The concentrations of protein, fat, five minerals (Na, K, P, Ca and Mg) and nine trace elements (Fe, Zn, Cu, Mn, Se, Al, Cd, Cr and Pb) have been determined in 347 samples of raw cow milk from the community of Navarra, north Spain, using infrared analysis, atomic absorption spectrometry (flame and electrothermal atomisation) and inductively coupled plasma atomic emission spectroscopy. A preliminary chemometric study with the use of pattern recognition methods was carried out in order to characterise, classify and distinguish the different collected samples on the basis of their contents. Principal component analysis (PCA) has permitted the reduction of 16 variables to five principal components which interpret reasonably well the correlations of these studied variables. These variable associations may be attributed to intrinsic (lactogenesis) and other extrinsic factors, such as seasonal variation, animal feeding or geographical situation. Changes in these contents during different seasons were also assessed and consistently interpreted. Linear discriminant analysis (LDA) was used to explore cow milk samples, classifying according to season or geographical location, providing complementary information to PCA. This work shows that PCA and LDA are useful chemometric tools for the multivariate characterisation of raw cows’ milk.
展开▼
