Advances in Animal Biosciences (2013), 4:3, pp 600–605 & The Animal Consortium 2013 doi:10.1017/S2040470013000150 advances in animal biosciences Phenotyping of robustness and milk quality D. P. Berry 1- , S. McParland 1 , C. Bastin 2 , E. Wall 3 , N. Gengler 2,4 and H. Soyeurt 2,4 1 Animal & Bioscience Research Department, Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Co. Cork, Ireland; 2 Agricultural Sciences Department, Gembloux Agro-Bio Tech, University of Lie ` ge, Passage des De ´ porte ´ s 2, B-5030 Gembloux, Belgium; 3 SRUC, Easter Bush, Penicuik, Midlothian, EH25 9RG, Scotland; 4 National Fund for Scientific Research (F.R.S.-FNRS), B-1000 Brussels, Belgium 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: infrared, rapid, low cost, dairy, phenotype Introduction A phenotype can be described as the outcome of the inter- acting development between the genotype of an individual and its specific environment throughout life (Bowman, 1974). Successful breeding programmes, however, require routine access, preferably at a low cost, to accurate phenotypes on which genetic or genomic evaluations can be performed. The resulting information can be used to make selection decisions, thereby progressing genetic gain. Here we describe the state- of-the-art in phenotyping strategies focusing mainly on animal robustness and milk quality, as breeding goals need to be adopted to accommodate these traits. Milk quality in dairy production systems was traditionally synonymous with the concentrations of the macro constituents of milk fat, protein and lactose, as well as somatic cell count and, in the case of bulk milk samples, bacterial counts. However, fat concentration in its entirety is mainly an accumulation of individual fatty acid concentrations, and similarly protein concentration, as traditionally measured, is mainly an accumulation of casein and whey fractions, which in turn can further be partitioned into their respective individual components. Similar to milk quality, robustness can be decomposed into its individual components including animal health, fertility and energy balance. Being able to phenotype accurately the individual components of robustness and milk quality not only helps to resolve genetic antagonisms between the sub-components through animal breeding, but also facilitates a greater under- standing of the physiological mechanisms underlying these complex phenotypes. Particular emphasis in this review will be on the research results generated by the EU-funded ROBUSTMILK project (http://www.robustmilk.eu). Phenotyping strategies Phenotypic information can be collected through a series of mechanisms including (1) farmer-scored (e.g. calving difficulty), (2) professionally scored (e.g. linear type traits) or (3) exploita- tion of technological advancements (e.g. milk recording). Each strategy has its own advantages and disadvantages, and each strategy is more or less compatible with different pheno- types. Farmer-scored traits, for example, have a low associated - E-mail: Donagh.berry@teagasc.ie 600