A Practical Framework Integrating Two‐Way Chemometric Methods With Three‐Way Ones for the Analysis of Hyphenated Chromatographic Data of Complex Systems
ABSTRACT Hyphenated chromatographic techniques are widely used to analyze and characterize complex samples. Chemometric methods are generally needed to extract the qualitative and quantitative information of the target analytes from complex hyphenated chromatographic data. However, neither two‐way n...
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Veröffentlicht in: | Journal of chemometrics 2024-12, Vol.38 (12), p.n/a |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | ABSTRACT
Hyphenated chromatographic techniques are widely used to analyze and characterize complex samples. Chemometric methods are generally needed to extract the qualitative and quantitative information of the target analytes from complex hyphenated chromatographic data. However, neither two‐way nor three‐way chemometric methods are efficient enough in analyzing hyphenated chromatographic data with both severe peak overlapping and retention time shift across samples. To address this issue, a practical framework was proposed herein. It consists of three chemometric algorithms, that is, (1) “fix‐sized moving window evolving target spectral projection” for locating the possible peak positions of the target analytes, (2) “target identification based on singular value comparison” for determining whether the identified peaks are indeed the chromatographic peaks of the target analytes, and (3) “fix‐sized moving window evolving trilinear decomposition” for obtaining the quantitative results of the target analytes. Experimental results on the GC‐MS data sets of mixture samples of 10 compounds verified that the proposed framework could deal with the problems of both severe peak overlapping and retention time shift across samples. The proposed framework has the advantages of simplicity in concept, easy implementation, and good performance and hence is expected to be a competitive alternative to existing methods for the analysis of hyphenated chromatographic data of complex samples. |
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ISSN: | 0886-9383 1099-128X |
DOI: | 10.1002/cem.3625 |