Geographical Origin Classification of Chinese Wines Based on Carbon and Oxygen Stable Isotopes and Elemental Profiles

被引:20
|
作者
Su, Ying-Yue [1 ,2 ,3 ,4 ]
Gao, Jie [5 ]
Zhao, Yong-Fang [2 ,3 ,4 ]
Wen, Hao-Song [2 ,3 ,4 ]
Zhang, Jin-Jie [2 ,3 ,4 ]
Zhang, Ang [2 ,3 ,4 ]
Yuan, Chun-Long [1 ]
机构
[1] Northwest A&F Univ, Coll Enol, Yangling 712100, Shaanxi, Peoples R China
[2] Technol Ctr Qinhuangdao Customs, Qinhuangdao 066000, Hebei, Peoples R China
[3] State Lab Risk Verificat & Assessment Im Ex Food, Qinhuangdao 066000, Hebei, Peoples R China
[4] Qinhuangdao Key Testing Lab Wine, Qinhuangdao 066000, Hebei, Peoples R China
[5] Zangdong Treasure Winery Co, Chengdu 854512, Tibet, Peoples R China
关键词
Chinese wine; Geographic origin; Inductively coupled plasma mass spectrometry; Isotope ratio mass spectrometry; Multielement analysis; ICP-MS; CHEMOMETRIC ANALYSIS; RED WINES; RATIOS; DISCRIMINATION; SR-87/SR-86; VALIDATE; MINERALS; REGIONS; WHITE;
D O I
10.4315/JFP-19-499
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Wines from different regions have different qualities due to the impact of geographical location and climate. The sale of inferior wines seriously violates the fair-trade rights of consumers. This article provides an elemental analysis classification method for verifying the geographical origin of wines in the People's Republic of China. Inductively coupled plasma mass spectrometry, liquid chromatography isotope ratio mass spectrometry. and an isotope ratio mass spectrometer were used to analyze 142 wine samples collected from Helan Mountain, Xinjiang, Yunchuanzang, the Yanhuai Valley, and the Hexi Corridor regions. The data included elemental profiles, carbon isotope ratios (delta C-13), and oxygen isotope ratios (delta O-18). The results of multivariate analysis revealed that the geographical origin of wine is closely related to variations in elemental profiles and isotope ratios. Introducing delta O-18 and the elements Li, Mn, Ag, In, Th, Ta, and Re into the discriminant model yielded correct classification rates of the linear discriminant model of 90.8% for the training set and 87.3% for the test set.
引用
收藏
页码:1323 / 1334
页数:12
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