| 光谱学与光谱分析 |
|
|
|
|
|
| Nondestructive Quantitative Analysis of Cofrel Medicines by Improved Partial Least Squares-NIR Spectroscopy |
| LIU Ming-yang1,MENG Yu2,REN Yu-lin1,ZHANG Han-qi1 |
1. College of Chemistry，Jilin University，Changchun 130023，China
2. Prefz Pharmaceutical Co.，Dalian 116600，China |
|
|
|
|
Abstract In the present paper，improved partial least squares(PLS) method was used to parse near infrared(NIR) reflectance spectrum of Cofrel medicine. The contents of benproperine phosphate，a availability pharmaceutical in Cofrel medicine，were accurately nondestructively quantitatively predicted. The best number of principal components (PC) was designed by scores plot of samples in PC. The effects of the wavelength range，conventional spectra，first-derivative spectra and second-derivative spectra on the results were discussed respectively. Comparing the results with those of HPLC，the relative errors(RE%) of benproperine phosphate were less than 0.42%. The analytical results were sufficient for practical manufacture of Cofrel medicine.
|
|
Received: 2006-05-10
Accepted: 2006-08-20
|
|
|
|
Corresponding Authors:
LIU Ming-yang
E-mail: liumingyangs@sohu.com
|
|
| Cite this article: |
|
LIU Ming-yang,MENG Yu,REN Yu-lin, et al. Nondestructive Quantitative Analysis of Cofrel Medicines by Improved Partial Least Squares-NIR Spectroscopy [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(06): 1098-1101.
|
|
|
|
| URL: |
|
https://www.gpxygpfx.com/EN/Y2007/V27/I06/1098 |
[1] LU Wan-zhen，YUAN Hong-fu，XU Guang-tong, et al(陆婉珍, 袁洪福, 徐广通, 等). Modern Analysis Technique of NIR Spectroscopic(现代近红外光谱分析技术). Beijing：Sinica Petro Chemistry Press(北京：中国石化出版社)，2000. 193.
[2] Morisseau K M, Rhodes C T. Drug Development and Industrial Pharmacy，1995，21(9)：1071.
[3] Galante L J，Brinkley M A. Anal. Chem., 1990，62(23)：2514.
[4] Ciurczak E W. Applied Spectroscopy Reviews，1987，23(1-2)：147.
[5] DOU Ying，QIU Fang-ping，LIU Pei-yi，et al(窦 英, 邱芳萍, 刘培义, 等). Chem. J. Chinese Universities(高等学校化学学报)，2004，25(1)：53.
[6] Dou Y，Sun Y，Ren Y, et al. J. Pharm. and Biom. Anal.，2005，37：543.
[7] LIU Pei-yi，REN Yu-lin，GOU Yu-hui, et al(刘培义，任玉林，苟玉慧, 等). Chem. J. Chinese Universities(高等学校化学学报)，2000，21(4)：544.
[8] MA Qun，HAO Gui-qi，QIAO Yan-jiang，et al(马 群，郝贵奇，乔延江, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2006，26(10)：1842.
[9] CHEN Da，WANG Fang，SHAO Xue-guang，et al(陈 达，王 芳，邵学广, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2004，24(6)：672. |
| [1] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
| [2] |
LI Yu1, ZHANG Ke-can1, PENG Li-juan2*, ZHU Zheng-liang1, HE Liang1*. Simultaneous Detection of Glucose and Xylose in Tobacco by Using Partial Least Squares Assisted UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 103-110. |
| [3] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [4] |
WANG Cai-ling1，ZHANG Jing1，WANG Hong-wei2*, SONG Xiao-nan1, JI Tong3. A Hyperspectral Image Classification Model Based on Band Clustering and Multi-Scale Structure Feature Fusion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 258-265. |
| [5] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
| [6] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
| [7] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
| [8] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
| [9] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
| [10] |
ZHANG Shu-fang1, LEI Lei2, LEI Shun-xin2, TAN Xue-cai1, LIU Shao-gang1, YAN Jun1*. Traceability of Geographical Origin of Jasmine Based on Near
Infrared Diffuse Reflectance Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3389-3395. |
| [11] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
| [12] |
FANG Zheng, WANG Han-bo. Measurement of Plastic Film Thickness Based on X-Ray Absorption
Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3461-3468. |
| [13] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
| [14] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
| [15] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
|
|
|
|
