Research Institute for Pesticides and Water (IUPA), University Jaume I, Avda. Sos Baynat, E-12071 Castellón, Spain.
Research Institute for Pesticides and Water (IUPA), University Jaume I, Avda. Sos Baynat, E-12071 Castellón, Spain.
Food Chem. 2017 Feb 1;216:365-73. doi: 10.1016/j.foodchem.2016.08.033. Epub 2016 Aug 11.
The novel atmospheric pressure chemical ionization (APCI) source has been used in combination with gas chromatography (GC) coupled to hybrid quadrupole time-of-flight (QTOF) mass spectrometry (MS) for determination of volatile components of olive oil, enhancing its potential for classification of olive oil samples according to their quality using a metabolomics-based approach. The full-spectrum acquisition has allowed the detection of volatile organic compounds (VOCs) in olive oil samples, including Extra Virgin, Virgin and Lampante qualities. A dynamic headspace extraction with cartridge solvent elution was applied. The metabolomics strategy consisted of three different steps: a full mass spectral alignment of GC-MS data using MzMine 2.0, a multivariate analysis using Ez-Info and the creation of the statistical model with combinations of responses for molecular fragments. The model was finally validated using blind samples, obtaining an accuracy in oil classification of 70%, taking the official established method, "PANEL TEST", as reference.
新型常压化学电离(APCI)源与气相色谱(GC)联用,再结合混合四极杆飞行时间(QTOF)质谱(MS),用于测定橄榄油中的挥发性成分,通过基于代谢组学的方法增强了根据橄榄油质量对橄榄油样品进行分类的潜力。全谱采集允许检测橄榄油样品中的挥发性有机化合物(VOCs),包括特级初榨、初榨和灯盏花品质。采用动态顶空提取与盒式溶剂洗脱。代谢组学策略包括三个不同步骤:使用 MzMine 2.0 对 GC-MS 数据进行全质谱对齐,使用 Ez-Info 进行多变量分析,并使用分子片段的响应组合创建统计模型。最后使用盲样验证模型,得到 70%的油分类准确性,以官方制定的方法“PANEL TEST”作为参考。