文章基本信息

标题：Detection of olive oil adulteration with vegetable oils by ultra‐performance convergence chromatography‐quadrupole time‐of‐flight mass spectrometry (UPC2‐QTOF MS) coupled with multivariate data analysis based on the differences of triacylglycerol compositions
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作者：Yinghua Luo ; Boyan Gao ; Yaqiong Zhang 等
期刊名称：Food Science & Nutrition
电子版ISSN：2048-7177
出版年度：2020
卷号：8
期号：7
页码：3759-3767
DOI：10.1002/fsn3.1664
出版社：John Wiley & Sons, Ltd.
摘要：Three different vegetable oils, including soybean, corn, and sunflower oils, were differentiated from olive oil by using ultra‐performance convergence chromatography coupled with quadrupole time‐of‐flight (UPC 2 ‐QTOF MS) and multivariate data analysis based on their differences in triacylglycerol compositions. Then, olive oil was adulterated by adding these three vegetable oils in 1%, 0.75%, and 0.5% (v/v), and the adulterated olive oils were differentiated from the pure olive oils using the similar analytical strategies but different data processing approaches. After that, the representative markers in differentiating the adulterations were selected, and a mathematical model was created to detect the olive oil adulteration based on these specific markers. These results indicated that UPC 2 ‐QTOF MS coupled with multivariate data analysis is a sensitive and accurate method in detecting olive oil adulteration, even in 0.5% adulteration level (v/v). This method could be applied in olive oil adulteration detection, and potentially beneficial to the oil industry.
关键词：multivariate data analysis;Olive oil adulteration;quadrupole time‐of‐flight mass spectrometry (QTOF MS);triacylglycerol;ultra‐performance convergence chromatography (UPC2)