Hostname: page-component-8448b6f56d-c4f8m Total loading time: 0 Render date: 2024-04-23T14:46:45.783Z Has data issue: false hasContentIssue false
  • English
  • Français

Estimates of genetic parameters for fertility traits of Australian Holstein-Friesian cattle

Published online by Cambridge University Press:  18 August 2016

M. Haile-Mariam ,
J.M. Morton  and
M.E. Goddard
M. Haile-Mariam*
Affiliation:
Institute of Land and Food Resources, University of Melbourne, Parkville Victoria 3052, Australia
J.M. Morton
Affiliation:
InCalf Project, 78 Henna Street, Warrnambool Victoria 3280, Australia
M.E. Goddard
Affiliation:
Institute of Land and Food Resources, University of Melbourne, Parkville Victoria 3052, Australia Victorian Institute of Animal Science, Department of Natural Resources and Environment, Attwood Victoria 3049, Australia
*
†E-mail:mekonnen.hailemariam@nre.vic.gov.au
Get access

Abstract

Fertility data collected on 17131 Holstein-Friesian cows from 158 dairy herds in Australia were used to estimate heritabilities for and correlations among several fertility traits using a sire model. Pregnancy rate (PR), survival (Surv), calving interval (CI), calving to first service interval (CFS), insemination rate (coded as 1 if a cow received a service or 0 otherwise) (InsemR) and first service non-return rate (FNRR) were the main traits analysed in a six-trait model. Among the traits, CFS had the highest h2 (0·13) and FNRR had the lowest h2 (0·01). Genetic correlations among the traits were higher than environmental correlations in all cases. The genetic correlations of PR with InsemR, FNRR, CFS, CI and Surv were 0·74, 0·79 and -0·84, -0·57, and 0·67, respectively. The genetic correlation between InsemR and CFS was high (-0·95) indicating that they almost measure the same trait. Analysis of data from cows that did not return to service after the first service despite not being pregnant (so-called ‘phantom’ cow syndrome) showed that the syndrome is not heritable. The relatively high genetic correlation of PR with traits such as CI and Surv that can be extracted from milk recording data and CFS, FNRR and InsemR that can be obtained from mating data suggests that routine genetic evaluation of sires for daughter fertility based on these traits can be implemented in national selection programs.

Keywords

correlationdairy cattlefertilitygenetic parameters
Type
Research Article
Information
Animal Science , Volume 76 , Issue 1 , February 2003 , pp. 35 - 42
Copyright
Copyright © British Society of Animal Science 2003

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

Carrick, M., Goddard, M.E. and Bowman, P.J. 2000. Evaluation of bull fertility using field data (corrected NRR and CCR). Pilot system for routine collation of non-return data for bulls. In Predicting and monitoring the fertility of artificial insemination sires, pp. 9–24. The University of Queensland, Australia.Google Scholar
Castillo-Juarez, H., Oltenacu, P.A., Blake, R.W., Mcculloch, C.E. and Cienfuegos-Rivas, E.G. 2000. Effect of herd environment on genetic and phenotypic relationships among milk yield, conception rate and somatic cell score in Holstein cattle. Journal of Dairy Science 83: 807–814.CrossRefGoogle ScholarPubMed
Dairy Research and Development Corporation. 2000. The In-calf project – a progress report. DRDC, Melbourne, Australia.Google Scholar
Darwash, A.O., Lamming, G.E. and Woolliams, J.A. 1997. Estimation of genetic variation in the interval from calving to postpartum ovulation of dairy cows. Journal of Dairy Science 80: 1227–1234.CrossRefGoogle ScholarPubMed
Dematawewa, C.M.B. and Berger, P.J. 1998. Genetic and phenotypic parameters for 305-day yield, fertility and survival in Holsteins. Journal of Dairy Science 81: 2700–2709.Google Scholar
Farin, P.W. and Slenning, B.D. 2001. Managing reproductive efficiency in dairy herds. In Herd health: food animal production medicine, third edition (ed. Radostits, O.M.), pp. 255–289. W. B. Saunders Co., Philadelphia, USA.Google Scholar
Gilmour, A.R., Cullis, B.R., Welham, S.J. and Thompson, R. 2000. ASREML reference manual. NSW Agriculture biometric bulletin no. 3. Orange Agricultural Institute, Forest Road, Orange 2800 NSW, Australia.Google Scholar
Grosshans, T., Xu, Z.Z., Burton, L.J., Johnson, D.L. and Macmillan, K.L. 1997. Performance and genetic parameters for fertility of seasonal dairy cows in New Zealand. Livestock Production Science 51: 41–51.CrossRefGoogle Scholar
Haile-Mariam, M., Bowman, P.J. and Goddard, M.E. 2002. Genetic and environmental relationship among calving interval, survival, persistency of milk yield and somatic cell count in dairy cattle. Livestock Production Science In press.Google Scholar
Jonsson, N.N., Fulkerson, W.J., Pepper, P.M. and McGowan, M.R. 1999. Effect of genetic merit and concentrate feeding on reproduction of grazing dairy cows in a subtropical environment. Journal of Dairy Science 82: 2756–2765.Google Scholar
Kadarmideen, H.N., Thompson, R. and Simm, G. 2000. Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle. Animal Science 71: 411–419.Google Scholar
Nation, D.P., Morton, J., Cavalieri, J. and Macmillan, K.L. 2001. Factors associated with the incidence of ‘phantom cows’ in Australian dairy herds. Proceedings of the New Zealand Society of Animal Production 61: 180–183.Google Scholar
Philipsson, J. and Lindhe, B. 2000. Experiences of including categorical traits such as reproduction and health in Scandinavian cattle breeding programmes. Proceedings of the 51st annual meeting of the European Association for Animal Production, The Hague, 21-24 August, 2000.Google Scholar
Pryce, J.E., Nielsen, B.L., Veerkamp, R.F. and Simm, G. 1999. Genotype and feeding system effects and interactions for health and fertility traits in dairy cattle. Livestock Production Science 57: 193–201.Google Scholar
Pryce, J.E. and Veerkamp, R.F. 2001. The incorporation of fertility indices in genetic improvement programmes. In Fertility in the high producing dairy cow, volume 1 (ed. Diskin, M.G.), British Society of Animal Science occasional publication no. 26, pp. 237–250.Google Scholar
Veerkamp, R.F., Oldenbroek, J.K., Gaast, H.J. van der and Werf, J.H.J. van der. 2000. Genetic correlation between days until start of luteal activity and milk yield, energy balance and live weights. Journal of Dairy Science 83: 577–583.CrossRefGoogle ScholarPubMed
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 78: 205–220.Google Scholar
Weigel, K.A. and Rekaya, R. 2000. Genetic parameters for reproductive traits of Holstein cattle in California and Minnesota. Journal of Dairy Science 83: 1072–1080.CrossRefGoogle ScholarPubMed