Federal Research Institute of Nutrition and Food, Department of Safety and Quality of Milk and Fish Products, Max Rubner-Institut, Hermann-Weigmann-Strasse 1, 24103, Kiel, Germany.
Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146, Hamburg, Germany.
Anal Bioanal Chem. 2019 Oct;411(26):6931-6942. doi: 10.1007/s00216-019-02063-y. Epub 2019 Aug 10.
Cod liver oil is a popular dietary supplement marketed as a rich source of omega-3 fatty acids as well as vitamins A and D. Due to its high market price, cod liver oil is vulnerable to adulteration with lower priced vegetable oils. In this study, H and C nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, and gas chromatography (coupled to a flame ionization detector) were used in combination with multivariate statistics to determine cod liver oil adulteration with common vegetable oils (sunflower and canola oils). Artificial neural networks (ANN) were able to differentiate adulteration levels based on infrared spectra with a detection limit of 0.22% and a root mean square error of prediction (RMSEP) of 0.86%. ANN models using H NMR and C NMR data yielded detection limits of 3.0% and 1.8% and RMSEPs of 2.7% and 1.1%, respectively. In comparison, the ANN model based on fatty acid profiles determined by gas chromatography achieved a detection limit of 0.81% and an RMSEP of 1.1%. The approach of using spectroscopic techniques in combination with multivariate statistics can be regarded as a promising tool for the authentication of cod liver oil and may pave the way for a holistic quality assessment of fish oils. Graphical abstract.
鱼肝油是一种广受欢迎的膳食补充剂，被誉为富含欧米伽-3 脂肪酸以及维生素 A 和 D。由于其高昂的市场价格，鱼肝油很容易被价格较低的植物油掺假。在这项研究中，我们结合使用了 H 和 C 核磁共振波谱、傅里叶变换红外光谱和气相色谱（与火焰离子化检测器耦合），并结合多元统计分析，以确定鱼肝油与常见植物油（葵花籽油和菜籽油）的掺假情况。人工神经网络（ANN）能够根据红外光谱区分掺假水平，检测限为 0.22%，预测均方根误差（RMSEP）为 0.86%。基于 H NMR 和 C NMR 数据的 ANN 模型的检测限分别为 3.0%和 1.8%，RMSEP 分别为 2.7%和 1.1%。相比之下，基于气相色谱法测定的脂肪酸图谱的 ANN 模型的检测限为 0.81%，RMSEP 为 1.1%。该方法结合使用光谱技术和多元统计分析，可以被视为鱼肝油鉴伪的一种有前途的工具，并可能为鱼油的整体质量评估铺平道路。
