Characterization of the Fatty Acid and Elemental Composition of Human Milk with Chemometric Processing to Determine the Nutritional Value. (22nd January 2023)

• Record Type: Journal Article
• Authors: Covaciu, F.D.; Feher, I.; Molnar, C.; Floare-Avram, V.; Dehelean, A.
• Is Part Of: Analytical letters. Volume 56:Number 2(2023)
• Page Start: 344
• Page End: 356
• Publication Date: 2023-01-22
• Subjects: fatty acid -- gas chromatography-flame ionization detection (GC-FID) -- human milk -- inductively coupled plasma-mass spectrometry (ICP-MS) -- linear discriminant analysis (LDA) -- multielement; Chemistry, Analytic -- Periodicals; Chemistry, Analytic -- Abstracts; 543
• DOI: 10.1080/00032719.2022.2081857
• Languages: English
• ISSNs: 0003-2719

Abstract

Abstract: Breast milk represents the best food for growth and healthy development of new-borns and infants. Exclusive breast feeding is recommended for the first 6 months of life. The composition of human milk changes throughout the lactation period. The aim of this preliminary study was to evaluate the variations in fatty acid composition and elemental concentrations of breast milk during the first 6 months of lactation. Fatty acid methyl esters were prepared by standard methods, separated, and quantified by gas chromatography with flame ionization detection (GC-FID). An inductively coupled plasma mass spectrometry (ICP-MS) method was used to determine 16 elements in breast milk after acid microwave digestion. The mean concentrations of essential elements and potentially toxic elements were as follows: 410.3 mg/L (Na), 53.5 mg/L (Mg), 118.4 mg/L (P), 516 mg/L (K), 326.4 mg/L (Ca), 0.5 mg/L (Fe), 0.4 mg/L (Cu), 1.5 mg/L (Zn), 0.2 mg/L (Cr), 0.02 mg/L (Ni), 3.5 µg/L (Li), 5.0 µg/L (Mn), 0.6 µg/L (Co), 7.7 µg/L (As), and 1.5 µg/L (Pb). Analysis of variance (ANOVA), linear discriminant analysis (LDA) and Pearson's correlation analysis was applied to evaluate correlations among the lactation stages as a function of fatty acid and elemental contents and to identify the best discriminant markers.