Azizian Hormoz, Kramer John K G
NIR Technologies Inc., Oakville, Ontario, Canada.
Lipids. 2005 Aug;40(8):855-67. doi: 10.1007/s11745-005-1448-3.
A rapid method was developed for classifying and quantifying the FA composition of edible oils and fats using Fourier Transform near infrared spectroscopy (FT-NIR). The FT-NIR spectra showed unique fingerprints for saturated FA, cis and trans monounsaturated FA, and all n-6 and n-3 PUFA within TAG to permit qualitative and quantitative comparisons of fats and oils. The quantitative models were based on incorporating accurate GC data of the different fats and oils and FT-NIR spectral information into the calibration model using chemometric analysis. FT-NIR classification models were developed based on chemometric analyses of 55 fats, oils, and fat/oil mixtures that were used in the identification of similar materials. This database was used to prepare three calibration models-one suitable for the analysis of common fats and oils with low levels of trans FA, and the other two for fats and oils with intermediate and high levels of trans FA. The FT-NIR method showed great potential to provide the complete FA composition of unknown fats and oils in minutes. Compared with the official GC method, the FT-NIR method analyzed fats and oils directly in their neat form and required no derivatization of the fats to volatile FAME, followed by time-consuming GC separations and analyses. The FT-NIR method also compared well with the official FTIR method using an attenuated total reflectance (ATR) cell; the latter provided only quantification of specific functional groups, such as the total trans FA content, whereas FT-NIR provided the complete FA profile. The FT-NIR method has the potential to be used for rapid screening and/or monitoring of fat products, trans FA determinations for regulatory labeling purposes, and detection of contaminants. The quantitative FT-NIR results for various edible oils and fats and their mixtures are presented based on the FT-NIR models developed.
开发了一种利用傅里叶变换近红外光谱（FT-NIR）对食用油脂的脂肪酸（FA）组成进行分类和定量的快速方法。FT-NIR光谱显示了甘油三酯（TAG）中饱和FA、顺式和反式单不饱和FA以及所有n-6和n-3多不饱和脂肪酸（PUFA）的独特指纹图谱，以便对油脂进行定性和定量比较。定量模型是基于将不同油脂的准确气相色谱（GC）数据和FT-NIR光谱信息通过化学计量分析纳入校准模型而建立的。基于对55种用于识别相似材料的油脂和脂肪/油混合物的化学计量分析，开发了FT-NIR分类模型。该数据库用于建立三个校准模型——一个适用于分析反式FA含量低的常见油脂，另外两个适用于反式FA含量中等和高的油脂。FT-NIR方法显示出在几分钟内提供未知油脂完整FA组成的巨大潜力。与官方GC方法相比，FT-NIR方法直接对纯净形式的油脂进行分析，无需将油脂衍生化为挥发性脂肪酸甲酯（FAME），随后进行耗时的GC分离和分析。FT-NIR方法与使用衰减全反射（ATR）池的官方傅里叶变换红外光谱（FTIR）方法相比也表现良好；后者仅提供特定官能团的定量，如总反式FA含量，而FT-NIR提供完整的FA谱图。FT-NIR方法有潜力用于脂肪产品的快速筛选和/或监测、用于监管标签目的的反式FA测定以及污染物检测。基于所开发的FT-NIR模型，给出了各种食用油脂及其混合物的FT-NIR定量结果。
