Comparison of Chemical and Sensory Profiles between Cabernet Sauvignon and Marselan Dry Red Wines in China.
Xixian SongWeixi YangXu QianXinke ZhangMengqi LingLi YangYing ShiChang-Qing DuanYi-Bin LanPublished in: Foods (Basel, Switzerland) (2023)
The differences in chemical and sensory characteristics between Marselan and Cabernet Sauvignon in China were investigated with gas chromatography-mass spectrometry (GC-MS) and high-performance liquid chromatography-triple quadrupole mass spectrometry (HPLC-QqQ-MS/MS), combined with color parameters and sensory data. The paired t -test results showed that terpenoids, higher alcohols, and aliphatic lactones were significantly different according to the grape variety. Meanwhile, terpenoids could be considered as marker aroma compounds to distinguish Marselan wines from Cabernet Sauvignon, which could explain the distinct floral note in Marselan wines. The mean concentrations of the mv-vsol, mv-vgol, mv-vcol, mvC-vgol, mv-v(e)cat, mvC-v(e)cat, mv-di(e)cat, and cafA were higher in Marselan wines than Cabernet Sauvignon wines, and these compounds might confer Marselan wines with a deeper color, more red hue, and higher tannin quality. The phenolic profiles of Marselan and Cabernet Sauvignon wines were influenced by the winemaking process, mitigating the varietal differences. As for sensory evaluation, the intensities of herbaceous, oak, and astringency of Cabernet Sauvignon were more pronounced than Marselan, whereas the Marselan wines were characterized by a high color intensity and more redness, together with floral, sweet, and roasted sweet potato attributes, and tannin roughness.
Keyphrases
- high performance liquid chromatography
- mass spectrometry
- ms ms
- tandem mass spectrometry
- solid phase extraction
- simultaneous determination
- gas chromatography mass spectrometry
- liquid chromatography
- gas chromatography
- liquid chromatography tandem mass spectrometry
- ultra high performance liquid chromatography
- high resolution
- escherichia coli
- machine learning
- electronic health record
- high resolution mass spectrometry
- deep learning
- big data
- data analysis