|
|
|
|
|
|
| Application of Fluorescence Spectrometry Combined with Fisher Discriminant Analysis in Radix Panacis Quinquefolii Identification |
| CHEN Jia-wei1, HU Cui-ying1*, MA Ji2 |
1. Siyuan Laboratory, Department of Physics, Jinan University, Guangzhou 510632, China
2. College of Traditional Chinese Medicine, Southern Medical University, Guangzhou 510515, China |
|
|
|
|
Abstract The purpose of this paper was to establish a reliable Fisher discriminant model which was able to recognize the decoction pieces of radix panacis quinquefolii and its' common counterfeits rapidly, objectively and accurately. The fluorescence spectra of 90 samples (decoction pieces of radix panacis quinquefolii, radix ginseng and platycodon grandiflorum each 30 copies) that from different source were detected by a self-build staring spectral imaging instrument in this study. The experimental parameters included spectral wavelengths range from 400 to 720 nm, with the interval of 5 nm. Standard normal variate (SNV) transformation was used for spectral pretreatment, to reduce the noise information in original spectral data. According to the principle features and optimizing effect of principal component analysis (PCA) and stepwise discriminant analysis (SDA), PCA in combination with PCA was needed. At first, SNV spectral data was processed with PCA to obtain main information of spectrum distributed in the first few principal components. Then 12 principal components that with strong discriminant ability were selected from 65 principal components, and used for established the Fisher discriminant model. All kind of samples showed up a good clustering phenomenon in the scatter diagram, which plotted based on samples scores in two discriminant functions. In order to obtain an accurate discriminant result of the model, the Euclidean distance between the central of each species and the samples that under discriminate was calculated and as the gist. The result showed that the discriminant accuracy of the Fisher discriminant model in training set and prediction set was 98.33% and 96.67% respectively, demonstrating that the superior reliability and accuracy existed in the model. Therefore, fluorescence spectroscopy combined with Fisher discriminant analysis could be applied to the rapid identification between the decoction pieces of radix panacis quinquefolii and its' counterfeits.
|
|
Received: 2016-06-12
Accepted: 2016-11-09
|
|
|
|
Corresponding Authors:
HU Cui-ying
E-mail: hcyhome@163.com
|
|
[1] Chinese Pharmacopoeia Commission(国家药典委员会). Pharmacopeia of the People’s Republic of China Part Ⅰ(中华人民共和国药典一部). Beijing: China Medical Science Press(北京: 中国医药科技出版社), 2015. 131.
[2] Yuan C S, Wang C Z, Wicks S M, et al. Journal of Ginseng Research, 2010, 34(3): 160.
[3] Qi L W, Wang C Z, Yuan C S. Phytochemistry, 2011, 72(8): 689.
[4] HUANG Lin-fang, SUO Feng-mei, SONG Jing-yuan, et al(黄林芳，索风梅，宋经元，等). Acta Pharmaceutica Sinica(药学学报), 2013, 48(4): 580.
[5] Yuval G, Young I T, George M N. Cytometry Part A, 2006, 69(8): 735.
[6] Bioucas-Dias J M, Plaza A, Camps-Valls G, et al. IEEE Geoscience & Remote Sensing Magazine, 2013, 1(2): 6.
[7] Mahesh S, Jayas D S, Paliwal J, et al. Journal of Stored Products Research, 2015, 61: 17.
[8] Feng Y Z, Sun D W. Critical Reviews in Food Science & Nutrition, 2012, 52(11): 1039.
[9] Gautam R, Samuel A, Sil S, et al. Current Science, 2015, 108(3): 341.
[10] ZHAO Jing, PANG Qi-chang, MA Ji, et al(赵 静，庞其昌，马 骥，等). Acta Photonica Sinica(光子学报), 2008, 37(4): 758.
[11] Bi Y, Yuan K, Xiao W, et al. Analytica Chimica Acta, 2016, 909: 30.
[12] CHU Xiao-li, YUAN Hong-fu, LU Wan-zhen(褚小立，袁洪福，陆碗珍). Progress in Chemistry(化学进展), 2004, 16(4): 528.
