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Analytica
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  • Open Access

16 December 2025

Chemometric Approaches for Identification of Herbal Medicinal Products

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1
Department of Pharmaceutical and Toxicological Chemistry, Medical Institute, Рeoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Street, Moscow 117198, Russia
2
Department of Medical and Pharmaceutical Chemistry, Scientific and Educational Institute of Pharmacy Named After K.M. Lakin, Russian University of Medicine, 4 Dolgorukovskaya St, Moscow 127006, Russia
3
Department of Pharmacology and Pharmacy, Institute of Medicine, M.K. Ammosov North-Eastern Federal University, (NEFU), 58 Belinsky Street, Yakutsk 677027, Russia
4
V.A. Frolov Department of General Pathology and Pathological Physiology, Medical Institute, Рeoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Street, Moscow 117198, Russia
This article belongs to the Special Issue New Analytical Techniques and Methods in Pharmaceutical Science

Abstract

Quality control of herbal medicinal products (HMPs) is challenging due to their multicomponent composition. For most HMPs, chemical reference standards (CRSs) required for traditional chromatographic and spectral analyses are unavailable. According to USP and Ph. Eur., an exception is valerian tincture, for which highly specific CRSs have been developed. The aim of this study was to use principal component analysis (PCA) and the novel two-dimensional diffuse laser scattering (2D-DLS) method to identify HMPs and their aqueous-ethanolic extracts according to their botanical genera without relying on specific marker compounds. Spectral data were compiled into an extensive library covering a wide wavelength range—from 0.02 nm to 15,000 nm. PCA of the spectral data (UV spectrophotometry, fluorimetry, FTIR spectroscopy, and X-ray diffraction) enabled clustering of samples by individual botanical genera. The most significant information for sample differentiation was provided by wavenumbers of 1400, 1180, and 931 cm−1 in the IR spectra and wavelengths of 450 nm and 672 nm in the UV and fluorescence spectra, respectively. During model cross-validation, all “blind samples” were correctly classified by botanical genus, achieving a non-error rate (NER) of 100%. Furthermore, the unique 2D-DLS method was used to rapidly identify tinctures without opening the glass bottles.

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