactation cruves with a test day model. J. Dairy Sci. 75:1691-1700.
53. Swalve, H. H. 1991. Detection of bovine somatotropin treatment in dairy cattle performance records. J. Dairy Sci. 74:1690-1699.
54. Swalve, H. H. 1995. Test day models in the analysis of dairy production data - a review. Arch. Tierz. 38:591-612.
55. Swalve, H. H. 1998. Use of test day records in genetic evaluation. Proc. 6th World Congr. Genet. Appl. Livest. Prod., Armidale, New South Wales, Australia 23:295-302.
56. Swalve, H. H., and N. Gengler. 1998. Genetics of lactation persistency. Pages 75-82 in Proc. Int. Symp. Metabolic Stress in Dairy Cows. British Society of Animal Science (BSAS), EU Concerted Action Group on Genetic Improvement of Functional Traits (GIFT) und British Cattle Veterinary Assoc. (BCVA), Edinburgh, Scotland.
57. Tier, B., and H.-U. Graser. 1991. Predicting breeding values using an implicit representation of the mixed model equations for a multiple trait animal model. J. Anim. Breed. Genet. 108:81-88.
58. Van Bebber, J., N. Reinsch, W. Junge, and E. Kalm. 1999. A Kalman filter based procedure to cluster adjacent herd-test-days into comparison groups. Anim. Sci. (submitted).
59. Van der Werf, J.H.J., M. E. Goddard, and K. Meyer. 1998. The use of covariance functions and random regressions for genetic evaluation of milk production based on test day records. J. Dairy Sci. 81:3300-3306.
60. Van Tassell, C. P., R. L. Quaas, and R. W. Everett. 1992. Parameters estimates for 305-day ME records and 305-day test-day residual records. J. Dairy Sci. 75(Suppl. 1):251. (Abstr.)
61. Van Vleck, L. D., and D. J. Dwyer. 1985. Comparison of iterative procedures for solving equations for sire evaluation. J. Dairy Sci. 68:1006-1014.
62. Vereinigte Informationssysteme Tierhaltung. 1999. German sire proofs VIT, Verden, Germany.
63. Weigel, K. A., T. M. Fisher, C. Van der Linde, D. Gianola, and R. Rekaya. 1998. Impact of bovine somatotropin on genetic evaluation of dairy sires and cows. J. Dairy Sci. 81:2045-2051.
64. White, I.M.S., R. Thompson, and S. Brotherstone. 1999. Genetic and environmental smoothing of lactation curves with cubic splines. J. Dairy Sci. 82:632-638.
65. Wiggans, G. R., and M. E. Goddard. 1997. A computationally feasible test day model for genetic evaluation of yield traits in the United States. J. Dairy Sci. 80:1795-1800.
66. Wiggans, G. R., and N. Gengler. 1999. Strategies for combining test day evaluations into an index for lactation performance. J. Dairy Sci. 82(Suppl. 1):102. (Abstr.)
67. Wilmink, J.B.M. 1987. Studies on test-day and lactation milk, fat and protein yield of dairy cows. Ph.D. thesis, Landbouwuniversiteit, Wageningen, Netherlands.
68. Wood, F.D.P. 1967. Albegraic model of the lactation curve in cattle. Nature 216:164-165.