2011
DOI: 10.1016/j.chroma.2011.03.004
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Analysis of petroleum compositional similarity using multiway principal components analysis (MPCA) with comprehensive two-dimensional gas chromatographic data

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Cited by 58 publications
(37 citation statements)
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“…While the eye is quite adept at noticing pattern differences in such dense data, and simple manipulation such as difference and addition chromatograms are useful for determining pattern changes between single chromatograms, the consideration of the changes in this many chromatograms must utilize multivariate methods (Nelson et al, 2006;Ventura et al, 2011;Wardlaw et al, 2008). This is especially important as it is a well-accepted of petroleum analysis that ratios of chromatographic peaks are often more illuminating than peak volumes or heights themselves (Wang and Stout, 2006).…”
Section: Introductionmentioning
confidence: 97%
“…While the eye is quite adept at noticing pattern differences in such dense data, and simple manipulation such as difference and addition chromatograms are useful for determining pattern changes between single chromatograms, the consideration of the changes in this many chromatograms must utilize multivariate methods (Nelson et al, 2006;Ventura et al, 2011;Wardlaw et al, 2008). This is especially important as it is a well-accepted of petroleum analysis that ratios of chromatographic peaks are often more illuminating than peak volumes or heights themselves (Wang and Stout, 2006).…”
Section: Introductionmentioning
confidence: 97%
“…However, in order to release its full potential, innovative chemometric techniques that can handle the vast amount of data provided by GC Â GC become indispensable (Pierce et al, 2008). For this purpose, multivariate resolution techniques can be used (Ventura et al, 2011), although their performance and reliability depends on the reproducibility of the retention times in both dimensions during GC Â GC analysis. The problem of in-between and within run retention time shifting was addressed by a number of methods (Skov et al, 2009;Vial et al, 2009;Zhang et al, 2008;Van Mispelaar et al, 2003;Fraga et al, 2001), but it is still not fully resolved and is a limiting factor that needs further research.…”
Section: Oil Fingerprinting and Weathering Effectsmentioning
confidence: 99%
“…Groger and Zimmermann [36] used t-tests to select significant datapoint features from selected channels of GC × GC-TOFMS data for partial least-squares (PLS) discriminant analysis (DA). Ventura et al [57] recently used multiway PCA on GC × GC-FID data for maltene fractions of crude oils.…”
Section: Datapoint Featuresmentioning
confidence: 99%