| 光谱学与光谱分析 |
|
|
|
|
|
| Rapid Determination of Pinoresinol Diglucoside and Geniposidic Acid in Eucommia ulmoides with Near Infrared Spectroscopy Combined with Chemometrics Methods |
| LI Fang-fei1, 2, PENG Ying-zhi1, 2, XU Xiong-bo1, 2, ZI Wen1, 2, LIU Rui1, 2, LIU Shao1, 2* |
| 1. Xiangya Hospital, Central South University, Changsha 410008, China2. School of Pharmaceutical Sciences, Central South University, Changsha 410013, China |
|
|
|
|
Abstract To develop a quantitative models for simultaneous determination of pinoresinol diglucoside (PDG) and geniposidic acid (GPA) in Eucommia ulmoides with near-infrared (NIR) spectroscopy combined with chemometrics. The NIR spectra were collected in diffuse reflection mode and pretreated with various spectra preprocessing methods including first-order differentiator, multiplicative scatter correction and so on. The optimal wavelength variables were screened out by competition adaptive weighted sampling method. The quantitative models for the simultaneous determination of PDG and GPA in Eucommia ulmoides were established with partial least squares (PLS) algorithm and cross validation methods. The quantitative prediction models for simultaneous determination of PDG and GPA in Eucommia ulmoides showed good predictive ability. The correlation coefficients (R2) of the two calibration models were 0.961 5, 0.958 3 while the roots mean square of cross-validation (RMSECV) were 0.001 5, 0.006 4, respectively. The quantitative prediction models proved that near infrared spectra method used for the quantitative analysis of PDG and GPA in Eucommia ulmoides owned high prediction accuracy and can meet the precision need of rapid determinations of PDG and GPA in Eucommia ulmoides in reality so t it provides a new method to realize the real time on line of quality control of Eucommia ulmoides.
|
|
Received: 2015-04-26
Accepted: 2015-08-08
|
|
|
|
Corresponding Authors:
LIU Shao
E-mail: liushao999@hotmail.com
|
|
[1] GUANG Shu-yu, SU Wei-wei(管淑玉, 苏薇薇). Journal of Chinese Medicinal Materials(中药材), 2003, 26(2): 124.
[2] WANG Li-nan, YANG Mei-hua(王丽楠, 杨美华). Natural Product Research and Development(天然产物研究与开发), 2009, 1: 108.
[3] WANG Zhi-hong, PENG Sheng, LEI Ming-sheng, et al(王志宏, 彭 胜, 雷明盛, 等). Natural Product Research and Development(天然产物研究与开发), 2013, 25: 1302.
[4] Chinese Pharmacopoeia 2015. VolⅠ(中国药典2015年版. 一部). 2015. 165.
[5] LI Wei，SUN Su-qin，QIN Jie-ping，et al(李 伟, 孙素琴，覃洁萍，等). China Journal of Chinese Materia Medica(中国中药杂志), 2010, 35 (24): 3318.
[6] Kwon Y K, Jie E Y, Sartie A, et al. Food Chemistry, 2015, 166: 389.
[7] TANG Qi-kun, WANG Jue, WU Yue-jin, et al(汤其坤，王 钰，吴跃进，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2014, 34(10): 2719.
[8] Ixasonen M, Pulkkinen T H, Simard C, et al. Anal. Chem., 2003, 75(4): 754.
[9] WU Li-min, YANG Qiong, ZHOU Shang, et al(吴利敏，杨 琼，周 尚，等). Chinese Journal of Pharmaceutical Analysis(药物分析杂志)，2012，32(9)：1583.
[10] WANG Xiao-mei，JIAO Long，LIU Xiao-li, et al(王小梅，焦 龙，刘小丽，等). Chin. J. Pharm. Anal.(药物分析杂志), 2011, 6: 1016.
[11] Zhang C, Yun Y, Fan W, et al. International Journal of Biological Macromolecules, 2015, 79: 983.
[12] CHANG Jing, TANG Yan-lin, XU Jin, et al(常 静，唐延林，徐 锦，等). Computers and Applied Chemistry(计算机与应用化学), 2011, 28 (3): 288.
