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Classification of Edible Vegetable Oil Degradation Using Multivariate Data Analysis From Electrochemical Techniques
One of the main concerns about the use of edible vegetable oils in food industry frying processes is the oxidative degradation due to the high temperatures, presence of oxygen, ultraviolet radiation, and the presence of metal ions. The main compounds formed during oxidative reactions include aldehyd...
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Published in: | Food analytical methods 2021-12, Vol.14 (12), p.2597-2606 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | One of the main concerns about the use of edible vegetable oils in food industry frying processes is the oxidative degradation due to the high temperatures, presence of oxygen, ultraviolet radiation, and the presence of metal ions. The main compounds formed during oxidative reactions include aldehydes, ketones, alcohols, and carboxylic acids, being some of these electroactive compounds, which can be used with quantification purposes. In this work, cyclic voltammetry and a flow method based on headspace sampling with amperometric detection were performed, followed by principal component and cluster analysis to classify palm olein, soya bean, and sunflower oil samples according to their degradation state. The electrochemical techniques were based on the use of 1-butyl-3-methylimidazolium hexafluorophosphate as conductive media. The amperometric profile information provided a clearer classification than the voltammetric profile. Additionally, the amperometric results were applied to determine iodine value and aldehyde content by means of a partial least square regression. The values obtained were statistically similar than the estimated using
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H nuclear magnetic resonance spectroscopy and HPLC. The combination of electrochemical techniques and chemometric analysis offers valuable information for classification and quantification purposes. |
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ISSN: | 1936-9751 1936-976X |
DOI: | 10.1007/s12161-021-02083-4 |