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Advanced data handling techniques, specifically chemometric data analysis tools, have become an integral part of successful implementation of comprehensive two-dimensional (2D) gas chromatography (GC×GC) for the analysis of complex samples. When GC×GC is coupled with a multichannel detector such as a time-of-flight–mass spectrometer (TOFMS), enormous data sets are produced that require chemometric methods to glean meaningful information. Chemometric methods utilize linear algebra and statistical concepts to reveal underlying chemical relationships in the data that are related to the experimental design. However, the successful application of chemometrics is not without its challenges in order to reap the rewards. Since there are a myriad of chemometric methods, in this chapter we focus on the operation of the most common tools: deconvolution, pattern recognition, discovery-based analysis, and property prediction methods. Considerations of experimental design, preprocessing, data structure, and analysis goals are included. Current applications of these advanced data handling methods are demonstrated to highlight the ability to obtain useful information from complex samples. |
