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- Title
Solving chromatographic challenges in comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry using multivariate curve resolution-alternating least squares.
- Authors
Parastar, Hadi; Radović, Jagoš; Bayona, Josep; Tauler, Roma
- Abstract
Multivariate curve resolution-alternating least squares (MCR-ALS) analysis is proposed to solve chromatographic challenges during two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) analysis of complex samples, such as crude oil extract. In view of the fact that the MCR-ALS method is based on the fulfillment of the bilinear model assumption, three-way and four-way GC × GC-TOFMS data are preferably arranged in a column-wise superaugmented data matrix in which mass-to-charge ratios ( m/ z) are in its columns and the elution times in the second and first chromatographic columns are in its rows. Since m/ z values are common for all measured spectra in all second-column modulations, unavoidable chromatographic challenges such as retention time shifts within and between GC × GC-TOFMS experiments are properly handled. In addition, baseline/background contributions can be modeled by adding extra components to the MCR-ALS model. Another outstanding aspect of MCR-ALS analysis is its extreme flexibility to consider all samples (standards, unknowns, and replicates) in a single superaugmented data matrix, allowing joint analysis. In this way, resolution, identification, and quantification results can be simultaneously obtained in a very fast and reliable way. The potential of MCR-ALS analysis is demonstrated in GC × GC-TOFMS analysis of a North Sea crude oil extract sample with relative errors in estimated concentrations of target compounds below 6.0 % and relative standard deviations lower than 7.0 %. The results obtained, along with reasonable values for the lack of fit of the MCR-ALS model and high values of the reversed match factor in mass spectra similarity searches, confirm the reliability of the proposed strategy for GC × GC-TOFMS data analysis. [Figure not available: see fulltext.]
- Subjects
PETROLEUM chemicals; CHROMATOGRAPHIC analysis; GAS chromatography/Mass spectrometry (GC-MS); PETROLEUM prospecting; LEAST squares; STANDARD deviations
- Publication
Analytical & Bioanalytical Chemistry, 2013, Vol 405, Issue 19, p6235
- ISSN
1618-2642
- Publication type
Article
- DOI
10.1007/s00216-013-7067-y