[13] HE Xiao-qun(何晓群). Applied Multivariate Statistical Analysis(应用多元统计分析). Beijing: China Statistics Press(北京: 中国统计出版社), 2015. 181. |
| [1] |
LIU Hai-ling1, ZHAI Dong-wei1, YANG Yu-ping1*, CUI Bin1, ZHANG Zhen-wei2, ZHANG Cun-lin2. Identification of True and Counterfeit Hundred RMB of the 2005 Edition Based on Transmitted THz Pulse Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2021-2025. |
| [2] |
MA Dian-xu1, LIU Gang1*, OU Quan-hong1, YU Hai-chao1, LI Hui-mei1, SHI You-ming2. Discrimination of Common Wild Mushrooms by FTIR and Two-Dimensional Correlation Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2113-2122. |
| [3] |
CHEN Sheng, ZHANG Xun, XU Feng*. Study on Cell Wall Deconstruction of Pinus Massoniana during Dilute Acid Pretreatment with Confocal Raman Microscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2136-2142. |
| [4] |
TAN Ai-ling1, WANG Si-yuan1, ZHAO Yong2, ZHOU Kun-peng1, LU Zhang-jian1. Research on Vinegar Brand Traceability Based on Three-Dimensional Fluorescence Spectra and Quaternion Principal Component Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2163-2169. |
| [5] |
WU Xiao-hong1, 2, ZHAI Yan-li1, WU Bin3, SUN Jun1, 2, DAI Chun-xia1,4. Classification of Tea Varieties Via FTIR Spectroscopy Based on Fuzzy Uncorrelated Discriminant C-Means Clustering[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1719-1723. |
| [6] |
XU Wei-jie1, WU Zhong-chen1, 2*, ZHU Xiang-ping2, ZHANG Jiang1, LING Zong-cheng1, NI Yu-heng1, GUO Kai-chen1. Classification and Discrimination of Martian-Related Minerals Using Spectral Fusion Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1926-1932. |
| [7] |
WANG Chao, WANG Jian-ming, FENG Mei-chen, XIAO Lu-jie, SUN Hui, XIE Yong-kai, YANG Wu-de*. Hyperspectral Estimation on Growth Status of Winter Wheat by Using the Multivariate Statistical Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1520-1525. |
| [8] |
CAO Xiao-lan1, 2, CHEN Xing-ming2, ZHANG Shuai2, CUI Guo-xian1*. Ramie Variety Identification Based on the Hyperspectral Parameters and the Stepwise Discriminant Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1547-1551. |
| [9] |
WU Bin1, WANG Da-zhi2, WU Xiao-hong3, 4*, JIA Hong-wen1. Possibilistic Fuzzy K-Harmonic Means Clustering of Fourier Transform Infrared Spectra of Tea[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 745-749. |
| [10] |
LAI Tian-yue1, CAI Feng-huang1*, PENG Xin2*, CHAI Qin-qin1, LI Yu-rong1, 3, WANG Wu1, 3. Identification of Tetrastigma hemsleyanum from Different Places with FT-NIR Combined with Kernel Density Estimation Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 794-799. |
| [11] |
TU Yu-long, ZOU Bin*, JIANG Xiao-lu, TAO Chao, TANG Yu-qi, FENG Hui-hui. Hyperspectral Remote Sensing Based Modeling of Cu Content in Mining Soil[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(02): 575-581. |
| [12] |
REN Yu1,2, SUN Xue-jian2*, DAI Xiao-ai1, CEN Yi2, TIAN Ya-ming1, WANG Nan2, ZHANG Li-fu2. Variety Identification of Bulk Commercial Coal Based on Full-Spectrum Spectroscopy Analytical Technique[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(02): 352-357. |
| [13] |
WU Xi-yu1,2, ZHU Shi-ping1*, HUANG Hua1, XU Dan2, GUO Qi-gao3. Near Infrared Spectroscopy for Determination of the Geographical Origin of Huajiao[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(01): 68-72. |
| [14] |
LI Cui-ling1, 2, JIANG Kai1, 2, FENG Qing-chun1, 2, WANG Xiu1, 2*, MENG Zhi-jun1, 2, WANG Song-lin1, 2, GAO Yuan-yuan1, 2. Melon Seeds Variety Identification Based on Chlorophyll Fluorescence Spectrum and Reflectance Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(01): 151-156. |
| [15] |
TAN Nian1，SUN Yi-dan1，WANG Xue-shun1*，HUANG An-min2，XIE Bing-feng1. Research on Near Infrared Spectrum with Principal Component Analysis and Support Vector Machine for Timber Identification[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(11): 3370-3374. |
|
|
|
|
