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by: L.F. Huang, M.J. Wu, K.J. Zhong, X.J. Sun, Liang
Amazon.com's Price: $10.95 Prices subject to change.
Binding: Digital
Format: HTML
Label: Elsevier
Manufacturer: Elsevier
Publication Date: April 11, 2007
Publisher: Elsevier
Sales Rank: 5164156
Studio: Elsevier
Editorial Review:
Product Description:
This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
In this paper, chromatographic fingerprint was firstly used for quality control of tobacco flavors. Based on gas chromatography-mass spectrometry (GC-MS) and combined chemometrics methods, a simple, reliable and reproducible method for developing chromatographic fingerprint of coffee flavor, one of tobacco flavors, was described. Six coffee flavor samples obtained from different locations were used to establish the fingerprint. The qualitative and quantitative analysis of coffee flavor sample from Shenzhen was completed with the help of subwindow factor analysis (SFA). Fifty-two components of 68 separated constituents in coffee flavor sample from Shenzhen, accounting for 88.42% of the total content, were identified and quantified. Then, spectral correlative chromatography (SCC) was used to extract the common peaks from other five studied coffee flavor samples. Thirty-eight components were found to exist in all six samples. Finally, the method validation of fingerprint analysis was performed based on the relative retention time and the relative peak area of common peaks, sample stability and similarity analysis. The similarities of six coffee flavor samples were more than 0.9104 and showed that samples from different locations were consistent to some extent. The developed chromatographic fingerprint was successfully used to differentiate coffee flavor from coco flavor and some little difference sample prepared with coffee flavor and coco flavor by both similarity comparison and principal component projection analysis. The developed method can be used for quality control of coffee flavor.
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