Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-26T22:46:46.281Z Has data issue: false hasContentIssue false
  • English
  • Français

Adjustment of lamb birth and weaning weights for continuous effects of ewe age

Published online by Cambridge University Press:  09 March 2007

D. R. Notter ,
R. C. Borg  and
L. A. Kuehn
D. R. Notter*
Affiliation:
Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg 24061, USA
R. C. Borg
Affiliation:
Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg 24061, USA
L. A. Kuehn
Affiliation:
Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg 24061, USA
*
†E-mail: [email protected]
Get access

Abstract

Procedures for continuous adjustment of lamb birth and weaning weights for effects of ewe age were developed using 18 747 birth and 13 139 weaning weight records of Polypay sheep enrolled in the US National Sheep Improvement Program. Changes in birth and weaning weights across ewe age groups were modelled using hybrid curves that combined asymptotic regression models to describe initial increases in lamb weight as ewes moved into adulthood with secondorder polynomials to describe declines in lamb weights in older ewes. Lamb birth and weaning weights were highest (and the asymptotic and polynomial forms comprising the hybrid curves intersected) at ewe ages of 76 and 52 months, respectively. Across all ewe ages, hybrid curves were superior to second- and third-order polynomials in goodness of fit, producing a parabolic form with a flat top and different decay rates on either side of the ewe ages corresponding to maximum lamb weights. Fourth- and fifth-degree polynomials were equivalent to hybrid curves in goodness of fit, but generally did not produce reasonable predictions for the oldest ewes. Adjustment factors derived from the hybrid curve predicted that lamb birth weight would increase from 76% of maximum in 11-month-old ewes to 90 and 96% of maximum in 24- and 36-month-old ewes, respectively, and then decline to 97% of maximum at 105 months. For weaning weight, 83, 95, 99, and 93% of maximum lamb weight were attained at ewe ages of 11, 24, 36, and 105 months, respectively. Resulting multiplicative adjustment factors avoid discontinuities at boundaries between ewe age categories and are particularly useful in accelerated or other multiple-season lambing systems.

Keywords

adjustment factorsage groupsbirth weightsheepweaning weight
Type
Research Article
Information
Animal Science , Volume 80 , Issue 3 , June 2005 , pp. 241 - 248
Copyright
Copyright © British Society of Animal Science 2005

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

Bradford, G. E. 2003. SID sheep production handbook, 2002 edition. American Sheep Industry Inc., Centennial, CO.Google Scholar
Brown, D. J. and Reverter, A. 2002. A comparison of methods to pre-adjust data for systematic environmental effects in genetic evaluation of sheep. Livestock Production Science 75: 281–291.Google Scholar
Brown, D. J., Tier, B., Reverter, A., Banks, R. and Graser, H. U. 2000. OVIS: a multiple trait breeding value estimation program for genetic evaluation of sheep. Wool Technology and Sheep Breeding 48: 285–297.Google Scholar
Craven, P. and Wahba, G. 1979. Smoothing noisy data with spline functions: estimating the correct degree of smoothing by the method of generalized cross-validation. Numerische Mathematik 31: 377–403.Google Scholar
Freetley, H. C. and Leymaster, K. A. 2004. Relationship between litter birth weight and litter size in six breeds of sheep. Journal of Animal Science 82: 612–618.Google Scholar
Hulet, C. V., Ercanbrack, S.K. and Knight, A.D., 1984. Development of the Polypay breed of sheep. Journal of Animal Science 58: 15–24.CrossRefGoogle ScholarPubMed
Laird, A. K. 1966. Postnatal growth of birds and mammals. Growth 30: 349–363.Google Scholar
Lewis, R. M., Shelton, M., Sanders, J. O., Notter, D. R. and Pirie, W. R. 1989. Adjustment factors for 120-day weaning weight in Rambouillet range lambs. Journal of Animal Science 67: 1107–1115.Google Scholar
Notter, D. R. 2002. Opportunities to reduce seasonality of breeding in sheep by selection. Sheep and Goat Research Journal 17: 20–32.Google Scholar
Notter, D. R., Swiger, L. A. and Harvey, W. R. 1975. Adjustment factors for 90-day lamb weight. Journal of Animal Science 40: 383–391.Google Scholar
Quaas, R. L. and Pollak, E. J. 1980. Mixed model methodology for farm and ranch beef cattle testing programs. Journal of Animal Science 51: 1277–1287.Google Scholar
Richards, J. R. 1959. A flexible growth function for empirical use. Journal of Experimental Botany 10: 290–300.Google Scholar
Schumaker, L. L. 1993. Spline functions: basic theory. Krieger Publishing Co., Malabar, FL.Google Scholar
Statistical Analysis Systems Institute. 2003. SAS system release 82 for Windows. SAS Institute Inc., Cary, NCGoogle Scholar
Wahba, G. 1990. Spline models for observational data. Society for Industrial and Applied Mathematics, Philadelphia, PA.Google Scholar
White, I. M. S., Thompson, R. and Brotherstone, S. 1999. Genetic and environmental smoothing of lactation curves with cubic splines. Journal of Dairy Science 82: 632–638.Google Scholar