Fatty Acid Determination in Human Milk Using Attenuated Total Reflection Infrared Spectroscopy and Solvent-Free Lipid Separation

This study introduces the first mid-infrared (IR)-based method for determining the fatty acid composition of human milk. A representative milk lipid fraction was obtained by applying a rapid and solvent-free two-step centrifugation method. Attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy was applied to record absorbance spectra of pure milk fat. The obtained spectra were compared to whole human milk transmission spectra, revealing the significantly higher degree of fatty acid-related spectral features in ATR FT-IR spectra. Partial least squares (PLS)-based multivariate regression equations were established by relating ATR FT-IR spectra to fatty acid reference concentrations, obtained with gas chromatography-mass spectrometry (GC-MS). Good predictions were achieved for the most important fatty acid sum parameters: saturated fatty acids (SAT, R-CV(2) = 0.94), monounsaturated fatty acids (MONO, R-CV(2) = 0.85), polyunsaturated fatty acids (PUFA, R-CV(2) = 0.87), unsaturated fatty acids (UNSAT, R-CV(2) = 0.91), short-chain fatty acids (SCFA, R-CV(2) = 0.79), medium-chain fatty acids (MCFA, R-CV(2) = 0.97), and long-chain fatty acids (LCFA, R-CV(2) = 0.88). The PLS selectivity ratio (SR) was calculated in order to optimize and verify each individual calibration model. All mid-IR regions with high SR could be assigned to absorbances from fatty acids, indicating high validity of the obtained models.

Automated summary

This study presents a novel method for determining the fatty acid composition of human milk using mid-infrared spectroscopy. By analyzing the absorbance spectra of pure milk fat recorded via attenuated total reflection Fourier transform infrared spectroscopy and combining the results with gas chromatography-mass spectrometry measurements, multivariate regression equations were established to predict fatty acid concentrations. The method achieved good predictions for various important fatty acid parameters, demonstrating its high accuracy.