Comparison of partial least squares and artificial neural network chemometric techniques in determination of sulfamethoxazole and trimethoprim in pharmaceutical suspension by ATR–FTIR spectrometryReport as inadecuate




Comparison of partial least squares and artificial neural network chemometric techniques in determination of sulfamethoxazole and trimethoprim in pharmaceutical suspension by ATR–FTIR spectrometry - Download this document for free, or read online. Document in PDF available to download.

Spectroscopy - Volume 26 2011, Issue 2, Pages 105-114



Department of Chemistry, Faculty of Science, Imam Khomeini International University, Qazvin, Iran

Department of Chemistry, Faculty of Science, Zanjan University, Zanjan, Iran

Department of Chemistry and Polymer Laboratory, Engineering Research Institute, Tehran, Iran



Copyright © 2011 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Partial Least Square PLS and Artificial Neural Network ANN techniques were compared during development of an analytical method for quantitative determination of sulfamethoxazole SMX and trimethoprim TMP in Co-Trimoxazole

suspension. The procedure was based on Attenuated Total Reflectance Fourier Transform Infrared ATR–FTIR spectrometry. The 800–2500 cm

spectral region was selected for quantitative analysis. R

and relative error of prediction REP in PLS technique were 0.989, 2.128 and 0.986, 1.381 for SMX and TMP, respectively. These statistical parameters were improved using the ANN models considering the complexity of the sample and the speediness and simplicity of the method. R

and RMSEC in modified method were 0.997, 1.064 and 0.997, 0.634 for SMX and TMP, respectively.





Author: M. Khanmohammadi, N. Dallali, A. Bagheri Garmarudi, M. Zarnegar, and K. Ghasemi

Source: https://www.hindawi.com/



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