THE NEW APPROACHES TO IDENTIFICATION OF TINCTURES AND MEDICINAL PLANTS
DOI:
https://doi.org/10.22159/ijap.2024v16i2.49780Keywords:
Medicinal plants and tinctures, Identification, Spectral analysis, Principal component analysisAbstract
Objective: The objective of this study is to develop methods for identifying herbal medicines and tinctures by processing spectral results across a wide range of wavelengths using principal component analysis (PCA).
Methods: Medicinal plants and tinctures of valerian, motherwort, and hawthorn have been analyzed using UV spectrophotometry, spectrofluorimetry, ATR FTIR spectrometry, and X-ray fluorescence spectrometry. PCA was used to process the results of spectral analysis. Statistical processing of spectral results was carried out using the OriginPro program (OriginLab Corporation, USA, 2021).
Results: For herbal medicines with sedative, hypotensive, and cardiotonic effects, spectral data libraries have been created in the following dimensions: UV spectrophotometry with 1800 absorption units (Ai), spectrofluorimetry with 4010 fluorescence intensity units (Ii), IR spectroscopy with a light transmittance of 50250 units (Ti), and X-ray fluorescence spectrometry with an intensity of 1568 (Ii). These libraries were used as the primary matrices for PCA. Visualization of the PCA results was done using a scores plot and a loadings plot, which illustrate the contribution of each principal component (PC) to the PCA model. After performing chemometric processing on the original spectral results, it was discovered that samples belonging to the same botanical genus occupy distinct and compact regions in two-dimensional or three-dimensional space. Unknown plant samples (blind samples) and samples of other botanical species were successfully tested using new method.
Conclusion: For the first time, tinctures and medicinal plants were identified based on their botanical genus using spectral techniques coupled with principal component analysis, eliminating the need for a chemical reference substance.
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Copyright (c) 2024 TATIANA V. PLETENEVA, DAIAANA D. OGOTOEVA, OLGA V. LEVITSKAYA, DARIA A. GALKINA , ELENA V. USPENSKAYA, ANTON V. SYROESHKIN
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