Here, a method to characterize edible oils and edible oil mixtures through fingerprinting and the isolation of individual
analyte differences is reported. Aroma and flavor analytes in extra virgin olive, olive, peanut, grapeseed, and vegetable
oils were sampled with headspace solid-phase microextraction (HS-SPME). The samples were analyzed with complementary gas chromatography
(GC) systems; two-dimensional GC paired with time-of-flight mass spectro-metry (GC×GC–TOF-MS) and one-dimensional GC coupled
to high resolution TOF-MS. These methods allowed for comparing edible oil varieties by their chromatographic fingerprints,
characterizing the samples with the identification of individual analyte differences, differentiating oil mixtures from pure
oil varieties with principal component analysis (PCA), and confirming analyte identities with accurate mass data.
Characterization of food products, including distinguishing differences, is important in the food industry. Differences that
are intentionally introduced are of particular interest. The global marketplace has seen an increase in cases of food fraud, which is loosely defined as the deliberate misrepresentation of a product for the purpose of monetary gain, with cost estimates
of these types of fraud at $10–15 billion dollars per year (1). Olive oil adulteration ranks near the top of all reported
food fraud cases with common adulterations including the substitution of olive-derived oils with other less expensive edible
oils or the mislabeling of regular olive oils as extra virgin olive oil (2).
These adulterations are often difficult for a consumer to detect, but can decrease health benefits and have the potential
for unintended exposure to allergens — for example, by adulteration with nut oils. Detecting food fraud experimentally is
also challenging because of the inherent variations of natural products and the wide range of potential methods of adulteration.
Targeted analytical tools to screen for specific analytes or known adulterants have the risk of missing new or unanticipated
mechanisms of food fraud. Nontargeted analytical methods, especially those that isolate individual analytes within a food
matrix and characterize complex food products, are well-suited for addressing these challenges.
Gas chromatography (GC) is a well-established analytical approach used in the food industry for isolating individual analytes
within a complex matrix. For many samples, one-dimensional GC is sufficient to isolate the components of the mixture, but
as sample complexity increases so does the occurrence of coelution. One approach to handle increased complexity and analyte
coelution is the use of comprehensive two-dimensional GC (GC×GC), which couples a complementary second separation dimension
to the primary column and leads to an increase in the peak capacity, theoretically as high as the multiplicative of the individual
peak capacities of each column. This technique has been shown to be a powerful method for analyzing food products (3).
Coupling GC separations with mass spectrometry (MS) provides a means for identifying the isolated analytes present in the
food sample. When unanticipated analytes are present, identification can provide insight to the mode of adulteration. Time-of-flight
(TOF) MS is especially beneficial for nontargeted analyses as it is capable of collecting full mass range data at fast acquisition
rates and target analytes do not need to be specified before acquisition. Full mass range spectra can be library searched
for identification and accurate mass information from high-resolution MS systems provides added confidence to identifications
with formula computation capabilities. In this study, both one-dimensional (1D) and two-dimensional (2D) GC and both nominal
and accurate mass MS systems were utilized, providing complementary and confirmatory information to characterize edible oils.
These analytical tools have the potential to identify food fraud through differentiation of oil varieties and oil mixtures.