Please use this identifier to cite or link to this item:
https://hdl.handle.net/2445/121163| Title: | Authentication and quantitation of frauds in extra virgin olive oils based on HPLC-UV fingerprinting and multiariate calibration |
| Author: | Carranco, Núria Farrés-Cebrián, Mireia Saurina, Javier Núñez Burcio, Oscar |
| Keywords: | Cromatografia de líquids d'alta resolució Oli d'oliva Indústria alimentària Frau High performance liquid chromatography Olive oil Food industry Fraud |
| Issue Date: | 20-Mar-2018 |
| Publisher: | MDPI |
| Abstract: | HPLC-UV fingerprinting, obtained on a Zorbax Eclipse XDB-C8 reversed-phase column under gradient elution employing 0.1% formic acid aqueous solution and methanol as mobile phase, was applied to the analysis and characterization of olive oils. More than 130 edible oils, including monovarietal extra-virgin olive oils (EVOOs) and other vegetable oils, were analyzed. Principal component analysis results showed a noticeable discrimination between olive oils and other vegetable oils from raw HPLC-UV chromatographic profiles as data descriptors. In contrast, selected HPLC-UV chromatographic time-window segments were necessary to achieve discrimination among monovarietal EVOOs. Partial least square (PLS) regression was employed to tackle olive oil authentication of an Arbequina EVOO adulterated with a Picual EVOO, a refined olive oil, and a sunflower oil. Highly satisfactory results were obtained after PLS analysis, with overall errors in the quantitation of adulterations of an Arbequina EVOO (down to 2.5% adulterant) below 2.9%. |
| Note: | Reproducció del document publicat a: https://doi.org/10.3390/foods7040044 |
| It is part of: | Foods, 2018, vol. 7, num. 4, p. 44 |
| URI: | https://hdl.handle.net/2445/121163 |
| Related resource: | https://doi.org/10.3390/foods7040044 |
| ISSN: | 2304-8158 |
| Appears in Collections: | Articles publicats en revistes (Enginyeria Química i Química Analítica) |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 679250.pdf | 1.36 MB | Adobe PDF | View/Open |
This item is licensed under a
Creative Commons License
