Hostname: page-component-76fb5796d-5g6vh Total loading time: 0 Render date: 2024-04-25T21:14:37.272Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic analyses of profit for Australian dairy cattle

Published online by Cambridge University Press:  02 September 2010

P. M. Visscher  and
M. E. Goddard
P. M. Visscher
Affiliation:
Victorian Institute of Animal Science, 475 Mickleham Road, Attwood, VIC 3049, Australia
M. E. Goddard
Affiliation:
Victorian Institute of Animal Science, 475 Mickleham Road, Attwood, VIC 3049, Australia
Get access

Abstract

Direct genetic evaluation of profit was investigated as an alternative to a selection index. PROFk was defined as (net income)/(food requirement) until the start of the kth lactation, for k = 2 to 6. Genetic parameters such as heritabilities and genetic correlations were estimated for profit traits for Australian Holstein-Friesian and jersey dairy cattle. Heritabilities for profit until the start of a given lactation were moderate, ranging from 0·12 (for profit until the start of the second lactation in Holsteins) to 0·31 (profit until the start of the third lactation in Jerseys). Genetic correlations between profit traits were very high, and approached unity for most pairs of traits, so that profit early and late in herd life were nearly the same trait. Genetic correlations between profit traits and stayabilities until a given lactation were high, ranging from 0·71 to 0·97. Genetic correlations between profit traits and first lactation milk yield traits were approximately 0·80 for Holsteins and 0·90 for Jerseys. A single analysis urns carried out for lifetime profit using all data, including cows that were still in the herd at the time of data collection. Heritabilities were 0·13 for Holsteins and 0·19 for Jerseys. Genetic correlations between lifetime profit and first lactation yields were high. For the selection of dairy bulls, a multivariate analysis on a milk yield trait (e.g. protein yield) and profit until the last known lactation of bulls' progeny was suggested.

Keywords

dairy cattlegenetic parametersprofit analyses
Type
Research Article
Information
Animal Science , Volume 61 , Issue 1 , August 1995 , pp. 9 - 18
Copyright
Copyright © British Society of Animal Science 1995

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

Ahlborn, G. and Dempfle, L. 1992. Genetic parameters for milk production and body size in New Zealand Holstein-Friesian and Jersey. Livestock Production Science 31:205–219.CrossRefGoogle Scholar
Australian Dairy Herd Improvement Scheme. 1993. The ABV book: Australian breeding values for dairy sires. ADHIS Pty Ltd, Victoria, Australia.Google Scholar
Beard, K. T. 1992. Studies on breeding objectives and selection indices applicable to the Australian dairy cattle industry. PhD tliesis, University of New Soutli Wales, Australia.Google Scholar
Beaudry, T. F., Cassell, B. G., Norman, H. D. and Pearson, R. E. 1988. Impact of prices on profit functions in dairy cattle, journal of Dairy Science 71:485–491.CrossRefGoogle Scholar
Bertrand, J. A., Berger, P. J., Freeman, A. E. and Kelley, D. H. 1985. Profitability in daughters of high versu s average Holstein sires selected for milk yield of daughters. Journal of Dairy Science 68:2287–2294.CrossRefGoogle Scholar
Brascamp, E. W., Smith, C. and Guy, D. R. 1985. Derivation of economic weight from profit functions. Animal Production 40:175–180.Google Scholar
Cassell, B. G., Smith, B. B. and Pearson, R. E. 1993. Influence of herd-life opportunity and characteristics of cows an d herds on different net income functions, journal of Dairy Science 76:1182–1190.CrossRefGoogle Scholar
De Haan, M. H. A., Cassell, B. G., Pearson, R. E. and Smith, B. B. 1992. Relationships between net income, days of productive life, production, and linear type traits in grade and registered Holsteins. Journal of Dairy Science 75:3553–3561.CrossRefGoogle Scholar
Dommerholt, J. and Wilmink, J. B. M. 1986. Optimal selection responses under varying milk prices and margins for milk production. Livestock Production Science 14:109–121.CrossRefGoogle Scholar
Gibson, J. P., Graham, N. and Burnside, E. B. 1992. Selection indexes for production traits of Canadian dairy sires. Canadian journal of Animal Science 72:477–491.CrossRefGoogle Scholar
Goddard, M. E. 1983. Selection indices for non-linear profit functions. Theoretical and Applied Genetics 64:339–344.CrossRefGoogle ScholarPubMed
Jones, L. P. 1985. Australian breeding values for production characters. Proceedings of the fifth conference of the Australian Association of Animal Breeding and Genetics, pp. 242–247.Google Scholar
Jones, L. P. and Goddard, M. E. 1990. Five years experience with the animal model for dairy cattle evaluations in Australia. Proceedings of the fourth world congress of genetics applied to livestock production, Edinburgh, zvl. XIII, pp.382–385.Google Scholar
Klassen, D. J., Monardes, H. G., Jairath, L., Cue, R. I. and Hayes, J. F. 1992. Genetic correlations between lifetime production and linearized type in Canadian Holsteins. journal of Dairy Science 75:2272–2282.CrossRefGoogle ScholarPubMed
Meyer, K. 1985a. Maximum likelihood estimation of variance components for a multivariate mixed model with equal design matrices. Biometrics 41:153–165.CrossRefGoogle ScholarPubMed
Meyer, K. 1985b. Genetic parameters for dairy production of Australian black and white cows. Livestock Production Science 12:205–219.CrossRefGoogle Scholar
Moore, R. K., Kennedy, B. W., Schaeffer, L. R. and Moxley, J. E. 1991. Relationships between age and body weight at calving and production in first lactation Ayrshires and Holsteins. journal of Dairy Science 74:269–278.CrossRefGoogle Scholar
Patterson, H. D. and Thompson, R. 1971. Recovery of inter-block information when block sizes are unequal. Biometrika 58:545–554.CrossRefGoogle Scholar
Rozzi, P. 1991. The ne w quality milk index (ILQ) in Italy. Bianco Nero, supplement 9, pp.14–33.Google Scholar
Smith, C., James, J. W. and Brascamp, E. W. 1986. On the derivation of economic weights in livestock improvement. Animal Production 43:545–551.Google Scholar
Stott, A. W. and DeLorenzo, M. A. 1988. Factors influencing profitability of Jersey and Holstein lactations. Journal of Dairy Science 71:2753–2766.CrossRefGoogle Scholar
Strandberg, E. and Lundberg, C. 1991. A note on the estimation of environmental effects on lactation curves. Animal Production 53:399–402.Google Scholar
Van Vleck, L. D. 1985. Including records of daughters of selected bulls in estimation of sire components of variance. Journal of Dairy Science 68:2396–2401.CrossRefGoogle Scholar
Visscher, P. M., Bowman, P. J. and Goddard, M. E. 1994. Breeding objectives for pasture based dairy production systems. Livestock Production Science In press.Google Scholar
Visscher, P. M. and Goddard, M. E. 1995. Genetic parameters for milk yield, survival, workability and type traits for Australian dairy cattle, journal of Dairy Science In press.Google Scholar