[13] Cao Dong-sheng, Liang Yi-zeng, Xu Qing-song, et al. Journal of Computional Chemistry，2010, 31: 592.
[14] Li Wen-long, Cheng Zhi-wei, Wang Yue-fei, et al. Journal of Pharmaceutical and Biomedical Analysis, 2013, (72): 33.
[15] Li Xiao-li, He Yong, Wu Cang-qing, et al. Journal of Food Engineering, 2007, 82(3): 316.
[16] Li Hong-dong, Liang Yi-zeng, Xu Qing-song, et al. Analytica Chimica Acta, 2009, 648: 77. |
| [1] |
WANG Wen-xiu, PENG Yan-kun*, FANG Xiao-qian, BU Xiao-pu. Characteristic Variables Optimization for TVB-N in Pork Based on Two-Dimensional Correlation Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2094-2100. |
| [2] |
LE Ba Tuan1, 3, XIAO Dong1*, MAO Ya-chun2, SONG Liang2, HE Da-kuo1, LIU Shan-jun2. Coal Classification Based on Visible, Near-Infrared Spectroscopy and CNN-ELM Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2107-2112. |
| [3] |
LIU Jin, LUAN Xiao-li*, LIU Fei. Near Infrared Spectroscopic Modelling of Sodium Content in Oil Sands Based on Lasso Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2274-2278. |
| [4] |
YU Hui-ling1, MEN Hong-sheng2, LIANG Hao2, ZHANG Yi-zhuo2*. Near Infrared Spectroscopy Identification Method of Wood Surface Defects Based on SA-PBT-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1724-1728. |
| [5] |
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. |
| [6] |
LI Ying1, LI Yao-xiang1*, LI Wen-bin2, JIANG Li-chun3. Model Optimization of Wood Property and Quality Tracing Based on Wavelet Transform and NIR Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1384-1392. |
| [7] |
DU Jian1, 2, HU Bing-liang1*, LIU Yong-zheng1, WEI Cui-yu1, ZHANG Geng1, TANG Xing-jia1. Study on Quality Identification of Macadamia nut Based on Convolutional Neural Networks and Spectral Features[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1514-1519. |
| [8] |
HAN Guang, LIU Rong*, XU Ke-xin. Extraction of Effective Signal in Non-Invasive Blood Glucose Sensing with Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1599-1604. |
| [9] |
WANG Li-shuang, ZHANG Wen-bo*, TONG Li. Studies on Dimensional Stability of Wood under Different Moisture Conditions by Near Infrared Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1066-1069. |
| [10] |
HUANG Hua1, WU Xi-yu2, ZHU Shi-ping1*. Feature Wavelength Selection and Efficiency Analysis for Paddy Moisture Content Prediction by Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1070-1075. |
| [11] |
LI Hao-guang1,2, YU Yun-hua1,2, PANG Yan1, SHEN Xue-feng1,2. Study of Maize Haploid Identification Based on Oil Content Detection with Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1089-1094. |
| [12] |
PENG Cheng1, FENG Xu-ping2*, HE Yong2, ZHANG Chu2, ZHAO Yi-ying2, XU Jun-feng1. Discrimination of Transgenic Maize Containing the Cry1Ab/Cry2Aj and G10evo Genes Using Near Infrared Spectroscopy (NIR)[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1095-1100. |
| [13] |
LI Shuang-fang1,2, GUO Yu-bao1*, SUN Yan-hui2, GU Hai-yang2. Rapid Identification of Sunflower Seed Oil Quality by Three-Dimensional Synchronous Fluorescence Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1165-1170. |
| [14] |
XIA Ji-an1, YANG Yu-wang1*, CAO Hong-xin2, HAN Chen1, GE Dao-kuo2, ZHANG Wen-yu2. Classification of Broad Bean Pest of Visible-Near Infrared Spectroscopy Based on Cloud Computing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 756-760. |
| [15] |
MAO Ya-chun, WANG Dong, WANG Yue, LIU Shan-jun*. A FeO/TFe Determination Method of BIF Based on the Visible and Near-Infrared Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 765-770. |
|
|
|
|
