RESUMO
Since lipid oxidation often causes serious food safety issues worldwide, determination of oil's oxidative deterioration becomes quite significant, which still calls for efficient analytical methods. In this work, high-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) was firstly introduced for rapid detection of oxidative deterioration in edible oils. Through non-targeted qualitative analysis, oxidized oils with various oxidation levels were successfully discriminated for the first time by coupling HPPI-TOFMS with the orthogonal partial least squares discriminant analysis (OPLS-DA). Furthermore, by targeted interpretation of the HPPI-TOFMS mass spectra and the subsequent regression analysis (signal intensities vs TOTOX values), good linear correlations were observed for several predominant VOCs. Those specific VOCs were promising oxidation indicators, which would play important roles as TOTOX to judge the oxidation states of tested samples. The proposed HPPI-TOFMS methodology can be used as an innovative tool for accurate and effective assessment of lipid oxidation in edible oils.
Assuntos
Alimentos , Óleos , Espectrometria de Massas , Estresse Oxidativo , Óleos de Plantas/químicaRESUMO
High-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) combined with dynamic headspace sampling was developed for rapid identification of adulteration in extra virgin olive oil (EVOO). The volatile organic compound (VOC) fingerprints of EVOO, refined rapeseed oil (r-RO), peanut oil (PO), corn oil (CO), fragrant rapeseed oil (f-RO), and sunflower oil (SO) were obtained in just 1.5 min, which enabled satisfactory classification of different edible oils. 1,4-Bis(methylene)cyclohexane and dimethyl disulfide were unique VOCs in r-RO and f-RO, respectively, while 2,5-dimethylpyrazine and 2-methylpyrazine were distinctive VOCs in PO. Percentages as low as 3% r-RO, 1% PO, and 1% f-RO in r-RO-EVOO, PO-EVOO, and f-RO-EVOO mixtures, respectively, were successfully identified based on the characteristic VOCs. Linear regression equations of these VOCs were established and utilized for predicting the adulteration proportions. The good agreements between the actual adulteration proportions and the predicted ones demonstrated that HPPI-TOFMS was reliable for the quantification of EVOO adulteration.