A study published in the Journal of Food Science demonstrates the potential of using near-infrared spectroscopy to screen extra virgin olive oils (EVOO) for authenticity.
The researchers developed the test by using Fourier-transform near infrared (FT-NIR) spectroscopy in combination with univariate and multivariate data analysis methods. Using disposable glass tubes, spectra for 62 reference EVOO, 10 edible oil adulterants, 20 blends consisting of EVOO spiked with adulterants, 88 retail EVOO products, and other test samples were rapidly measured in the transmission mode without any sample preparation. The researchers used the univariate conformity index (CI) and the multivariate supervised soft independent modeling of class analogy (SIMCA) classification tool to analyze the various olive oil products that were tested for authenticity against a library of reference EVOO.
They observed better discrimination between the authentic EVOO and some commercial EVOO products using SIMCA than with CI analysis. Approximately 61% of all EVOO commercial products were flagged by SIMCA analysis, suggesting that further analysis be performed to identify quality issues and/or potential adulterants.
The researchers concluded that due to its simplicity and speed, FT-NIR spectroscopy in combination with multivariate data analysis can be used as a complementary tool to conventional official methods of analysis to rapidly flag EVOO products that may not belong to the class of authentic EVOO. This may provide government regulators and stakeholders a practical tool to rapidly assess EVOO quality and/or purity.