Identification of Adulterated Extra Virgin Olive Oil by Colorimetric Sensor Array
2022
Huang, Lu | Wang, Mengyao | Liu, Haiying
A method based on colorimetric sensor array (CSA) was utilized to identify extra virgin olive oil (EVOO) mixed with soybean oil and corn oil using the principle that volatile organic compounds (VOCs) interact with chemically responsive dyes to cause color changes. The array was fabricated by dropping solutions of seven pH indicators and two metalloporphyrins on porous and hydrophobic polyvinylidene fluoride (PVDF) membranes. Difference maps were acquired by deducting the “initial” one from the “final” image, and the color changes were transformed into digital information at the same time. The results of CSA were evaluated by linear discriminant analysis (LDA) to successfully distinguish EVOO adulterated with soybean oil and corn oil at different proportion. The accuracy of backtracking validation was 100% for both soybean oil and corn oil, and the accuracy of cross-validation was 90.7% and 81.5% respectively. Principal component analysis (PCA) was applied to process the same data, and the results showed that the contribution of the first three PCs was 60.98% and 53.8% of the total variance respectively. The CSA has wide application potential due to its low cost, easy operation, fast reaction, and visual observation.
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