Quantification of Casein Fractions and of Some of Their Genetic Variants in Phosphate Buffer by near Infrared Spectroscopy

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Milk casein and casein fraction contents have a great influence on milk rennet properties and cheese yield so that the selection of dairy cattle with genetic characteristics suitable for milk transformation is of great interest to dairy farms and firms. The possibility of a rapid and accurate determination of these parameters would be very useful to predict milk aptitude to cheese making. This work aimed to determine casein fractions and their genetic variants content using near infrared (NIR) spectroscopy in reconstituted casein samples by comparing the performance of different NIR equipment (a monochromator instrument and a Fourier transform instrument) and different modes of measurement (reflectance and transflectance) in order to evaluate the best operative conditions for this application. Fifty-eight raw milk samples, collected from different farms in the Asturias region, Spain, were analysed for protein (TP%) and non caseinic nitrogen (NCN%) content using the Kjeldahl method. Casein content was calculated as the difference between TP and NCN content. Casein fractions (αs0-, αs1-, αs2-, κ-casein) and genetic variants of β-casein (βB- βA1-, βA2-casein) were determined by a capillary electrophoresis system. Samples were ultra-centrifuged to obtain native casein and then reconstituted in phosphate buffer (pH = 6.8) at the same original milk concentration, previously determined by the Kjeldahl method. Spectra were collected at 37°C with a FT-NIR instrument in transflectance mode and a monochrometer in both transflectance and reflectance mode. Partial least square (PLS) analyses performed on transflectance spectra showed good prediction ability for all variables—(min R2 = 0.80 for κ-casein; max R2 = 0.94 for βA2–casein), with the exception of αs2-casein. NIR spectroscopy has the ability to determine and quantify casein genetic variants and could be used to select milk for its final purpose and to predict the aptitude of milk to cheese-making.