Genetic analysis of milk spectral data to develop management and selection tools to improve the nutraceutical properties of milk

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Milk laboratories quantify major milk components such as fat or protein using mid-infrared (MIR) spectrometry. These predictions are used for milk payments as well as for animal performances recording. All these predictions are based on the same initial data, the MIR spectrum, which represents the global milk composition. The advantaes of MIR spectrometry compared to traditional chemichal analysis are its rapidity and cheap cost. Recently it has been shown that it is possible to quantify other components than fat or protein such as lactose, casein, b-hydroxyburate ( a keytone body) acetone, fatty acids, lactoferrin, or minerals. All of these milk components are potential indicators of animal health and reproduction status, nutritional quality of the milk, or both. The objective of this project is to study directly the phenotypic and genotypic variability of the spectral data in order to improve cow robustness, nutrional quality of milk for human consumption and develop calibration equations for milk fatty acids from milk spectral data. This research project involves 3 stages: (1) reduction of the dimentionality of spectral data, (2) study of the spectral variability in relation with changes of animal health and reproduction status, (3) development of calibration equations for milk fatty acids from milk spectral data.