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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Recently polyphenols attracted great interest in the field of food and nutrition as well as in the pharmaceutical and cosmetics industries due to their health benefits through antioxidative behavior in the human body. However, because of the high number of compounds characterized as phenols and their structural diversity, quantification of polyphenols turns out to be a highly complex task. Although, a wide variety of analytical methods are used for the determination of total polyphenolic content, they are all found to be lacking in a variety of different tasks, such as their limits of detection and quantification, repeatability, accuracy and specificity. For this reason, a novel approach combining the advantages of solid phase purification, near infrared analysis and multivariate data analysis was investigated for the prediction of total polyphenolic content, suitable for a wide range of sample matrices. Dispersive solid phase extraction was performed and optimized using polyvinylpyrrolidone as sorbent, known to selectively bind polyphenols. Near-infrared detection of adsorbed polyphenols was carried out subsequently. Furthermore, the method was in-house validated, examining selectivity, repeatability and accuracy, working range, as well as multivariate limit of detection and limit of quantification, comparing it with two routinely used methods—namely, Folin–Ciocalteu photometric assay and Löwenthal titration. The novel established method was applied for the prediction of total polyphenolic content in tea and wine samples.

Details

Title
Innovative Combination of Dispersive Solid Phase Extraction Followed by NIR-Detection and Multivariate Data Analysis for Prediction of Total Polyphenolic Content
Author
Kappacher, Christoph 1   VIAFID ORCID Logo  ; Neurauter, Markus 1 ; Rainer, Matthias 1   VIAFID ORCID Logo  ; Bonn, Günther K 2 ; Huck, Christian W 1   VIAFID ORCID Logo 

 Institute of Analytical Chemistry and Radiochemistry, Leopold-Franzens University Innsbruck, 6020 Innsbruck, Austria; [email protected] (C.K.); [email protected] (M.N.); [email protected] (M.R.); [email protected] (G.K.B.) 
 Institute of Analytical Chemistry and Radiochemistry, Leopold-Franzens University Innsbruck, 6020 Innsbruck, Austria; [email protected] (C.K.); [email protected] (M.N.); [email protected] (M.R.); [email protected] (G.K.B.); ADSI—Austrian Drug Screening Institute GmbH, 6020 Innsbruck, Austria 
First page
4807
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
14203049
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2565476197
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.