Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-27T14:38:00.205Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic parameters of a biological lactation model: early lactation and secretion rate traits of dairy heifers

Published online by Cambridge University Press:  01 August 2009

G. E. Pollott
G. E. Pollott*
Affiliation:
Royal Veterinary College, Royal College Street, London, NW1 0TU, UK
*
†E-mail: gpollott@rvc.ac.uk
Get access

Abstract

Early lactation parameters are difficult to estimate from commercial dairy records due to the small number of records available before the peak of production. A biological model of lactation was used with weekly milk records from a single Holstein herd to estimate these early lactation parameters and the secretion rate of milk from the average cell throughout lactation. A genetic analysis of the lactation curve parameters, calculated curve characteristics and secretion rate traits was undertaken. Early lactation traits were found to have little genetic variation and effectively zero heritability. Secretion rate traits for milk, protein, lactose and water were all moderately heritable and highly genetically correlated (>0.87) but fat secretion rate had lower genetic correlations with the other secretion rates. A similar pattern of correlations was seen between total lactation yield traits for fat, protein, lactose and water. The genetic correlations between the lactation curve traits and the secretion rate traits were calculated. Total milk yield, peak yield and maximum secretion potential were all highly correlated with milk, lactose and water secretion rates but less so with fat and protein secretion rates. In particular, fat secretion rate had a moderate to low genetic correlation with these lactation curve traits. Persistency of lactation was highly correlated with fat and protein secretion rates, more persistent lactations being associated with lower rates of secretion of these milk components. Similar levels of heritability were found, where trait genetic parameters were directly equivalent to those derived from the same dataset by random regression methods. However, by using a biological model of lactation to analyse lactation traits new insights into the biology of lactation are possible and ways to select cows on a range of lactation traits may be achieved.

Keywords

biological modelgenetic parametersheiferslactation curve
Type
Full Paper
Information
animal , Volume 3 , Issue 8 , August 2009 , pp. 1085 - 1093
Copyright
Copyright © The Animal Consortium 2009

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

Albarrán-Portillo, B, Pollott, GE 2008. A genetic analysis of the parameters derived using a biological model of lactation on commercial dairy cow records. Journal of Dairy Science 91, 3639–3648.CrossRefGoogle Scholar
Dijkstra, J, France, J, Dhanoa, MS, Maas, JA, Hanigan, MD, Rook, AJ, Beever, DE 1997. A model to describe growth patterns of the mammary gland during pregnancy and lactation. Journal of Dairy Science 80, 2340–2354.CrossRefGoogle Scholar
Gilmour, AR, Gogel, BJ, Cullis, BR, Welham, SJ, Thompson, R 2002. ASReml users guide release 1.0. VSN International Ltd., Hemel Hempstead, HP1 1ES, UK.Google Scholar
Olori, VE, Brotherstone, S, Hill, WG, McGuirk, BJ 1997. Effect of gestation stage on milk yield and composition in Holstein-Friesian cattle. Livestock Production Science 52, 167–176.CrossRefGoogle Scholar
Olori, VE, Brotherstone, S, Hill, WG, McGuirk, BJ 1999a. Fit of standard models of the lactation curve to weekly records of milk production of cows in a single herd. Livestock Production Science 58, 55–63.CrossRefGoogle Scholar
Olori, VE, Hill, WG, McGuirk, BJ, Brotherstone, S 1999b. Estimating variance components for test day milk records by restricted maximum likelihood with a random regression animal model. Livestock Production Science 61, 53–63.CrossRefGoogle Scholar
Pollott, GE 2000. A biological approach to lactation curve analysis for milk yield. Journal of Dairy Science 83, 2448–2458.CrossRefGoogle ScholarPubMed
Pollott, GE 2004. Deconstructing milk yield and composition during lactation using biologically-based lactation models. Journal of Dairy Science 87, 2375–2387.CrossRefGoogle ScholarPubMed
Pollott, GE, Gootwine, E 2000. Appropriate mathematical models for describing the complete lactation of dairy sheep. Animal Science 71, 197–207.CrossRefGoogle Scholar
Pollott, GE, Gootwine, E 2001. A genetic analysis of complete lactation milk production in improved Awassi sheep. Livestock Production Science 71, 37–47.CrossRefGoogle Scholar
SAS/STAT 1989. SAS/STAT user’s guide, version 6, vol. 2, 4th edition, GLM-VARCOMP. SAS Institute Inc., Cary, NC, USA.Google Scholar
Strathie, RJ, McGuirk, BJ 1995. Developments with the MOET dairy breeding scheme. British Cattle Breeders Club 50, 9–15.Google Scholar
Vetharaniam, IS, Davis, R, Soboleva, TK, Shorten, PR, Wake, GC 2003. Modeling the interaction of milking frequency and nutrition in mammary gland growth and lactation. Journal of Dairy Science 86, 1987–1996.CrossRefGoogle ScholarPubMed