Issue 24, 2016

A chemometrics-assisted excitation–emission matrix fluorescence method for simultaneous determination of arbutin and hydroquinone in cosmetic products

Abstract

A fast analytical method that combines second-order calibration based on alternating trilinear decomposition (ATLD) algorithm with excitation–emission matrix (EEM) fluorescence technique is proposed to mathematically separate the overlapped spectra and simultaneously quantify arbutin (AR) and hydroquinone (HQ) in cosmetic products. This method inherits the merit of high sensitivity of traditional fluorescence and fully realizes the “second-order advantage”. For AR and HQ, the calibration ranges are 40.00–400.00 and 20.00–200.00 ng mL−1, respectively. The limits of detection for both analytes are in the range of 1.51–4.01 ng mL−1. The proposed method could be applied to diluted samples of different cosmetic products with satisfactory results. The actual concentrations of AR in the tested cosmetic products are found to be in the allowable concentration range (7%); while, the prohibited skin whitening agent HQ is detected in lotion. The contents of AR and HQ in the tested cosmetic products obtained by the proposed method are also in accordance with those of the validated high-performance liquid chromatographic method. These satisfactory results indicate that the proposed method has the potential to accurately quantify AR and HQ in complex matrices containing uncalibrated interferents, and shows promise as a reliable tool for quality monitoring of cosmetic products.

Graphical abstract: A chemometrics-assisted excitation–emission matrix fluorescence method for simultaneous determination of arbutin and hydroquinone in cosmetic products

Article information

Article type
Paper
Submitted
21 Mar 2016
Accepted
24 May 2016
First published
25 May 2016

Anal. Methods, 2016,8, 4941-4948

A chemometrics-assisted excitation–emission matrix fluorescence method for simultaneous determination of arbutin and hydroquinone in cosmetic products

L. Zhu, H. Wu, L. Xie, H. Fang, S. Xiang, Y. Hu, Z. Liu, T. Wang and R. Yu, Anal. Methods, 2016, 8, 4941 DOI: 10.1039/C6AY00821F

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