{"title":"基于UHPLC-Q-Exactive Orbitrap MS的黑茶非靶向代谢组学研究","authors":"Zhiwei Zhang, Yuanxi Han, Zhendong Liu, Liang Li","doi":"10.1007/s00217-025-04668-3","DOIUrl":null,"url":null,"abstract":"<div><p>Dark tea, being a fermented variety, is intrinsically linked to its regional provenance in terms of its quality and market value. Therefore, precisely verifying the geographical origin of dark tea is essential for guaranteeing its quality and establishing its market value. The study used a method called non-targeted metabolomics and ultra-high-performance liquid chromatography-quadrupole-electrostatic field Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap MS) to find out what chemicals are in dark tea from different parts of the world. Chemometric modeling was utilized to ascertain the origin of the tea. Through non-targeted metabolomics analysis of 47 dark tea samples, 12 principal metabolites were identified, predominantly determined by altitude. An orthogonal partial least squares-discriminant analysis (OPLS-DA) validation model was built utilizing these differential metabolites. Additionally, this study developed a method that integrates geographical characteristics, including altitude, and created OPLS-DA validation models for each region. Following model fitting, validation, and discrimination training, the findings indicated no overfitting, with accuracy rates for both the training and validation sets achieving 100%. This study’s method demonstrates considerable promise for identifying the geographical origin of dark tea and establishes a robust basis for origin identification in fermented foods.</p></div>","PeriodicalId":549,"journal":{"name":"European Food Research and Technology","volume":"251 5","pages":"785 - 798"},"PeriodicalIF":3.0000,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Altitude and regional differentiation of dark tea using non-targeted metabolomics based on UHPLC-Q-Exactive Orbitrap MS\",\"authors\":\"Zhiwei Zhang, Yuanxi Han, Zhendong Liu, Liang Li\",\"doi\":\"10.1007/s00217-025-04668-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Dark tea, being a fermented variety, is intrinsically linked to its regional provenance in terms of its quality and market value. Therefore, precisely verifying the geographical origin of dark tea is essential for guaranteeing its quality and establishing its market value. The study used a method called non-targeted metabolomics and ultra-high-performance liquid chromatography-quadrupole-electrostatic field Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap MS) to find out what chemicals are in dark tea from different parts of the world. Chemometric modeling was utilized to ascertain the origin of the tea. Through non-targeted metabolomics analysis of 47 dark tea samples, 12 principal metabolites were identified, predominantly determined by altitude. An orthogonal partial least squares-discriminant analysis (OPLS-DA) validation model was built utilizing these differential metabolites. Additionally, this study developed a method that integrates geographical characteristics, including altitude, and created OPLS-DA validation models for each region. Following model fitting, validation, and discrimination training, the findings indicated no overfitting, with accuracy rates for both the training and validation sets achieving 100%. This study’s method demonstrates considerable promise for identifying the geographical origin of dark tea and establishes a robust basis for origin identification in fermented foods.</p></div>\",\"PeriodicalId\":549,\"journal\":{\"name\":\"European Food Research and Technology\",\"volume\":\"251 5\",\"pages\":\"785 - 798\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Food Research and Technology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00217-025-04668-3\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Food Research and Technology","FirstCategoryId":"97","ListUrlMain":"https://link.springer.com/article/10.1007/s00217-025-04668-3","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Altitude and regional differentiation of dark tea using non-targeted metabolomics based on UHPLC-Q-Exactive Orbitrap MS
Dark tea, being a fermented variety, is intrinsically linked to its regional provenance in terms of its quality and market value. Therefore, precisely verifying the geographical origin of dark tea is essential for guaranteeing its quality and establishing its market value. The study used a method called non-targeted metabolomics and ultra-high-performance liquid chromatography-quadrupole-electrostatic field Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap MS) to find out what chemicals are in dark tea from different parts of the world. Chemometric modeling was utilized to ascertain the origin of the tea. Through non-targeted metabolomics analysis of 47 dark tea samples, 12 principal metabolites were identified, predominantly determined by altitude. An orthogonal partial least squares-discriminant analysis (OPLS-DA) validation model was built utilizing these differential metabolites. Additionally, this study developed a method that integrates geographical characteristics, including altitude, and created OPLS-DA validation models for each region. Following model fitting, validation, and discrimination training, the findings indicated no overfitting, with accuracy rates for both the training and validation sets achieving 100%. This study’s method demonstrates considerable promise for identifying the geographical origin of dark tea and establishes a robust basis for origin identification in fermented foods.
期刊介绍:
The journal European Food Research and Technology publishes state-of-the-art research papers and review articles on fundamental and applied food research. The journal''s mission is the fast publication of high quality papers on front-line research, newest techniques and on developing trends in the following sections:
-chemistry and biochemistry-
technology and molecular biotechnology-
nutritional chemistry and toxicology-
analytical and sensory methodologies-
food physics.
Out of the scope of the journal are:
- contributions which are not of international interest or do not have a substantial impact on food sciences,
- submissions which comprise merely data collections, based on the use of routine analytical or bacteriological methods,
- contributions reporting biological or functional effects without profound chemical and/or physical structure characterization of the compound(s) under research.