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Phenotyping of robustness and milk quality

Published online by Cambridge University Press:  30 July 2013

D. P. Berry ,
S. McParland ,
C. Bastin ,
E. Wall ,
N. Gengler  and
H. Soyeurt
D. P. Berry*
Affiliation:
Animal & Bioscience Research Department, Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Co. Cork, Ireland
S. McParland
Affiliation:
Animal & Bioscience Research Department, Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Co. Cork, Ireland
C. Bastin
Affiliation:
Agricultural Sciences Department, Gembloux Agro-Bio Tech, University of Liège, Passage des Déportés 2, B-5030 Gembloux, Belgium
E. Wall
Affiliation:
SRUC, Easter Bush, Penicuik, Midlothian, EH25 9RG, Scotland
N. Gengler
Affiliation:
Agricultural Sciences Department, Gembloux Agro-Bio Tech, University of Liège, Passage des Déportés 2, B-5030 Gembloux, Belgium National Fund for Scientific Research (F.R.S.-FNRS), B-1000 Brussels, Belgium
H. Soyeurt
Affiliation:
Agricultural Sciences Department, Gembloux Agro-Bio Tech, University of Liège, Passage des Déportés 2, B-5030 Gembloux, Belgium National Fund for Scientific Research (F.R.S.-FNRS), B-1000 Brussels, Belgium
*
†E-mail: Donagh.berry@teagasc.ie
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Abstract

A phenotype describes the outcome of the interacting development between the genotype of an individual and its specific environment throughout life. Animal breeding currently exploits large data sets of phenotypic and pedigree information to estimate the genetic merit of animals. Here we describe rapid, low-cost phenomic tools for dairy cattle. We give particular emphasis to infrared spectroscopy of milk because the necessary spectral data are already routinely available on milk samples from individual cows and herds, and therefore the operational cost of implementing such a phenotyping strategy is minimal. The accuracy of predicting milk quality traits from mid-infrared spectroscopy (MIR) analysis of milk, although dependent on the trait under investigation, is particularly promising for differentiating between good and poor-quality dairy products. Many fatty acid concentrations in milk, and in particular saturated fatty acid content, can be very accurately predicted from milk MIR. These results have been confirmed in many international populations. Albeit from only two studied populations investigated in the RobustMilk project, milk MIR analysis also appears to be a reasonable predictor of cow energy balance, a measure of animal robustness; high accuracy of prediction was not expected as the gold standard method of measuring energy balance in those populations was likely to contain error. Because phenotypes predicted from milk MIR are available routinely from milk testing, longitudinal data analyses could be useful to identify animals of superior genetic merit for milk quality and robustness, as well as for monitoring changes in milk quality and robustness because of management, while simultaneously accounting for the genetic merit of the animals. These sources of information can be very valuable input parameters in decision-support tools for both milk producers and processors.

Keywords

infraredrapidlow costdairyphenotype
Type
Full Paper
Information
Advances in Animal Biosciences , Volume 4 , Issue 3: Proceedings of the ROBUSTMILK project, an EU wide programme which was financially supported by the European Commission under the Seventh Research Framework Program, Grant Agreement KBBE–211708 , July 2013 , pp. 600 - 605
Copyright
Copyright © The Animal Consortium 2013 

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