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Origin verification of French red wines using isotope and elemental analyses coupled with chemometrics.
Wu, Hao; Lin, Guanghui; Tian, Ling; Yan, Zhi; Yi, Bingqing; Bian, Xuehai; Jin, Baohui; Xie, Liqi; Zhou, Haichao; Rogers, Karyne M.
Affiliation
  • Wu H; Food Inspection and Quarantine Center, Shenzhen Customs, Shenzhen 518033, China.
  • Lin G; Department of Earth System Science, Tsinghua University, Beijing 100084, China; Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, China.
  • Tian L; Management College, Shenzhen Polytechnical, Shenzhen 518055, China.
  • Yan Z; Food Inspection and Quarantine Center, Shenzhen Customs, Shenzhen 518033, China.
  • Yi B; Food Inspection and Quarantine Center, Shenzhen Customs, Shenzhen 518033, China.
  • Bian X; Food Inspection and Quarantine Center, Shenzhen Customs, Shenzhen 518033, China.
  • Jin B; Food Inspection and Quarantine Center, Shenzhen Customs, Shenzhen 518033, China.
  • Xie L; Food Inspection and Quarantine Center, Shenzhen Customs, Shenzhen 518033, China.
  • Zhou H; School of Life and Marine Sciences, Shenzhen University, Shenzhen 518055, China.
  • Rogers KM; National Isotope Centre, GNS Science, Lower Hutt 5040, New Zealand. Electronic address: k.rogers@gns.cri.nz.
Food Chem ; 339: 127760, 2021 Mar 01.
Article in En | MEDLINE | ID: mdl-32860996
Origin verification of 240 French wines from four regions of France was undertaken using isotope and elemental analyses. Our aim was to identify and differentiate the geographical origin of these red wines, and more importantly, to build a classification tool that can be used to verify geographic origin of French red wines using machine learning models. Multivariate analyses of the isotopic and elemental data revealed that it is possible to determine the geographical origin of French wines with a high level of confidence for most regions analyzed in this study. The wine verification accuracy of four French wine producing regions of Bordeaux, Burgundy, Languedoc-Roussillon and Rhone using an Artificial Neural Network (ANN) method was 98.2%. The results also show that ANN is more suitable than Discriminant Analysis for this verification purpose. The most important variables for French wine regional traceability were Mg, Mn, Na, Sr, Ti and Rb.
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Full text: 1 Database: MEDLINE Main subject: Wine / Food Analysis / Metals Type of study: Prognostic_studies Country/Region as subject: Europa Language: En Journal: Food Chem Year: 2021 Type: Article Affiliation country: China

Full text: 1 Database: MEDLINE Main subject: Wine / Food Analysis / Metals Type of study: Prognostic_studies Country/Region as subject: Europa Language: En Journal: Food Chem Year: 2021 Type: Article Affiliation country: China