Effect of data preprocessing methods in near-infrared diffuse reflectance spectroscopy for the determination of the active compound in a pharmaceutical preparation

M. Blanco, J. Coello, H. Iturriaga, S. Maspoch, C. De La Pezuela

Research output: Contribution to journalArticleResearchpeer-review

66 Citations (Scopus)

Abstract

Near-infrared diffuse reflectance spectroscopy (NIRS) with a fiber-optic probe was used for the determination of the active compound in a commercial pharmaceutical preparation. In order to reduce the strong scatter in the spectra and prevent scatter-induced changes in measurements from prevailing over concentration-induced changes, several data preprocessing methods were tested: normalization, derivatives, multiplicative scatter correction, standard normal variate, and detrending. The effectiveness for reducing the scattering of each data preprocessing was assessed, and the best results were obtained with the use of the second derivative. The effect of the treatments on the quantitation of the active compound by partial least-squares regression (PLSR) was studied, similar results being obtained in all cases, with a relative standard error of prediction lower than 1.55%.
Original languageEnglish
Pages (from-to)240-246
JournalApplied Spectroscopy
Volume51
Issue number2
DOIs
Publication statusPublished - 1 Jan 1997

Keywords

  • Data preprocessing
  • Near-infrared spectroscopy
  • Partial least-squares regression
  • Scatter correction

Fingerprint Dive into the research topics of 'Effect of data preprocessing methods in near-infrared diffuse reflectance spectroscopy for the determination of the active compound in a pharmaceutical preparation'. Together they form a unique fingerprint.

Cite this