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Phytochemical profiling of oak bark extract: A combined approach using near-infrared spectroscopy and liquid chromatography-mass spectrometry.

Authors :
Schwarz B
Kappacher C
Huck CW
Source :
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy [Spectrochim Acta A Mol Biomol Spectrosc] 2024 Sep 05; Vol. 325, pp. 125089. Date of Electronic Publication: 2024 Sep 05.
Publication Year :
2024
Publisher :
Ahead of Print

Abstract

The aim of the presented study was to qualitatively and quantitatively determine the chemical composition of oak bark extracts in order to gain insights into the effectiveness as alternative medication for various diseases. The primary emphasis was on developing a near-infrared spectroscopy (NIRS) method for precise quantification of two key polyphenolic compounds, specifically gallic acid and catechin, in form of a fast and non-destructive quality control. A comprehensive dataset consisting of 48 samples from various production batches was analyzed throughout this research. Qualitative analysis was conducted using High Performance Liquid Chromatography coupled with a mass detector (LC-MS) to separate and identify individual components of the oak bark extract. Individual components were identified, confirmed and quantified using existing literature combined with appropriate standard references. Whereas the predominant nature of identified substances was of polyphenolic nature. Furthermore, a semi-quantitative assessment was additionally performed for eight identified constituents to identify their chemical stability or possible occurring transformations during storage, utilizing quantification via internal standard met in order to identify fluctuations and chemical variability within oakbark, five key components were precisely quantified using LC-MS and corresponding standard substances. For this purpose, HPLC measurements coupled to an Ultraviolet/Visible (UV/Vis) detector were utilized as reference method. NIRS measurements were performed on a FT-NIR benchtop device in transmission mode. Partial least squares regression (PLSR) was then applied for model building, after identifying the optimal spectral pretreatment. Model evaluation was performed using leave-one-out-cross validation followed by evaluation of an independent test set. The model proved promising results for the quantification of gallic acid on the benchtop device with a standard error of cross validation (SECV) of 13.41 mg/L and a standard error of prediction (SEP) of 19.33 mg/L, while the absolute concentrations of the different batches analyzed ranged from 126.49 to 332.54 mg/L. For the quantification of catechin the SECV was reported at 23.61 mg/L, the SEP at 32.35 mg/L with sample concentrations falling between 13.50 and 383.72 mg/L. In this study, we introduce various analytical methodologies for both qualitative and quantitative assessment of a complex phytochemical sample, specifically oak bark extract, aimed at identifying and confirming the presence of active compounds within the extract.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1873-3557
Volume :
325
Database :
MEDLINE
Journal :
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Publication Type :
Academic Journal
Accession number :
39270369
Full Text :
https://doi.org/10.1016/j.saa.2024.125089