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利用衰减全反射红外光谱法和无溶剂脂质分离法测定人乳中的脂肪酸。

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

机构信息

27259Institute of Chemical Technologies and Analytics, Technische Universität Wien, Wien, Austria.

Competence Center CHASE GmbH, Linz, Austria.

出版信息

Appl Spectrosc. 2022 Jun;76(6):730-736. doi: 10.1177/00037028211065502. Epub 2022 Feb 4.

Abstract

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 = 0.94), monounsaturated fatty acids (MONO, R = 0.85), polyunsaturated fatty acids (PUFA, R = 0.87), unsaturated fatty acids (UNSAT, R = 0.91), short-chain fatty acids (SCFA, R = 0.79), medium-chain fatty acids (MCFA, R = 0.97), and long-chain fatty acids (LCFA, R = 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.

摘要

本研究介绍了一种基于中红外(IR)的方法,用于确定人乳中的脂肪酸组成。通过应用快速且无溶剂的两步离心方法获得代表性的乳脂馏分。衰减全反射傅里叶变换红外(ATR FT-IR)光谱用于记录纯乳脂的吸收光谱。获得的光谱与人乳全透射光谱进行比较,揭示了 ATR FT-IR 光谱中脂肪酸相关光谱特征的显著程度更高。通过将 ATR FT-IR 光谱与气相色谱-质谱(GC-MS)获得的脂肪酸参考浓度相关联,建立了偏最小二乘(PLS)多元回归方程。对于最重要的脂肪酸总和参数,实现了良好的预测:饱和脂肪酸(SAT,R = 0.94)、单不饱和脂肪酸(MONO,R = 0.85)、多不饱和脂肪酸(PUFA,R = 0.87)、不饱和脂肪酸(UNSAT,R = 0.91)、短链脂肪酸(SCFA,R = 0.79)、中链脂肪酸(MCFA,R = 0.97)和长链脂肪酸(LCFA,R = 0.88)。为了优化和验证每个单独的校准模型,计算了偏最小二乘选择性比(SR)。所有具有高 SR 的中红外区域都可以分配给脂肪酸的吸收,表明所获得的模型具有很高的有效性。

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