Metabolomic-Based Strategy for Fingerprinting of <i>Sambucus nigra</i> L. Berry Volatile Terpenoids and Norisoprenoids: Influence of Ripening and Cultivar

The integration of plant metabolomics to support preharvest fruit development studies can provide important insights into the biochemical mechanisms involved and lately support producers on harvesting management. A metabolomic-based strategy for fingerprinting of volatile terpenoids and norisoprenoids from <i>Sambucus nigra</i> L. berries from three cultivars, through ripening, was established. From 42 monoterpenic, 20 sesquiterpenic, and 14 norisoprenoid compounds, 48 compounds are reported for the first time as <i>S. nigra</i> berries components. Chemometric tools revealed that ripening was the factor that influenced more the volatile fraction profile and physicochemical parameters (pH, TS, and TSS), followed by cultivar. For the unripe stages, a higher overall content of the studied metabolites was observed, which gradually decreased over the ripening stages, being consistent for the three cultivars. These trends were mainly ruled by limonene, <i>p</i>-cymene, aromadendrene, β-caryophyllene, and dihydroedulan, which might therefore be used by producers as an additional simple decision making tool in conjunction with physicochemical parameters

In-depth search focused on furans, lactones, volatile phenols, and acetals as potential age markers of Madeira wines by comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry combined with solid phase microextraction

The establishment of potential age markers of Madeira wine is of paramount significance as it may contribute to detect frauds and to ensure the authenticity of wine. Considering the chemical groups of furans, lactones, volatile phenols, and acetals, 103 volatile compounds were tentatively identified; among these, 71 have been reported for the first time in Madeira wines. The chemical groups that could be used as potential age markers were predominantly acetals, namely, diethoxymethane, 1,1-diethoxyethane, 1,1-diethoxy-2-methyl-propane, 1-(1-ethoxyethoxy)-pentane, trans-dioxane and 2-propyl-1,3-dioxolane, and from the other chemical groups, 5-methylfurfural and cis-oak-lactone, independently of the variety and the type of wine. GC × GC-ToFMS system offers a more useful approach to identify these compounds compared to previous studies using GC−qMS, due to the orthogonal systems, that reduce coelution, increase peak capacity and mass selectivity, contributing to the establishment of new potential Madeira wine age markers. Remarkable results were also obtained in terms of compound identification based on the organized structure of the peaks of structurally related compounds in the GC × GC peak apex plots. This information represents a valuable approach for future studies, as the ordered-structure principle can considerably help the establishment of the composition of samples. This new approach provides data that can be extended to determine age markers of other types of wines