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基于熵分析(EA)和因子聚类分析(FCA)对中国贵州五种茶叶中的20种氨基酸、热重参数和微量元素进行化学计量分析。

Stoichiometric analysis of 20 amino acids, thermogravimetric parameters and trace elements in five types of tea from Guizhou, China, based on entropy analysis (EA) and factor cluster analysis (FCA).

作者信息

Zhou Libing, Huang Chunli

机构信息

Guangxi Science & Technology Normal University, Laibin 546199, Guangxi, China.

出版信息

Food Chem X. 2025 Apr 14;27:102457. doi: 10.1016/j.fochx.2025.102457. eCollection 2025 Apr.

DOI:10.1016/j.fochx.2025.102457
PMID:40463663
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12131247/
Abstract

This study employed a range of indicators, including heat of combustion, combustibility, fat content, amino acid content, ash content, crude fiber content, trace element content, and concentrations of catechins, theanine, and caffeine, to develop comprehensive evaluation systems for assessing the quality of five tea samples: Duyun Maojian tea, Liping fragrant tea, Shuicheng spring tea, Huaxi jasmine tea, and Zunyi black tea. Analytical techniques such as gray pattern recognition (GPR), gray principal component analysis (GPCA), gray factor analysis (GFA), entropy analysis (EA), and factor cluster analysis (FCA) were utilized. Based on the 42variable data, the nutritional value ranked as follows: Shuicheng spring tea > Huaxi jasmine tea > Duyun Maojian tea > Liping fragrant tea > Zunyi black tea. These findings offer significant theoretical and practical insights for the determination and comprehensive evaluation of tea quality indicators, contributing to scientific research on the nutrition, health, and classification aspects of tea.

摘要

本研究采用了一系列指标,包括燃烧热、可燃性、脂肪含量、氨基酸含量、灰分含量、粗纤维含量、微量元素含量以及儿茶素、茶氨酸和咖啡因的浓度,来建立综合评价体系,以评估都匀毛尖茶、黎平香茶、水城春茶、花溪茉莉花茶和遵义红茶这五个茶叶样品的质量。运用了灰色模式识别(GPR)、灰色主成分分析(GPCA)、灰色因子分析(GFA)、熵分析(EA)和因子聚类分析(FCA)等分析技术。基于42个变量的数据,营养价值排名如下:水城春茶>花溪茉莉花茶>都匀毛尖茶>黎平香茶>遵义红茶。这些研究结果为茶叶质量指标的测定和综合评价提供了重要的理论和实践见解,有助于茶叶营养、健康和分类方面的科学研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/94ad8ca5900b/gr5b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/ebf368920d64/gr1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/c534d0cc59ef/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/42d5032bbad2/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/5136604b850f/gr5a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/94ad8ca5900b/gr5b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/ebf368920d64/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/d1f12aa8f732/gr2a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/bbac2de260f7/gr2b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/573c4b18d472/gr2c.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/c3e35859c27e/gr2d.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/2a99f9abbdf3/gr2e.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/c534d0cc59ef/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/42d5032bbad2/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/5136604b850f/gr5a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26bd/12131247/94ad8ca5900b/gr5b.jpg

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