## 3 GC\(\times\)GC Separation  
Beer and wine contain many different volatile compounds. From the identification point of view, direct injection mass spectrometry, lacking separation, will result in a mixed MS signal of all the compounds. Hence, chromatography is used to separate VOCs before detection. Mass spectrometry (MS) can provide information for both identification and quantification in a single measurement. A gas chromatographic separation stage (GC) is commonly used for VOC analysis in beverages, and GC-MS is the technique of choice for most applications. According to the study purpose, there are two types of approaches: untargeted VOC profiling and targeted VOC quantification. A biological phenomenon's modeling must consider many possible chemical variables. Targeted VOC quantification only requires good separation in the specific chromatographic region. The fast analytical rate can be accomplished in the most efficient way via Fast GC, but not via GC\(\times\)GC. Fast GC application is characterized by a duration of less than 20 min [111]. GC\(\times\)GC is more suitable for non-targeted profiling, which focuses on the detection of as many VOCs as possible to obtain patterns or fingerprints of a specific beverage production process. For these reasons, including the unannotated peaks, it only requires semi-quantitative measurement of concentration. The profiling result is usually used to explore the similarities and differences between sample groups [112]. The research question could be, for example, whether there are any volatile biomarkers when a newly developed yeast is used in the fermentation. In this type of study, ensuring analytical coverage is essential for the reliability of the results. Better separation is a key factor in obtaining excellent analytical coverage. Beer and wine contain too many volatile compounds, which overcrowd the chromatogram of a traditional one-dimensional GC (1 DGC). When signals from VOCs overlap with each other, it is difficult to proceed with their identification and quantification. GC\(\times\)GC was developed to conquer this problem [113]. In GC\(\times\)GC analysis, the analytes are first separated on the first column. The elute of \({}^{1}\)D separation is continuously concentrated and injected into the \({}^{2}\)D column for further separation. The schematic diagram of GC\(\times\)GC is simply demonstrated in Figure 1. For a complete and detailed description of the instrument, please refer to a previous review [114].  
Compared with 1 DGC, GC\(\times\)GC method development requires more factors to be considered, such as column combination and sequence and modulator parameter adjustment. Additionally, there are secondary or higher-level interactions among these parameters. For this reason, the optimization of GC\(\times\)GC is complex, and each parameter cannot be simply optimized individually. Currently, most GC\(\times\)GC studies use the method adapted from 1 DGC or rely on the analytical setting recommended by the instrument manufacturer. In doing so, the high separation power of GC\(\times\)GC is not fully utilized to complete the separation of target analytes. Improper setup may lead to reduced separation power, co-eluting peaks, and distorted peaks, resulting in annotation and quantification errors. Optimizing GC\(\times\)GC is a challenge to the developer's knowledge of instrumentation and data handling capabilities.