Hong-Lin Liu, Yi-Tao Zeng, Kai Zhang, Xin Zhao, Tian-Lai Yang
{"title":"Improving the geographical traceability of tea in China based on stable isotope ratios","authors":"Hong-Lin Liu, Yi-Tao Zeng, Kai Zhang, Xin Zhao, Tian-Lai Yang","doi":"10.1007/s13197-024-05970-w","DOIUrl":null,"url":null,"abstract":"<div><p>The potential of improving the classification of tea samples from different regions was studied by using stable isotope ratios analysis. The stable isotope ratios of 44 elements in tea samples were determined (<i>p</i> < 0.05).The results showed that 34 stable isotopes ratios were statistically significant, and tea in the four regions had their own characteristic variables. PCA, HCA, PLS-DA, BP-ANN and LDA were used to analyze the stable isotope ratio data in tea. Six key variables were identified to provide the greatest difference between the samples. The overall correct classification rate, cross validation rate and blind validation rate given by LDA are all 100%, and the result is the best. This study has proved that the stable isotope ratio analysis method could improve the geographical origin traceability of Chinese tea.</p></div>","PeriodicalId":632,"journal":{"name":"Journal of Food Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7010,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Science and Technology","FirstCategoryId":"1","ListUrlMain":"https://link.springer.com/article/10.1007/s13197-024-05970-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The potential of improving the classification of tea samples from different regions was studied by using stable isotope ratios analysis. The stable isotope ratios of 44 elements in tea samples were determined (p < 0.05).The results showed that 34 stable isotopes ratios were statistically significant, and tea in the four regions had their own characteristic variables. PCA, HCA, PLS-DA, BP-ANN and LDA were used to analyze the stable isotope ratio data in tea. Six key variables were identified to provide the greatest difference between the samples. The overall correct classification rate, cross validation rate and blind validation rate given by LDA are all 100%, and the result is the best. This study has proved that the stable isotope ratio analysis method could improve the geographical origin traceability of Chinese tea.
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