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Chemometrics

Enhanced Selectivity of Ultraviolet-Visible Absorption Spectroscopy with Trilinear Decomposition on Spectral pH Measurements for the Interference-Free Determination of Rutin and Isorhamnetin in Chinese Herbal Medicine

, , , , , , , & ORCID Icon show all
Pages 2750-2768 | Received 29 Dec 2020, Accepted 07 Feb 2021, Published online: 24 Feb 2021
 

Abstract

Ultraviolet-visible absorption spectrometry is used for the determination of many inorganic, organic, and biological species. However, poor selectivity limits its applications for quantitative analysis in complex mixtures. In this work, its mathematical selectivity was explored using trilinear decomposition on spectral-pH measurements for the selective determination of two flavonoids in three Chinese herbal medicines. Through introducing a pH mode, second-order spectral pH data were constructed per sample. By using trilinear decomposition on the calibration and prediction samples, the rutin signals were extracted from lonicerae japonicae flos, perillae folium, and perillae fructus samples, respectively. Novel second-order calibration was developed for interference-free determination of rutin in these medicines followed by univariate regression of the decomposed intensity versus concentration. The predicted 95% confidence intervals for the concentration of rutin in these samples were 5.19 ± 0.16, 5.81 ± 0.10, and 7.00 ± 0.36 μg mL−1, respectively. These results were validated by high performance liquid chromatography (HPLC). Similarly, interference-free determination of isorhamnetin was achieved in these materials. By increasing the selectivity of ultraviolet-visible spectroscopy with trilinear decomposition, the requirements for sample preparation and chemical separation are reduced. The developed spectral pH second-order calibration allows direct analysis of complex samples by ultraviolet-visible absorption spectrometry due to the mathematical selectivity.

Disclosure statement

No potential conflict of interests was reported by the author(s).

Additional information

Funding

This work was supported by the Science and Technology Project of Guizhou Province by grant numbers 20177293, 20175788, 20191070, and 20204Y133; the Natural Science Project of Department of Education of Guizhou Province by grant number 2017116; the Scientific Research Foundation for Introduced Talent of Guizhou University by grant numbers 201564 and 201769; and the Science and Technology Project of Guizhou Tobacco Company by grant numbers 201822 and 201922.

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