Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-13T05:03:42.869Z Has data issue: false hasContentIssue false

Genetic parameters of test day records of British Holstein-Friesian heifers

Published online by Cambridge University Press:  02 September 2010

B. L. Pander
Affiliation:
Institute of Cell, Animal and Population Biology, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT
W. G. Hill
Affiliation:
Institute of Cell, Animal and Population Biology, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT
R. Thompson
Affiliation:
AFRC Institute of Animal Physiology and Genetics Research, Edinburgh Research Station, Roslin, Midlothian EH25 9PS
Get access

Abstract

Estimates of genetic parameters for test day records of yields of milk, fat and protein and concentrations of fat and protein were obtained on 47 736 British Holstein-Friesian heifers in 7973 herds, progeny of 40 proven (to improve connectedness) and 707 young sires (comprising about one-fifth of the progeny), using multivariate restricted maximum likelihood methods with a sire model.

Heritability estimates for lactation yields of milk, fat and protein and concentrations of fat and protein were 0·49, 0·39, 0·43, 0·63 and 0·47, respectively. Estimates for individual test day records of these traits ranged from 0·27 to 0·43, 0·16 to 0·34, 0·22 to 0·33, 0·11 to 0·48 and 0·21 to 0·43, respectively. Generally, heritability estimates for test day records were lowest at start and highest in mid lactation.

Estimates of genetic correlations among yields of a trait on different test days ranged from 0·57 to 0·99, and for fat and protein concentrations from 0·34 to 0·99, the correlations being highest for adjacent tests. Phenotypic correlations were lower than genetic correlations. Genetic correlations of test day records with corresponding lactation traits were high (0·76 to 0·99), being highest in mid lactation.

Genetic correlations of test day milk yield with test day yields and concentrations of fat and protein throughout the lactation were similar to those for complete lactation.

The high heritabilities of test day yields and their high genetic correlations with complete lactation, except for the first 1 or 2 test days, suggest that lactation performance may be predicted from test days in early and mid lactation.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1992

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Auran, T. 1973. Studies on monthly and cumulative monthly milk yield records. I. The effect of age, month of calving, herd and length of first test period. Ada Agricuhurae Scandinavica 23:189199.CrossRefGoogle Scholar
Auran, T. 1976. Studies on monthly and cumulative monthly milk yield records. III. Estimates of genetic and phenotypic parameters. Ada Agriculturae Scandinavica 26: 39.CrossRefGoogle Scholar
British Standards Institution. 1972. Recommendations for the methods of milk recording of cow. British Standard 4866, pp. 1217.Google Scholar
Bulmer, M. G. 1971. The effect of selection on genetic variability. American Naturalist 105: 201211.CrossRefGoogle Scholar
Chauhan, V. P. S. and Hill, W. G. 1986. Seasonal grouping in a herd-year-season model of sire evaluation. Animal Production 43: 6371.Google Scholar
Danell, B. 1982a. Studies on lactation yield and individual test day yields of Swedish dairy cows. I. Environmental influences and development of adjustment factors. Ada Agriculturae Scandinavica 32:6581.CrossRefGoogle Scholar
Danell, B. 1982b. Studies on lactation yield and individual test day yields of Swedish dairy cows. II. Estimates of genetic and phenotypic parameters. Acta Agriculturae Scandinavica 32: 8392.CrossRefGoogle Scholar
Danell, B. 1990. Genetic aspects of different parts of lactation. Proceedings of the fourth world congress on genetics applied to livestock production, Edinburgh, vol. 14, pp. 114117.Google Scholar
Harvey, W. R. 1977. Users guide for LSML76. Mixed model least-squares and maximum likelihood computer program. Ohio State University, Columbus. (Mimeograph).Google Scholar
Hill, W. G., Edwards, M. R., Ahmed, M.-K. A. and Thompson, R. 1983. Heritability of milk yield and composition at different levels and variability of production. Animal Production 36: 5968.Google Scholar
Keown, J. F. and Van Vleck, L. D. 1971. Selection on test day fat percentage and milk production. Journal of Dairy Science 54:199203.CrossRefGoogle Scholar
Meyer, K. 1984. Estimates of genetic parameters for milk and fat yield for the first three lactations in British Friesian cows. Animal Production 38: 313322.Google Scholar
Meyer, K. 1986. Restricted maximum likelihood to estimate genetic parameters-in practice. Proceedings of the third world congress on genetics applied to livestock production, Nebraska, vol. 12, pp. 454459.Google Scholar
Meyer, K. 1987. Estimates of variances due to sire × herd interactions and environmental covariances between paternal half-sibs of first lactation dairy production. Livestock Production Science 17: 95115.CrossRefGoogle Scholar
Meyer, K., Graser, H. U. and Hammond, K. 1989. Estimates of genetic parameters for first lactation test day production of Australian Black and White cows. Livestock Production Science 21:177199.CrossRefGoogle Scholar
Milk Marketing Board. 1979. The improved contemporary comparison. Report of the Breeding and Production Organisation, Milk Marketing Board, no. 29, pp. 9195.Google Scholar
Patterson, H. D. and Thompson, R. 1971. Recovery of inter- block information when block sizes are unequal. Biometrika 58: 545554.CrossRefGoogle Scholar
Quaas, R. L., Everett, R. W. and McClintock, A. C. 1979. Maternal grandsire model for dairy sire evaluation, journal of Dairy Science 62: 16481654.CrossRefGoogle Scholar
Swanson, G. J. T. and Gnanasakthy, A. 1990. Estimation of genetic parameters for milk cell count and correlation with production traits in Friesian/Holstein heifers. Animal Production 52: 611 (abstr.).Google Scholar
Van der Werf, J. H. J. and De Boer, W. 1989a. Influence of nonadditive effects on estimation of genetic parameters in dairy cattle. Journal of Dairy Science 72: 26062614.CrossRefGoogle Scholar
Van der Werf, J. H. J. and De Boer, W. 1989b. Estimation of genetic parameters in a crossbred population of Black and White dairy cattle. Journal of Dairy Science 72: 26152623.CrossRefGoogle Scholar
Van Vleck, L. D. and Henderson, C. R. 1961. Estimates of genetic parameters of some functions of part lactation milk records. Journal of Dairy Science 44:10731084.CrossRefGoogle Scholar
Visscher, P. M. 1991. Estimation of genetic parameters in dairy cattle using an animal model and implications for genetic improvement. Ph.D. thesis, University of Edinburgh.Google Scholar
Wilmink, J. B. M. 1987a. Adjustment of test day milk, fat and protein yield for age, season and stage of lactation. Livestock Production Science 16: 335348.CrossRefGoogle Scholar
Wilmink, J. B. M. 1987b. Efficiency of selection for different cumulative milk, fat and protein yields in first lactation. Livestock Production Science 17: 211224.CrossRefGoogle Scholar
Wilmink, J. B. M. 1988. Effects of incomplete records on genetic parameters among cumulative yields in first lactation and on extension of part lactations. Livestock Production Science 18:1934.CrossRefGoogle Scholar