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":"61 10","pages":"1943 - 1954"},"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.
期刊介绍:
The Journal of Food Science and Technology (JFST) is the official publication of the Association of Food Scientists and Technologists of India (AFSTI). This monthly publishes peer-reviewed research papers and reviews in all branches of science, technology, packaging and engineering of foods and food products. Special emphasis is given to fundamental and applied research findings that have potential for enhancing product quality, extend shelf life of fresh and processed food products and improve process efficiency. Critical reviews on new perspectives in food handling and processing, innovative and emerging technologies and trends and future research in food products and food industry byproducts are also welcome. The journal also publishes book reviews relevant to all aspects of food science, technology and engineering.