| 光谱学与光谱分析 |
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| Discrimination of Minnan Oolong Tea Varieties by NIR Spectroscopy |
| CHENG Quan1, YANG Fang2*, WANG Dan-hong2, LIN Zhen-yu1, QIU Bin1 |
1. Key Laboratory of Analysis and Detection for Food Safety, Ministry of Education, Fujian Provincial Key Laboratory of Analysis and Detection Technology for Food Safety, Department of Chemistry, Fuzhou University, Fuzhou 350108, China
2. Fujian Enry-Exit Inspection &Quarantine Bureau of P.R.C, Fuzhou 350001, China |
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Abstract The present paper presented a fast and non-destructive method for the discrimination of minnan oolong tea varieties by near-infrared spectroscopy technology. Two hundred ten samples including Tieguanyin, Huangjingui, Benshan, Maoxie and Meizhan were collected in different tea plantations of Minnan. NIR spectra of 1 100～1 300 nm and 1 640～2 498 nm were successfully obtained. Prediction model was built by principal component analysis (PCA), and the effects of multiplicative scatter correction(MSC) and standard normal variate(SNV) on the model were observed and compared. It was indicated that the effect of MSC on the model was superior for the effect of SNV because the classification accuracy of model for the calibration samples reached 96%, and this number to the prediction samples was about 90%. These results demonstrated that the near-infrared spectroscopy method established could be an efficient and accurate way for the discrimination of minnan oolong teas and would have a strong practical value.
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Received: 2013-05-29
Accepted: 2013-07-20
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Corresponding Authors:
YANG Fang
E-mail: yangf@fjciq.gov.cn
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[1] Ng C L，Wehling R L，Cuppett S L. J. Agric. Food Chem., 2011，59(23): 12286.
[2] Fernández-Cabanás V M，Polvillo O，Rodríguez-Acuna R，et al. Food Chem., 2011，124: 373.
[3] Zhou Y，Xiang B，Wang Z，et al. Anal. Lett., 2009，42: 1518.
[4] Sanchez M T，Flores-Rojas K，Guerrero J E，et al. Pest. Manag. Sci., 2010，66: 580.
[5] Mishra S，Ka nmboj U，Kaur H，et al. Int. J. Food Sci. Nutr., 2010，61(3)：306.
[6] Zhu X，Li S，ShanY，et al. J. Food Eng., 2010，101：92.
[7] Pizarro C，Esteban-Diez I，Gonzalez-Saiz J M，et al. Anal. Chim. Acta, 2007，585(2)：266.
[8] Luo W，Huan S，Fu H，et al. Food Chem., 2011，128(2)：555.
[9] Nicoletta S，Lorenzo C，Valentina D E，et al. Food Res. Int., 2010，43(1)：369.
[10] Chen Q，Zhao J，Lin H. Spectrochim Acta A, Mol. Biomol. Spectrosc., 2009，72：845.
[11] Tan S M，Luo R M，Zhou Y P，et al. J. Chemomet, 2012，26：34.
[12] ZHOU Jian，CHENG Hao，WANG Li-yuan，et al(周 健，成 浩，王丽鸳，等). Journal of Tea Science(茶叶科学), 2009，29(1)：34.
[13] NI Zhen，HU Chang-qin，FENG Fang(尼 珍，胡昌勤，冯 芳). Pharmaceutical Analysis(药物分析杂志)，2008，28(5)：824.
[14] Paul Gemperline. Paul Gemperline(化学计量学实用指南). Translated by WU Hai-long，KANG Chao, et al(吴海龙，康 超，等译). Beijing：Science Press(北京：科学出版社)，2012. |
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