An approximate bayesian analysis of somatic cell score curves in holsteins

Acta Agriculturae Scandinavica A: Animal Sciences

Volumn 50, Issue 4, 2000, Pages 291-299

  Rodriguez Zas, Sandra L ^a   Gianola, Daniel ^a   Shook, George E ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0034311140     PISSN: 09064702     EISSN: 16511972     Source Type: Journal    
DOI: 10.1080/090647000750069485     Document Type: Article

References (29)

1. Afifi, Y. A. 1968. The influence of mastitis, milk production and ease of milking on leukocyte counts in milk. Neth. Milk Dairy J.22, 83-89.
2. Akaike, H. 1974. A new look at the statistical model identification. IEEE Trans. Auto. Control 19, 716-723.
3. Dempster, A. P., Laird, N. M. & Rubin, D. B. 1977. Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B 38, 1-38.
4. Emanuelson, U. 1997. Clinical mastitis in the population: epidemiology and genetics. In: 48th EAAP Meeting, 25th-28th August, Vienna, Austria.
5. Emanuelson, U. & Philipsson, J. 1984. Studies on somatic cell counts in milk from Swedish dairy cows. II. Estimates of genetic parameters of monthly test-day results. Acta Agric. Scand. 34, 45-52.
6. Gianola, D. & Fernando, R. L. 1986. Bayesian methods in animal breeding theory. J. Anim. Sci. 63, 217-244.
7. Gianola, D. & Foulley, J. L. 1983. Sire evaluation for ordered categorical data with a threshold model. Gen. Sel. Evol. 15, 201-212.
8. Gianola, D. & Kachman, S. D. 1983. Prediction of breeding value in situations with nonlinear structure, categorical responses, growth functions and lactation curves. In: Proc. 34th EAAP Meeting, Madrid, Spain.
9. Harmon, R. J. 1994. Physiology of mastitis and factors affecting somatic cell counts. J. Dairy Sci. 77, 2103-2112.
10. Harville, D. A. 1974. Bayesian inference for variance components using only error contrasts. Biometrika 61, 383-385.
11. Kachman, S. D. 1985. Prediction of Genetic merit for growth curve parameters in outbred ICR mice. MSc Thesis, University of Illinois, Urbana, IL.
12. Kachman, S. D. & Gianola, D. 1984. A Bayesian estimator of variance and covariance components in nonlinear growth models. J. Anim. Sci. 59 (Suppl. 1), 176.
13. Kennedy, B. W., Sethar, M. S., Moxley, J. E. & Downey, B. R. 1982. Heritability of somatic cell count and its relationship with milk yield and composition in Holsteins. J. Dairy Sci. 65, 843-852.
14. Lindstrom, M. J. & Bates, D. M. 1990. Nonlinear mixed effects models for repeated measures data. Biometrics 46, 673-687.
15. Morant, S. V. & Gnanasakthy, A. 1989. A new approach to the mathematical formulation of lactation curves. Anim. Prod. 49, 151-162.
16. Nelder, J. A. 1966. Inverse polynomials, a useful group of multifactor response functions. Biometrics 22, 128 -141.
17. Reneau, J. K. 1986. Effective use of dairy herd improvement somatic cell counts in mastitis control. J. Dairy Sci. 69, 1708-1720.
18. Rodriguez-Zas, S. L. 1998. Bayesian analysis of somatic cell score lactation patterns in Holstein cows using nonlinear mixed effects models. PhD Thesis, University of Wisconsin, Madison, WI.
19. Rodriguez-Zas, S. L., Gianola, D. & Shook, G. E. 1997. Nonlinear mixed effects models for somatic cell count test-day data in Holstein cattle. J. Dairy Sci. 80 (Suppl. 1), 227.
20. Rodriguez-Zas, S. L., Gianola, D. & Shook, G. E. 1998. Nonlinear mixed effects Bayesian modeling of somatic cell score lactation patterns in dairy cows. In: Proc. 6th World Congress on Gen. Appl. Lives. Prod., Armidale, NSW, Australia, January 11-16, pp. 497-550.
21. Schutz, M. M., Hansen, L. B., Steuernagel, G. R., Renau, J. K. & Luck, A. L. 1990. Genetic parameters for somatic cells, protein and fat in milk of Holsteins. J. Dairy Sci. 73, 494-513.
22. Schwarz, G. 1978. Estimating the dimension of a model. Annal. Stat. 6, 461-464.
23. Sheldrake, R. F., McGregor, G. D. & Hoare, R. J. T. 1983. Somatic cell count, electrical conductivity and albumin concentration for detecting bovine mastitis. J. Dairy Sci. 66, 542-547.
24. Shook, G. E. 1982. Approaches to summarizing somatic cell counts which improve interpretability. In: Proc. 21st Annual Meeting Nat. Mastitis Council, pp. 150-166.
25. Wakefield, J. C., Smith, A. F. M., Racine-Poon, A. & Gelfand, A. E. 1994. Bayesian analysis of linear and nonlinear population models using the Gibbs sampler. Appl. Stat. 43, 201-221.
26. Weller, J. E., Saran, A. & Zeliger, Y. 1992. Genetic and environmental relationships among somatic cell count, bacterial infection, and clinical mastitis. J. Dairy Sci. 75, 2532-2545.
27. Wiggans, G. R. & Shook, G. E. 1987. A lactation measure of somatic cell count. J. Dairy Sci. 70, 2666-2675.
28. Wolfinger, R. & Lin, X. 1997. Two Taylor-series approximation methods for nonlinear mixed models. Comp. Stat. Data An. 25, 465 -490.
29. Wood, P. D. P. 1967. Algebraic model of the lactation curve in cattle. Nature 216, 164-165.