Multivariate Analysis for 1H-NMR Spectra of Two Hundred Kinds of Tea in the World

• FUJIWARA Masako

  JEOL DATUM LTD.

• ANDO Itiro

  Environmental Research Center Ltd. National Institute of Advanced Industrial Science and Technology (AIST)

• ARIFUKU Kazunori

  JEOL DATUM LTD.

書誌事項

タイトル別名

• Multivariate Analysis for ¹H-NMR Spectra of Two Hundred Kinds of Tea in the World

抄録

NMR measurements coupled with pattern-recognition analysis offer a powerful mixture-analysis tool for latent-feature extraction and sample classification. As fundamental applications of this analysis for mixtures, the ¹H spectra of 176 kinds of green, black, oolong and other tea infusions were acquired by a 500 MHz NMR spectrometer. Each spectrum pattern was analyzed by a multivariate statistical pattern-recognition method where Principal Component Analysis (PCA) was used in combination with Soft Independent Modeling of Class Analogy (SIMCA). SIMCA effectively selected variables that contribute to tea categorization. The final PCA resulted in clear classification reflecting the fermentation and processing of each tea, and revealed marker variables that include catechin and theanine peaks.

収録刊行物

• Analytical Sciences

  Analytical Sciences 22 (10), 1307-1314, 2006

  社団法人 日本分析化学会

キーワード

• Analytical Chemistry

詳細情報

• CRID: 1390282679235110144
• NII論文ID: 130004441179
• NII論文ID: 10018321752
• NII書誌ID: AA10500785
• DOI: 10.2116/analsci.22.1307
• ISSN: 13482246
• ISSN: 09106340
• NDL書誌ID: 8080246
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I8080246
• Web Site: https://link.springer.com/content/pdf/10.2116/analsci.22.1307.pdf
• Web Site: https://link.springer.com/article/10.2116/analsci.22.1307/fulltext.html
• Web Site: https://www.jstage.jst.go.jp/article/analsci/22/10/22_10_1307/_pdf
• 本文言語コード: en
• データソース種別:
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  • NDL
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