数字农科院2.0

Wine characterisation according to geographical origin using analysis of mineral elements and rainfall correlation of oxygen isotope values

文献类型： 外文期刊

作者： Su Y.; Zhao Y.; Cui K.; Wang F.; Zhang J.; Zhang A.

作者机构：

关键词： Authentication; Discriminant analysis; Isotopes; Mass spectrometry; Minerals; Oxygen; Rain; Wine; Chinese wine; Geographical origins; Isotopic ratios; Linear discriminant analyze; Mineral element; Multielements; Oxygen isotope values; Oxygen isotopic; Oxygen isotopic ratio; Traceability; Neural networks

期刊名称： International Journal of Food Science and Technology

ISSN： 0950-5423

年卷期： 2022 年 57 卷 1 期

页码：

收录情况： SCIE（2022版） ; EI（2022版）

摘要： The wine industry has developed rapidly; however, wine fraud is a potential risk for consumers. In China, methods for detecting wine authenticity are far from perfect. To reduce the risk of counterfeit wines, Inductively Coupled Plasma-Mass Spectrometry and Isotope Ratio Mass Spectrometry were used to geographically classify 104 wines from four major production areas. In this paper, the naturally distributed characteristics of thirty-eight mineral elements contents and the effect of rainfall on the oxygen isotope values in wine were investigated. The result of δ18O ranged from −13‰ to 7‰. The oxygen isotope of wine water in Northwest China is obviously more positive than that in South China. Linear discriminant analysis (LDA) showed 88.5% classification accuracy in training set and 81.7% in the cross-validation result. An artificial neural network (ANN) model determined origin of the wine with higher accuracy than LDA model. Furthermore, δ18O and Sr/Rb are important recognition elements in ANN, and the accuracy of region recognition can reach 90.9%. Thus, mineral elements and isotope ratios are effective in contributing to wine authenticity control in wine origin. © 2021 Institute of Food, Science and Technology (IFSTTF)

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