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Estimation of genetic and crossbreeding parameters of fatty acid concentrations in milk fat predicted by mid-infrared spectroscopy in New Zealand dairy cattle

Published online by Cambridge University Press:  23 July 2014

Nicolas Lopez-Villalobos ,
Richard J. Spelman ,
Janine Melis ,
Stephen R. Davis ,
Sarah D. Berry ,
Klaus Lehnert ,
Stephen E. Holroyd ,
Alastair K.H. MacGibbon  and
Russell G. Snell
Nicolas Lopez-Villalobos*
Affiliation:
Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Palmerston North, New Zealand
Richard J. Spelman
Affiliation:
Livestock Improvement Corporation, Hamilton, New Zealand
Janine Melis
Affiliation:
Livestock Improvement Corporation, Hamilton, New Zealand
Stephen R. Davis
Affiliation:
Livestock Improvement Corporation, Hamilton, New Zealand
Sarah D. Berry
Affiliation:
School of Biological Sciences, University of Auckland, Auckland, New Zealand
Klaus Lehnert
Affiliation:
School of Biological Sciences, University of Auckland, Auckland, New Zealand
Stephen E. Holroyd
Affiliation:
Fonterra Research and Development Centre, Palmerston North, New Zealand
Alastair K.H. MacGibbon
Affiliation:
Fonterra Research and Development Centre, Palmerston North, New Zealand
Russell G. Snell
Affiliation:
School of Biological Sciences, University of Auckland, Auckland, New Zealand
*
*For correspondence; e-mail: [email protected]
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Abstract

The objective of this study was to estimate heritability and crossbreeding parameters (breed and heterosis effects) of various fatty acid (FA) concentrations in milk fat of New Zealand dairy cattle. For this purpose, calibration equations to predict concentration of each of the most common FAs were derived with partial least squares (PLS) using mid-infrared (MIR) spectral data from milk samples (n=850) collected in the 2003–04 season from 348 second-parity crossbred cows during peak, mid and late lactation. The milk samples produced both, MIR spectral data and concentration of the most common FAs determined using gas chromatography (GC). The concordance correlation coefficients (CCC) between the concentration of a FA determined by GC and the PLS equation ranged from 0·63 to 0·94, suggesting that some prediction equations can be considered to have substantial predictive ability. The PLS calibration equations were then used to predict the concentration of each of the fatty acids in 26 769 milk samples from 7385 cows that were herd-tested during the 2007–08 season. Data were analysed using a single-trait repeatability animal model. Shorter chain FA (16 : 0 and below) were significantly higher (P<0·05) in Jersey cows, while longer chain, including unsaturated longer chain FA were higher in Holstein-Friesian cows. The estimates of heritabilities ranged from 0·17 to 0·41 suggesting that selective breeding could be used to ensure milk fat composition stays aligned to consumer, market and manufacturing needs.

Keywords

Fatty acidsgenetic parameterscrossbreedinginfrared spectrometry
Type
Research Article
Information
Journal of Dairy Research , Volume 81 , Issue 3 , August 2014 , pp. 340 - 349
Copyright
Copyright © Proprietors of Journal of Dairy Research 2014 

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