Henan Key Laboratory for Environmental Pollution Control, Key Laboratory for Yellow River and Huai River Water Environmental Pollution and Control, Ministry of Education, School of Environment, Henan Normal University, Xinxiang, 453007, PR China; Key Laboratory of Green Chemical Media and Reactions, Ministry of Education, Collaborative Innovation Center of Henan Province for Green Manufacturing of Fine Chemicals, School of Chemistry and Chemical Engineering, Henan Normal University, Xinxiang, 453007, PR China.
Key Laboratory of Green Chemical Media and Reactions, Ministry of Education, Collaborative Innovation Center of Henan Province for Green Manufacturing of Fine Chemicals, School of Chemistry and Chemical Engineering, Henan Normal University, Xinxiang, 453007, PR China.
Anal Chim Acta. 2022 Aug 15;1221:340159. doi: 10.1016/j.aca.2022.340159. Epub 2022 Jul 11.
In this study, a cooling assisted solid-phase microextraction technique (CA-SPME) was proposed and used for identifying volatile and semi-volatile compounds in edible oil innovatively coupled to gas chromatography-mass spectrometry. Compared with regular SPME technique, CA-SPME presented significantly higher extraction efficiencies for analytes in edible oil due to its synergistic effect of heating and cooling. After optimization of the extraction conditions including heating temperature, cooling temperature, extraction time, and added amount of edible oil, thirty-eight, thirty-six, twenty-nine, and thirty-three kinds of compounds in peanut oil, olive oil, canola oil, and soybean oil were successfully identified, respectively, using DVB/CAR/PDMS coating with extraction time of 30 min and edible oil amounts of 20 μL. Principal component analysis, partial least squares discriminant analysis, and hierarchical clustering analysis (HCA) were performed to evaluate the potential of proposed method in discriminating edible oils adulteration (peanut oil adulterated with canola oil, peanut oil adulterated with soybean oil, olive oil adulterated with canola oil) subsequently. Results demonstrated that the method was useful in successful discrimination of pure and adulterated edible oils with adulteration percentages ranging from 0.5 to 10%. Furthermore, volatiles contributing to classifications between pure and adulterated edible oils were also illustrated based on variable importance for the projection analysis and distributions of volatiles in HCA heatmaps. The proposed method provided a novel strategy for sensitive detection of edible oil adulteration without any other sample pretreatment.
本研究创新性地提出了一种冷却辅助固相微萃取技术（CA-SPME），并将其与气相色谱-质谱联用，用于鉴定食用油中的挥发性和半挥发性化合物。与常规 SPME 技术相比，CA-SPME 由于加热和冷却的协同作用，对食用油中的分析物具有更高的萃取效率。通过优化萃取条件，包括加热温度、冷却温度、萃取时间和添加的食用油量，使用 DVB/CAR/PDMS 涂层，萃取时间为 30 min，食用油量为 20 μL，成功鉴定了花生油、橄榄油、菜籽油和大豆油中的三十八、三十六、二十九和三十三种化合物。随后采用主成分分析、偏最小二乘判别分析和层次聚类分析（HCA）对所提出方法在鉴别食用油掺假（菜籽油掺花生油、菜籽油掺大豆油、橄榄油掺菜籽油）中的潜力进行了评价。结果表明，该方法可成功鉴别纯油和掺假油，掺假率为 0.5%至 10%。此外，还基于投影分析的挥发性物质的重要性和 HCA 热图中挥发性物质的分布，说明了对纯油和掺假油进行分类的挥发性物质。该方法为无需任何其他样品预处理即可灵敏检测食用油掺假提供了一种新策略。
