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Discrimination Between Shaoxing Wines and Other Chinese Rice Wines by Near-Infrared Spectroscopy and Chemometrics.

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Title: Discrimination Between Shaoxing Wines and Other Chinese Rice Wines by Near-Infrared Spectroscopy and Chemometrics.
Authors: Shen, Fei1, Yang, Danting1, Ying, Yibin1 yingyb@zju.edu.cn, Li, Bobin2, Zheng, Yunfeng2, Jiang, Tao2
Source: Food & Bioprocess Technology. Feb2012, Vol. 5 Issue 2, p786-795. 10p.
Subjects: Rice wines, Near infrared spectroscopy, Chemometrics, Food chemistry, Principal components analysis, Mathematical models, Least squares
Abstract: Shaoxing rice wine (also called Shaoxing wine) is the most well-known Chinese rice wine in China. The common fraudulent practice in the commercialization of Chinese rice wine is to sell wines from different geographical origins under the denomination of Shaoxing rice wine. In this study, the use of near-infrared (NIR) spectroscopy combined with chemometrics as a rapid tool for the discrimination of Chinese rice wine from three geographical origins ('Fujian', 'non-Shaoxing', 'Shaoxing') has been preliminarily investigated. NIR spectra were collected in transmission mode in the wavelength range of 800-2,500 nm. Discriminant models were developed by principal component analysis (PCA), discriminant analysis (DA), and discriminant partial least-squares analysis (DPLS). The chemical properties of Chinese rice wine were also investigated to find out the difference between samples from three varied origins. The results showed that good classification could be obtained after spectral pre-treatment. The percentage of samples correctly classified by both DA and DPLS methods in calibration and validation set was 97.2% and 100%, respectively. The results demonstrated that NIR could be used as a simple and rapid technique to distinguish Shaoxing wines from non-Shaoxing wines and Fujian wines. To further validate the ability of NIR spectroscopy, more samples should be incorporated to build a more robust model. [ABSTRACT FROM AUTHOR]
Copyright of Food & Bioprocess Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
An: 71106894
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  Data: <searchLink fieldCode="DE" term="%22Rice+wines%22">Rice wines</searchLink><br /><searchLink fieldCode="DE" term="%22Near+infrared+spectroscopy%22">Near infrared spectroscopy</searchLink><br /><searchLink fieldCode="DE" term="%22Chemometrics%22">Chemometrics</searchLink><br /><searchLink fieldCode="DE" term="%22Food+chemistry%22">Food chemistry</searchLink><br /><searchLink fieldCode="DE" term="%22Principal+components+analysis%22">Principal components analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Least+squares%22">Least squares</searchLink>
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  Data: Shaoxing rice wine (also called Shaoxing wine) is the most well-known Chinese rice wine in China. The common fraudulent practice in the commercialization of Chinese rice wine is to sell wines from different geographical origins under the denomination of Shaoxing rice wine. In this study, the use of near-infrared (NIR) spectroscopy combined with chemometrics as a rapid tool for the discrimination of Chinese rice wine from three geographical origins ('Fujian', 'non-Shaoxing', 'Shaoxing') has been preliminarily investigated. NIR spectra were collected in transmission mode in the wavelength range of 800-2,500 nm. Discriminant models were developed by principal component analysis (PCA), discriminant analysis (DA), and discriminant partial least-squares analysis (DPLS). The chemical properties of Chinese rice wine were also investigated to find out the difference between samples from three varied origins. The results showed that good classification could be obtained after spectral pre-treatment. The percentage of samples correctly classified by both DA and DPLS methods in calibration and validation set was 97.2% and 100%, respectively. The results demonstrated that NIR could be used as a simple and rapid technique to distinguish Shaoxing wines from non-Shaoxing wines and Fujian wines. To further validate the ability of NIR spectroscopy, more samples should be incorporated to build a more robust model. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Food & Bioprocess Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Feb2012
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