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. Issue 7 (25th May 2020)

• Record Type: Journal Article
• Authors: Luo, Yinghua; Gao, Boyan; Zhang, Yaqiong; Yu, Liangli (Lucy)
• Is Part Of: Food science & nutrition. Volume 8:Issue 7(2020)
• Page Start: 3759
• Page End: 3767
• Publication Date: 2020-05-25
• Subjects: multivariate data analysis -- Olive oil adulteration -- quadrupole time‐of‐flight mass spectrometry (QTOF MS) -- triacylglycerol -- ultra‐performance convergence chromatography (UPC2); Food industry and trade -- Periodicals; Food -- Periodicals; Nutrition -- Periodicals; 664
• DOI: 10.1002/fsn3.1664
• Languages: English
• ISSNs: 2048-7177

Abstract

Abstract: 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. Abstract : This manuscript reported the study of differentiating three different vegetable oils, including soybean oil, corn oil, and sunflower oil from olive oil by using UPC2‐QTOF MS and multivariate data analysis based on their differences in triacylglycerol compositions. After that, these three vegetable oils were adulterated to olive oil in 1%, 0.75%, and 0.5% (v/v), and the adulterated olive oil samples were differentiated from the pure olive oil using the similar analytical strategies but different data processing approaches. Then, the representative triacylglycerols in differentiating olive oil adulterations were selected and identified, and a mathematical model was created to detect the olive oil adulteration based on these specific triacylglycerols.