Development and evaluation of a holographic method for analysis of infant formula humanization based on the milk nutrient molecular dataset.

A comprehensive understanding of the qualitative and quantitative similarities and distinctions between the nutrient system of human milk and infant formula is critical in developing infant formulas. However, a holographic comparison method has not been intensively developed to measure the degree of humanization of infant formulas. Consequently, discriminative biomarkers affecting the degree of humanization of infant formulas have not been extensively investigated. This study compiled a milk nutrient molecular dataset, and then presented a new method to identify the degree of humanization of infant formula. The molecular information was converted into a matrix, and then the degree of humanization was elucidated according to the matrix correlation, PCA and OPLS-DA. Compared with infant formulas 2 and 3, infant formula 1 showed the highest degree of humanization at 0.9563. Furthermore, we reported many discriminative biomarkers, such as His, Leu, and Thr, which have not been found in other studies.