Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful technique for separating, identifying, and quantifying volatile and semi-volatile compounds in complex samples. Typically, mass spectrometry (MS) is used for peak identification in GC×GC, but relying solely on MS library comparison can have limitations, especially for isomers with similar mass spectra. Additionally, optimizing the separation conditions to achieve improved resolution in GC×GC can be challenging.

This research presents a computational approach to simulate GC×GC results using a calculation method based on first- and second-dimensional retention indices (1I and 2I). The simulation includes the prediction of the retention times (1tR and 2tR) and contour plots of samples from GC×GC-MS data. For cases where 1tR and 2tR data of alkane references (1tR(n) and 2tR(n)) are not available, the following steps are applied: curve fitting based on the van den Dool and Kratz relationship to simulate 1tR(n) using a training set of volatile compounds with their experimental 1tR data; or simulation of 2tR(n) at different 1tR(n) values to construct isovolatility curves based on a nonlinear equation with six constants, obtained through curve fitting using the experimental 2tR data of the training set.

The approach was applied to simulate results for 622 compounds in various samples, including saffron, Boswellia papyrifera, acacia honey, incense powder/smoke, and perfume. The simulated results were compared with experimental data, showing good correlation with R2 values, ranging from 0.975 to 0.999 for 1tR and 0.449 to 0.992 for 2tR. The approach was then applied to propose 10 compounds that may have been incorrectly identified in the literature based on significant differences between the simulated and experimental 2tR values.