Chemometric studies of several minerals in milks.

A statistical study of correlation, factorial, and discriminant analysis on the metal composition (Se, Fe, Cu, Zn, Na, K, Ca, Mg) of different types of milks (human, cow, goat, pasteurized, and powdered infant formula) was carried out to establish the relationships between the metal concentrations and, therefore, differentiate the samples according to the type of milk. A large number of significant intermetallic correlations were found in all samples, which could be due to biological relationships between the metals studied. After the factorial analysis, the dimension space was reduced from eight variables to two factors, accounting for approximately 71.4% of the total variance. After an orthogonal rotation, the first factor was positively correlated with Ca and the second factor with Fe. The representation of the scores makes it possible to separate not only human milk from powdered infant formula but also to separate both of these from the other milks. In the discriminant analysis, four discriminant functions were obtained, which are linear combinations of the quantitative variables that best explain the differences among the different milks analyzed. These functions make it possible to classify 98% of the samples analyzed within each type of milk correctly. Therefore, discriminant functions obtained here can be used to identify the origin of any milk sample.