He Xi, Jeleń Henryk H
Food Volatilomics and Sensomics Group, Faculty of Food Science and Nutrition, Poznań University of Life Sciences, Poznań, Poland; Natural Resources Institute, University of Greenwich, Kent, UK.
Food Volatilomics and Sensomics Group, Faculty of Food Science and Nutrition, Poznań University of Life Sciences, Poznań, Poland.
Food Chem. 2025 Feb 15;465(Pt 2):142004. doi: 10.1016/j.foodchem.2024.142004. Epub 2024 Nov 12.
Comprehensive two dimensional gas chromatography - time of flight mass spectrometry (GC × GC-TOFMS) with sample introduction using headspace solid phase microextraction (HS-SPME) was used for the botanical classification of raw spirits obtained from C3 (corn and sorghum) and C4 (rye, wheat and potato) plants. 45 spirit samples representing these raw materials (10 spirits produced from rye, corn, wheat and potato, and 5 from sorghum) were analyzed. Volatile compounds profiles were compared by PCA, and after removal of outliers samples were subjected to the classification model. OPLS-DA model was built (RY = 0.924 QY = 0.895) that enabled clear separation of all tested spirits of different botanical origin. The model was validated with training and testing sets and 100 % correct assignment was achieved. GC × GC-TOFMS proved to be a method that not only can be used as a tool for botanic origin of raw spirits, but also provides detailed information of volatile fermentation by-products, characteristic for particular spirit.
采用顶空固相微萃取（HS-SPME）进样的全二维气相色谱-飞行时间质谱联用技术（GC×GC-TOFMS）对来源于C3植物（玉米和高粱）和C4植物（黑麦、小麦和马铃薯）的原酒进行植物分类。分析了代表这些原料的45个酒样（10个由黑麦、玉米、小麦和马铃薯酿造的酒，5个由高粱酿造的酒）。通过主成分分析（PCA）比较挥发性化合物谱图，去除异常值后将样品用于分类模型。构建了正交偏最小二乘法判别分析（OPLS-DA）模型（RY = 0.924，QY = 0.895），该模型能够清晰分离所有不同植物来源的受试原酒。该模型通过训练集和测试集进行验证，实现了100%的正确分类。GC×GC-TOFMS被证明不仅可以作为一种确定原酒植物来源的工具，还能提供特定原酒挥发性发酵副产物的详细信息。
