# Analysis of Potent Odour-Active Volatile Thioids in Foods and Beverages with a Focus on Wine
## 4 Analytical Instrumentation
### Matrix Effects and Quantitative Analysis  
With the advances in chromatography and MS capabilities, instrumentation with higher separation ability and detection sensitivity has become more available, which leads to a greater number of analytical methods being reported for volatile thiols in more foods and beverages. However, matrix effects in trace analysis have been noted in modern analytical methods that were developed for agricultural samples [76]. In addition, the concentrations of these unstable compounds are at trace to ultra-trace levels and in complex matrices, so their quantitative analysis has to be treated with great care to avoid inaccurate or inconclusive outcomes regarding these potent odour-active molecules. Matrix effects should be critically evaluated when developing quantitative methods to achieve accurate and reliable results. It is well known that matrix interferences have significant impacts on the extraction, separation, detection, and consequently the quantitation of analytes. This is of particular importance, given both the reactivity and trace concentrations of potent volatile thiols. Matrix effects have been clearly noticed and explored during method development for volatile thiol analysis [18; 41]. One way to distinguish the extent of matrix effects is to compare the slopes of calibration curves that have been obtained from different matrices [18; 31]. While using this approach, a matrix effect was evidently observed in model wine vs. real wines [18; 41] and oxidised vs. non-oxidised wines [30], with various impacts during the extraction, separation, or detection steps potentially leading to differences in the results. For instance, undiluted solvent-assisted flavour evaporation (SAFE) distillate [23], competitive absorption on an HS-SPME fibre [25], or ESI-MS signal enhancement/suppression [77] could cause large matrix effects. Even when using matrix-matched calibration approaches, the choice of IS can be extremely important in minimising or compensating for matrix effects. Many compounds with similar properties to volatile thiols that showed a negligible matrix effect have been suggested as internal standards, such as 4-methoxy-2-methyl-2-mercaptoethanoluate [22] and 6-sulfanylhexan-1-ol (6-SH) [60]. Even so, stable isotope labelled IS are the best option in a stable isotope dilution assay (SIDA), which is arguably the most accurate analytical approach, and, in most cases, can efficiently eliminate a matrix effect by compensating extraction, separation, and detection variabilities due to the almost identical properties between analytes and their stable isotope, labelled analogues [78]. SIDA has been widely employed for LC-MS [7; 36; 41] and GC-MS [19; 25; 27; 30; 31; 32; 33] methods for volatile thiols analysis, and both \({}^{2}\)H [7; 19; 25; 30; 32; 33; 36; 41] and \({}^{13}\)C labelled [27] internal standards have been used in various cases (Table 2, Entries with bolded numbers). Typically, the ideal degree of atom labelling should be greater than two [76], but d\({}_{2}\)-3-SHA [36] and d\({}_{2}\)-3-SH [30; 36] have been reported in a few cases as stable isotope labelled IS. Additionally, the elution of stable isotope labelled IS generally occurs slightly earlier than analytes depending on the extent of isotope incorporation, and such examples can be seen for both GC [31; 32] or LC [7; 41]. However, the co-elution of analytes and stable isotope labelled IS would be desirable to completely compensate for matrix effects [78]. Indeed, SIDA does not guarantee the complete elimination of matrix effects for thiol analysis in wine. It has been shown that deuterated IS spiked into an oxidised wine somehow underwent a faster oxidation than native analyte, which led to a persistent matrix effect [30]. On the other hand, phenols or pigments in red wines have a potentially significant impact on LC-MS/MS signal responses, as evident when comparing calibration curve slopes from different wine and model wine matrices [41].