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Quantification of target components in complex mixtures using alternative moving window factor analysis and two-step

Zhong-Da Zeng1, Yi-Zeng Liang, Zhi-Hong Jiang

  • 1College of Chemistry and Chemical Engineering, Research Center of Modernization of Chinese Medicines, Central South University, Changsha 410083, PR China.

Talanta
|March 29, 2008
PubMed
Summary
This summary is machine-generated.

A new two-step iterative constraint method (TICM) enables independent quantification of chemical components in complex mixtures. This approach simplifies analysis for herbal medicines, metabonomics, and systems biology.

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Area of Science:

  • Analytical Chemistry
  • Chemometrics

Background:

  • Alternative moving window factor analysis (AMWFA) facilitates component comparison but requires pure spectra for quantification.
  • Existing methods face challenges in quantifying individual analytes within complex mixtures.

Purpose of the Study:

  • To develop a novel method for independent quantification of target analytes in complex mixtures.
  • To improve the analysis of multi-component systems in fields like herbal medicine and metabonomics.

Main Methods:

  • A two-step iterative constraint method (TICM) was developed for component isolation and quantification.
  • Employed constraints include non-negative, single-peaked profiles, and zero concentration outside elution windows.
  • Simplified complex mixtures into sub-systems for processing with AMWFA, leveraging bilinear data properties.

Main Results:

  • TICM successfully mined pure chromatographic profiles from complex mixtures.
  • Demonstrated good performance on simulated LC-DAD data and GC-MS data of ginseng and herb samples.
  • Achieved effective purification of targets from interferers.

Conclusions:

  • TICM offers an efficient approach for qualitative and quantitative analysis of complex multi-component systems.
  • The method addresses urgent analytical needs in herbal medicine, metabonomics, and systems biology.
  • TICM enhances the capabilities of AMWFA for analyzing intricate chemical mixtures.