Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of Anatolia

This study aimed to evaluate the biochemical composition and biological activity of propolis samples from different regions of Türkiye to characterize and classify 24 Anatolian propolis samples according to their geographical origin. Chemometric techniques, namely, principal component analysis (PCA)...

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Main Authors: Ümit Altuntaş, İsmail Güzel, Beraat Özçelik
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Molecules
Subjects:
Online Access:https://www.mdpi.com/1420-3049/28/3/1121
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author Ümit Altuntaş
İsmail Güzel
Beraat Özçelik
author_facet Ümit Altuntaş
İsmail Güzel
Beraat Özçelik
author_sort Ümit Altuntaş
collection DOAJ
description This study aimed to evaluate the biochemical composition and biological activity of propolis samples from different regions of Türkiye to characterize and classify 24 Anatolian propolis samples according to their geographical origin. Chemometric techniques, namely, principal component analysis (PCA) and a hierarchical clustering algorithm (HCA), were applied for the first time to all data, including antioxidant capacity, individual phenolic constituents, and the antimicrobial activity of propolis to reveal the possible clustering of Anatolian propolis samples according to their geographical origin. As a result, the total phenolic content (TPC) of the propolis samples varied from 16.73 to 125.83 mg gallic acid equivalent per gram (GAE/g) sample, while the number of total flavonoids varied from 57.98 to 327.38 mg quercetin equivalent per gram (QE/g) sample. The identified constituents of propolis were phenolic/aromatic acids (chlorogenic acid, caffeic acid, <i>p</i>-coumaric acid, ferulic acid, and trans-cinnamic acid), phenolic aldehyde (vanillin), and flavonoids (pinocembrin, kaempferol, pinobanksin, and apigenin). This study has shown that the application of the PCA chemometric method to the biochemical composition and biological activity of propolis allows for the successful clustering of Anatolian propolis samples from different regions of Türkiye, except for samples from the Black Sea region.
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spelling doaj.art-e71a0a21a0044ee98d47917d9bb57d742023-11-16T17:27:56ZengMDPI AGMolecules1420-30492023-01-01283112110.3390/molecules28031121Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of AnatoliaÜmit Altuntaş0İsmail Güzel1Beraat Özçelik2Department of Food Engineering, İstanbul Technical University, 34469 İstanbul, TurkeyDepartment of Mathematical Engineering, İstanbul Technical University, 34469 İstanbul, TurkeyDepartment of Food Engineering, İstanbul Technical University, 34469 İstanbul, TurkeyThis study aimed to evaluate the biochemical composition and biological activity of propolis samples from different regions of Türkiye to characterize and classify 24 Anatolian propolis samples according to their geographical origin. Chemometric techniques, namely, principal component analysis (PCA) and a hierarchical clustering algorithm (HCA), were applied for the first time to all data, including antioxidant capacity, individual phenolic constituents, and the antimicrobial activity of propolis to reveal the possible clustering of Anatolian propolis samples according to their geographical origin. As a result, the total phenolic content (TPC) of the propolis samples varied from 16.73 to 125.83 mg gallic acid equivalent per gram (GAE/g) sample, while the number of total flavonoids varied from 57.98 to 327.38 mg quercetin equivalent per gram (QE/g) sample. The identified constituents of propolis were phenolic/aromatic acids (chlorogenic acid, caffeic acid, <i>p</i>-coumaric acid, ferulic acid, and trans-cinnamic acid), phenolic aldehyde (vanillin), and flavonoids (pinocembrin, kaempferol, pinobanksin, and apigenin). This study has shown that the application of the PCA chemometric method to the biochemical composition and biological activity of propolis allows for the successful clustering of Anatolian propolis samples from different regions of Türkiye, except for samples from the Black Sea region.https://www.mdpi.com/1420-3049/28/3/1121propolisAnatoliaantioxidant activityphenolicsclusteringPCA
spellingShingle Ümit Altuntaş
İsmail Güzel
Beraat Özçelik
Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of Anatolia
Molecules
propolis
Anatolia
antioxidant activity
phenolics
clustering
PCA
title Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of Anatolia
title_full Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of Anatolia
title_fullStr Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of Anatolia
title_full_unstemmed Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of Anatolia
title_short Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of Anatolia
title_sort phenolic constituents antioxidant and antimicrobial activity and clustering analysis of propolis samples based on pca from different regions of anatolia
topic propolis
Anatolia
antioxidant activity
phenolics
clustering
PCA
url https://www.mdpi.com/1420-3049/28/3/1121
work_keys_str_mv AT umitaltuntas phenolicconstituentsantioxidantandantimicrobialactivityandclusteringanalysisofpropolissamplesbasedonpcafromdifferentregionsofanatolia
AT ismailguzel phenolicconstituentsantioxidantandantimicrobialactivityandclusteringanalysisofpropolissamplesbasedonpcafromdifferentregionsofanatolia
AT beraatozcelik phenolicconstituentsantioxidantandantimicrobialactivityandclusteringanalysisofpropolissamplesbasedonpcafromdifferentregionsofanatolia