Use of continuous wavelet transform approach for simultaneous quantitative determination of multicomponent mixture by UV-Vis spectrophotometry

Mahmoud Reza Sohrabi; Vahid Mirzabeygi; Mehran Davallo

doi:10.1016/j.saa.2018.05.020

Use of continuous wavelet transform approach for simultaneous quantitative determination of multicomponent mixture by UV-Vis spectrophotometry

Spectrochim Acta A Mol Biomol Spectrosc. 2018 Aug 5:201:306-314. doi: 10.1016/j.saa.2018.05.020. Epub 2018 May 8.

Authors

Mahmoud Reza Sohrabi¹, Vahid Mirzabeygi², Mehran Davallo²

Affiliations

¹ Department of Chemistry, Faculty of Chemistry, Azad University, North Tehran Branch, P.O. Box 1913674711, Tehran, Iran. Electronic address: Sohrabi.m46@yahoo.com.
² Department of Chemistry, Faculty of Chemistry, Azad University, North Tehran Branch, P.O. Box 1913674711, Tehran, Iran.

PMID: 29763824
DOI: 10.1016/j.saa.2018.05.020

Abstract

In the present paper, a multicomponent analysis approach based on spectrophotometry method was developed for simultaneous determination of Guaifenesin (GU), Chlorpheniramine (CHL) and Pseudoephedrine (PSE) without any separation steps. The method under study is signal processing method based on Continuous Wavelet Transform (CWT) coupled with zero cross point technique. In this paper, CWT method was tested by synthetic ternary mixtures and was applied to the commercial cough syrup as a real sample and assessed by applying the standard addition technique. For demonstrate the accuracy of the results, other applications of signal processing, such as Derivative Transform (DT), Partial Least Squares (PLS) regression and Principal Components Regression (PCR) were used as comparative methods. Afterwards, the obtained results from analyzing the cough syrup by all methods were compared to the High-Performance Liquid Chromatography (HPLC) as a reference method. One-way analysis of variance test at 95% confidence level showed no significant differences between CWT and other applications.

Keywords: Continuous wavelet transform; Derivative transform; Multicomponent measurement; Partial least squares regression; Principal components regression; Spectrophotometry.