Multidimensional Gas Chromatography: Advances in Instrumentation, Chemometrics, and Applications

Prebihalo, Sarah E.; Berrier, Kelsey L.; Freye, Chris E.; Bahaghighat, H. Daniel; Moore, N. R.; Pinkerton, David K.; Synovec, Robert E.

doi:10.1021/acs.analchem.7b04226

Cited by 167 publications

(110 citation statements)

References 227 publications

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“…Separation of chiral compounds is gaining interest [27]. Multidimensional gas chromatography allows 2-dimensional separations, will require chemometrics and can be combined with MS [28].…”

Section: Highlights Of Research In Analytical Chemistry -2018mentioning

confidence: 99%

European analytical column number 47

2019

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“…Separation of chiral compounds is gaining interest [27]. Multidimensional gas chromatography allows 2-dimensional separations, will require chemometrics and can be combined with MS [28].…”

Section: Highlights Of Research In Analytical Chemistry -2018mentioning

confidence: 99%

European analytical column number 47

2019

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“…On the one hand, this makes possible to differentiate between samples using established pattern recognition or classification methods, such as PCA or PLS‐DA multivariate approaches. On the other hand, the quantitative information can be used to obtain possible markers related to the factor under study using methods such as statistical inference tests or the selected VIP variables obtained in the PLS‐DA model …”

Section: Peak Detection and Profilingmentioning

confidence: 99%

“…The PARAFAC method has been widely used for the analysis of multidimensional chromatographic data and, in particular, the work done by Synovec and collaborators in the GC × GC‐MS data processing can be highlighted . In this data approach, it is assumed that the data obtained from GC × GC‐MS instruments behave in a multilinear way, which is not always the case.…”

Section: Peak Detection and Profilingmentioning

confidence: 99%

“…PARAFAC‐based methods have been applied in the study of multidimensional data in several fields of research. In the case of omic studies, these examples are found mainly in the field of metabolomics using GC × GC‐MS . For example, the work of Snyder et al.…”

Section: Peak Detection and Profilingmentioning

confidence: 99%

“…Therefore, it is mandatory to check if sample profiles in the chromatographic dimensions are constant when considering different modulations within a sample and between different samples. These profiles are characterized by the retention time and the peak shape observed for the same compound in different modulations and samples . The fulfillment of this same behavior condition (known as multilinearity condition, e.g., trilinearity for second‐order data or quadrilinearity for third‐order data) implies that a component (sample profile) of a higher‐order data structure (second‐order or more) can be described mathematically as a linear function of chromatographic and spectral profiles in the different data modes .…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography

et al. 2018

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The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis.

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Comprehensive Two‐dimensional Chromatography: An Insight into the Analysis of Food and Food Products

Zoccali

Cacciola

Arena

et al. 2021

Encyclopedia of Analytical Chemistry

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Food chemistry is a branch of food science involved in the evaluation of the composition along with chemical, physical, and functional properties of foods and food products during their different processing stages and storage periods. Chromatographic methods are the most employed analytical techniques for their analysis. However, when a single chromatographic method is not sufficient for providing satisfactory results, more advanced and performant strategies need to be considered. In this regard, comprehensive two‐dimensional chromatography, involving two different separation modes, turned out to be a powerful analytical strategy for the analysis of very complex food samples. This article aims to highlight how the hyphenation of two single separation systems could be a valuable tool for handling such complex samples. The first part deals with general considerations about the technique including the design of modulation interfaces, whereas in the second part selected applications to food analytes of interest, analyzed by both comprehensive two‐dimensional liquid and gas chromatography, are reported and discussed.

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Multidimensional Gas Chromatography: Advances in Instrumentation, Chemometrics, and Applications

Cited by 167 publications

References 227 publications

European analytical column number 47

European analytical column number 47

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography

Comprehensive Two‐dimensional Chromatography: An Insight into the Analysis of Food and Food Products

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