## 3 Identification and Quantification of Volatile and Semi-Volatile Compounds in Sparkling Wines
### Analytical Techniques
CI-ELLSA (Competitive Indirect Enzyme-Linked Lectin Sorbent Assay), used to quantify specific protein groups [125]. SDS-PAGE (Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis), a method for separating proteins and glycoproteins based on molecular weight [125]. Size-Exclusion Fast Protein Liquid Chromatography (FPLC), applied by [PERSON], [PERSON] et al. [29] and [PERSON], [PERSON] et al. [126] for detailed protein profiling. Folin-Ciocalteu assay, used for determining total phenol and protein content [37; 80; 112]. Antioxidant capacity is another extensively explored aspect in sparkling wine research. Techniques commonly used include FRAP (Ferric Reducing Antioxidant Power) [37; 111; 124], DPPH (2,2-diphenyl-1-picryhydrazyl radical scavenging assay) [52; 80; 111; 124], and MRSA (Hydroxyl Radical Scavenging Activity) [37; 52]. For thiol determination, a DTDP (4,4\({}^{\prime}\)-dithiodipyridine) method was employed [13]. Regarding sparkling properties, foamability is defined as a quality attribute. Studies have assessed how various production variables influence foam formation, using the Mosalux technique, which quantifies foam height and stability under standardized conditions [17; 18; 125; 127; 128; 129; 66; 129]. For elemental sparkling wine characterization, [PERSON], [PERSON] et al. [36] employed the PIXE (Particle-Induced X-ray Emission) technique to study the elemental transfer between cork stoppers and white sparkling wine over 18 months [36]. In the oenology field, sensory analysis is usually imperative to assess sparkling wine quality. Evaluations are typically conducted under blind testing, conducted by trained male and female panelists. The professionals rate different attributes such as aroma, taste, mouthfeel, bubble, oxidation, and overall balance. This method allows objective comparisons between chemical analyses. Considering innovative methodologies, [PERSON], [PERSON] et al. [130] introduced a novel sensory methodology to assess the aging potential of wine, a concept traditionally described subjectively by professionals. Unlike conventional one-dimensional approaches, this method uses a three-dimensional sensory framework (incorporating time, quality, and potential). The approach, known as \"projective categorization,\" integrates multiple dependent variables and offers a visual tool for evaluators to project a wine's developmental trajectory. This investigation was applied to 33 Champagne reserve wines aged from 1 to 29 years, and the method demonstrated strong discriminatory power regarding aging and provided statistical insight into judge consensus and performance [130]. The combination of instrumental and sensory data, along with emerging strategies such as machine learning, is crucial to better understand the volatile aroma compounds that contribute to the complexity of sparkling wine matrices. In recent years, systematic reviews and meta-analyses have helped consolidate the current knowledge on aroma-active compounds in alcoholic beverages, including sparkling wines [131; 132]. These studies provide a broader framework for selecting key analytical targets and interpreting the interactions among volatile compounds that shape wine aroma [131; 132].