期刊
APPLIED SPECTROSCOPY
卷 76, 期 6, 页码 730-736出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/00037028211065502
关键词
Mid-infrared spectroscopy; human milk; attenuated total reflection; partial least squares regression; fatty acids
资金
- European Union [818110]
- COMET Centre CHASE within the COMET -Competence Centers for Excellent Technologies programme by the BMK
- BMDW
- Federal Province of Upper Austria
- Federal Province of Vienna
- Instituto de Salud Carlos III, Ministry of Economy and Competitiveness, Spain [CD19/00176, CP16/00034]
- H2020 Societal Challenges Programme [818110] Funding Source: H2020 Societal Challenges Programme
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.
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.
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