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Gas chromatography (GC) is a technique for separating and analyzing volatile compounds in a sample. Its primary purpose is to identify and quantify components in complex mixtures, making it essential in fields such as environmental analysis, pharmaceuticals, and petrochemicals. GC is also called vapor-phase chromatography (VPC) or gas-liquid partition chromatography (GLPC).
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Coping with matrix effects in headspace solid phase microextraction gas chromatography using multivariate calibration

Vicente Ferreira1, Paula Herrero1, Julián Zapata2

  • 1Laboratory for Aroma Analysis and Enology, Aragón Institute of Engineering Research (I3A), Department of Analytical Chemistry, Faculty of Sciences, University of Zaragoza, 50009 Zaragoza, Spain.

Journal of Chromatography. A
|July 14, 2015
PubMed
Summary

Solid-phase microextraction (SPME) is sensitive to experimental factors. A multivariate strategy using 13 internal standards effectively minimizes matrix effects, enabling reliable quantification of 47 compounds.

Keywords:
HS-SPME-GC–MSMultivariate calibrationPLSRVolatile compounds

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Area of Science:

  • Analytical Chemistry
  • Chemometrics
  • Food Science

Background:

  • Solid-phase microextraction (SPME) is highly sensitive to experimental parameters influencing distribution coefficients.
  • Matrix effects in SPME can significantly impact the accuracy of analyte quantification.
  • Developing robust methods to mitigate these effects is crucial for reliable analysis.

Purpose of the Study:

  • To quantify the influence of experimental parameters on SPME.
  • To design a multivariate strategy using internal standards to minimize matrix effects.
  • To develop a reliable method for quantifying multiple compounds in complex matrices.

Main Methods:

  • Preparation of synthetic wine samples with controlled variations in ethanol, non-volatile, and volatile constituents using a factorial design.
  • Analysis using ANOVA to determine the significance of matrix effects and constituent contributions.
  • Implementation of two multivariate calibration strategies: Multivariate Internal Standards (MIS) and direct calibration using Partial Least Square Regression (PLSR) with 13 internal standards.

Main Results:

  • Matrix effects were found to be significant and additive, primarily driven by major volatile constituents, even with matrix dilution.
  • A single internal standard was insufficient for robust calibration of all analytes (15 out of 47).
  • Multivariate calibration strategies using 13 internal standards successfully addressed matrix effects, enabling reliable quantification.

Conclusions:

  • Major volatile constituents are the dominant factor contributing to matrix effects in SPME of wine.
  • Multivariate calibration strategies, particularly MIS and direct PLSR with multiple internal standards, are effective in overcoming SPME matrix effects.
  • A single, fully automated method allows for the reliable quantification of 47 compounds with uncertainties below 15%.