Institute of Food and Nutraceutical Science, Department of Food Science and Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.
Food Chem. 2021 Sep 15;356:129604. doi: 10.1016/j.foodchem.2021.129604. Epub 2021 Mar 20.
A non-targeted chemometric method was devised to detect possible butter adulteration without prior knowledge of the adulterant and marker compounds. Nine common edible oils including vegetable oils, animal fats and margarines were selected as potential adulterants to build a unified classification model. The samples were analyzed using the high-performance liquid chromatography hyphenated with an evaporative light scattering detector (UHPLC-ELSD) and an ultraviolet detector (UHPLC-UV), with the pointwise chromatograms instead of individual peaks for modelling. Both models achieved over 95% correct classification in external validation at the adulteration levels as low as 5% (w/w). The root mean squared errors of prediction (RMSEP) of the regression model were 0.9865 and 1.9080 for UHPLC-ELSD and UHPLC-UV, respectively. Non-targeted chemometrics analyses based on pointwise chromatographic profiles could be valuable for detecting adulterated butter.
本研究建立了一种无需预先了解掺杂物和标记化合物的非靶向化学计量学方法来检测可能的黄油掺假。选择了包括植物油、动物脂肪和人造黄油在内的 9 种常见食用油作为潜在的掺杂物，以构建统一的分类模型。采用高效液相色谱-蒸发光散射检测器（UHPLC-ELSD）和紫外检测器（UHPLC-UV）对样品进行分析，模型建立采用逐点色谱图而不是单个峰。在掺假水平低至 5%（w/w）的外部验证中，两种模型的正确分类率均超过 95%。UHPLC-ELSD 和 UHPLC-UV 的回归模型的预测均方根误差（RMSEP）分别为 0.9865 和 1.9080。基于逐点色谱图的非靶向化学计量学分析可能对检测掺假黄油具有重要价值。
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