基于稀土元素指纹分析识别葡萄酒原产地

被引:19
作者
赵芳 [1 ]
林立 [2 ]
孙翔宇 [1 ]
毛文华 [3 ]
孙玉强 [4 ]
战吉宬 [1 ]
机构
[1] 中国农业大学食品科学与营养工程学院
[2] 陕西师范大学食品工程与营养科学学院
[3] 中国农业机械化科学研究院
[4] 国家果酒及果蔬饮品质量监督检验中心
关键词
葡萄酒; 稀土元素; ICP-MS; 原产地; 判别分析;
D O I
10.13982/j.mfst.1673-9078.2015.2.041
中图分类号
TS262.6 [葡萄酒、香槟酒];
学科分类号
100403 [营养与食品卫生学];
摘要
本研究为探讨稀土元素指纹分析对于葡萄酒原产地判别的可行性,采用电感耦合等离子体质谱法(inductively coupled plasma-mass spectrometry,ICP-MS)测定了三个原产地228个葡萄酒中的15种稀土元素含量,并对数据进行相关性分析、方差分析和判别分析。葡萄酒原产地和稀土元素含量间显著相关(p<0.01),不同原产地间存在显著性差异(p<0.001),沙城葡萄酒中稀土元素含量最低,通化最高,贺兰山东麓居中。Fisher线性判别分析(fisher linear discriminant analysis,FLD)模型对沙城、贺兰山东麓、通化三产地的交叉验证判别率分别为92.98%、98.25%、100.00%,外部验证判别率分别为84.21%、89.47%、100.00%;偏最小二乘判别分析(partial least squares-discriminant analysis,PLS-DA)模型判别能力略差,三个产地的交叉验证判别率分别为82.46%、98.25%、91.23%,外部验证判别率仅为73.68%、84.21%、100.00%。说明稀土元素含量结合多元统计分析可以应用于葡萄酒原产地的鉴别。
引用
收藏
页码:261 / 267
页数:7
相关论文
共 11 条
[1]
基于稀土元素指纹分析判别普洱古树茶和台地茶的研究 [J].
林昕 ;
黎其万 ;
和丽忠 ;
兰珊珊 ;
林涛 ;
刘宏程 .
现代食品科技, 2013, 29 (12) :2921-2925+2893
[2]
地理标志产品 通化山葡萄酒.[S].吉林省葡萄酒质量监督检验中心;通化葡萄酒股份有限公司;通化天池葡萄酒有限责任公司;通化通天酒业股份有限公司;通化市质量技术监督局.中华人民共和国国家质量监督检验检疫总局;中国国家标准化管理委员会.2007,
[3]
Differentiation of Romanian Wines on Geographical Origin and Wine Variety by Elemental Composition and Phenolic Components [J].
Geana, Elisabeta Irina ;
Marinescu, Adrian ;
Iordache, Andreea Maria ;
Sandru, Claudia ;
Ionete, Roxana Elena ;
Bala, Camelia .
FOOD ANALYTICAL METHODS, 2014, 7 (10) :2064-2074
[4]
A sharper characterization of the geographical origin of Lebanese wines by a new interpretation of the hydrogen isotope ratios of ethanol.[J].Joseph Bejjani;Maha Balaban;Toufic Rizk.Food Chemistry.2014,
[5]
Detection of the origin of Brazilian wines based on the determination of only four elements using high-resolution continuum source flame AAS.[J].Wiliam Boschetti;Roger T. Rampazzo;Morgana B. Dessuy;Maria Goreti R. Vale;Alessandro de Oliveira Rios;Plinho Hertz;Vitor Manfroi;Paulo G. Celso;Marco F. Ferrão.Talanta.2013,
[6]
Classification and characterisation of Spanish red wines according to their appellation of origin based on chromatographic profiles and chemometric data analysis [J].
Serrano-Lourido, Daniel ;
Saurina, Javier ;
Hernandez-Cassou, Santiago ;
Checa, Antonio .
FOOD CHEMISTRY, 2012, 135 (03) :1425-1431
[7]
Classification of Tempranillo wines according to geographic origin: Combination of mass spectrometry based electronic nose and chemometrics.[J].Wies Cynkar;Robert Dambergs;Paul Smith;Daniel Cozzolino.Analytica Chimica Acta.2009, 1
[8]
Multivariate determination of the geographical origin of wines from four different countries.[J].X. Capron;J. Smeyers-Verbeke;D.L. Massart.Food Chemistry.2006, 4
[9]
Classifying wine according to geographical origin via quadrupole-based ICP–mass spectrometry measurements of boron isotope ratios [J].
Paul P. Coetzee ;
Frank Vanhaecke .
Analytical and Bioanalytical Chemistry, 2005, 383 :977-984
[10]
Comparison of supervised pattern recognition methods with McNemar’s statistical test.[J].Y. Roggo;L. Duponchel;J.-P. Huvenne.Analytica Chimica Acta.2002, 2