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Quantification from highly drifted and overlapped chromatographic peaks using second-order calibration methods.

Enric Comas1, R Ana Gimeno, Joan Ferré

  • 1Department of Analytical Chemistry and Organic Chemistry, Rovira i Virgili University, Pl. Imperial Tarraco, 1, 43005-Tarragona, Spain.

Journal of Chromatography. A
|May 6, 2004
PubMed
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Second-order calibration algorithms like GRAM, PARAFAC, and MCR-ALS accurately quantify pesticides and phenolic compounds in wastewater, even with complex matrices. These methods offer improved precision and efficiency compared to traditional univariate calibration.

Area of Science:

  • Analytical Chemistry
  • Environmental Chemistry

Background:

  • Solid phase extraction (SPE) is common for pesticide and phenolic compound analysis in water but lacks selectivity.
  • Humic and fulvic acids in samples cause baseline drift and peak overlap, hindering accurate quantification by univariate calibration.

Purpose of the Study:

  • To compare the effectiveness of three second-order calibration algorithms (GRAM, PARAFAC, MCR-ALS) for analyzing pesticides and phenolic compounds in river and wastewater.
  • To evaluate the impact of time-shift errors on these algorithms and identify the most robust method.

Main Methods:

  • Utilized high performance liquid chromatography with a diode array detector (HPLC-DAD) to generate second-order data (response matrices).
  • Applied Generalized Rank Annihilation Method (GRAM), Parallel Factor Analysis (PARAFAC), and Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) for data analysis.

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  • Implemented a time-shift correction algorithm to improve peak alignment and prediction accuracy.

    • Main Results:

    • Second-order algorithms accurately quantified analytes, even with unresolved peaks, eliminating the need for direct peak area measurement.
    • MCR-ALS demonstrated the highest robustness against time-shift errors.
    • All three algorithms yielded predictions comparable to sulfite addition, but with significantly better precision (%R.S.D. = 3) than univariate calibration (%R.S.D. = 13).

    Conclusions:

    • Second-order calibration methods provide a more accurate and precise approach for quantifying target analytes in complex environmental samples compared to univariate calibration.
    • MCR-ALS is a particularly robust method for handling time-shift issues in chromatographic data.
    • These advanced algorithms offer time and resource savings by enabling quantification of overlapping peaks.