中药的近红外光谱计算分析方法学研究
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摘要
目前,中药产业中缺乏能够全面反映中药质量的快速、有效的分析方法,这导致了中药产品质量不稳定可控,严重制约我国中药制药工业的发展。因此,在当前药物分析学研究领域急待攻克的诸多关键科学问题及共性关键技术中,一项十分重要的研究任务是研发中药材和中成药产品快速分析技术,建立中药生产过程在线分析方法学,实现中药制药过程质量监测和优化控制,从而保证中药产品质量的稳定性和均一性。近红外光谱(Near Infrared Spectroscopy,NIRS)是一种先进的计算机辅助快速分析测试技术,有望解决中药快速检测的难题。由于中药化学物质体系的复杂性,在实际应用中,使用常规的NIRS校正建模或模式分类等方法往往不能取得理想的定量或定性分析结果,导致其成为阻碍中药NIRS分析技术应用发展的瓶颈。为此,有必要研究中药NIRS计算分析方法学,特别是发展NIRS非线性校正建模、光谱信息特征提取、化学模式信息处理以及模糊分类辨识等方法,发展形成中药材和中成药产品快速分析新技术,实现中药生产全过程质量控制,这对于推进中药现代化进程具有重大科学意义和显著的实际应用价值。
本文根据中药质量控制关键环节中的不同要求,提出系列相关计算分析方法用于解决NIRS分析技术在中药领域应用的技术难题,探讨利用NIRS分析技术提高中药分析和质量控制水平的途径,以发展形成中药质量快速分析新方法。本文主要研究内容包括:
1.针对复杂中药材质量辨识难题,提出基于模糊神经元分类器(FNN)的NIRS分析方法用于对天然中药材质量的快速鉴别。阿胶实验结果表明,所提出的方法对分类界面含糊的复杂中药材体系辨识的学习能力和外推能力强,精度高,大大优于参比经典的BP-ANN,是一种简便、无损、快速有效的方法。
2.针对目前中药注射剂中缺少快速质量鉴别方法的现状,利用NIR透射光谱分析方法基于自组织映射神经网络(SOM)和模糊神经网络(FNN)实现了对不同厂家参麦注射液质量的快速鉴别,所提方法是适合常规分类困难的中药注射剂质量鉴别的有效工具,可望发展成为中药质量类别快速测定方法。
3.通过中药活性成分含量测定中NIRS分析方法学的研究,提出利用神经
The modernization and internationalization of Traditional Chinese Medicine (TCM) are blocked by its poor consistence and instability. One of the main reasons is the absences of fast and efficient analytical methods for quality control of TCM. Among the key technologies need to be investigated in pharmaceutical analysis field, one of main tasks is to develop fast analytical technologies and methodologies for TCM, establish on-line analytical methodologies for TCM process, realize the optimal control and evaluation of the quality of TCM in its pharmaceutical process and ensure consistence and equality of its quality. Near infrared spectroscopy (Near Infrared Spectroscopy, NIRS) is an advanced computer aided fast technique, and it could be a promising solution to solve the problem of fast measurement for TCM. Since the composition of TCM is quite complex, the traditional methods for modeling and pattern recognition sometimes could not get the ideal quantitative or qualitative results. So it is difficult to use NIR spectra practically in pharmaceutical industry of TCM. Therefore, it is necessary to carry on the studies on computational methodologies of NIRS, especially develop methods for non-linear modeling, feature extraction, chemical pattern information processing, fuzzy classification and etc., develop the new analytical technologies for pharmaceutical process of TCM and realize the quality control for the whole pharmaceutical process of TCM. Such studies have great scientific meaning and remarkable practical value in progress of TCM modernization.In this paper, some computational analytical methods have been developed according to the content and demand of quality control of TCM. These methods could be used to solve the application problems of using NIR technologies for TCM. The approaches improving the level of analysis and quality control of TCM are discussed, and could be used to develop new fast analytical methodologies of quality control for TCM. The main results obtained from the paper are listed as following:
1. To distinguish quality of complex TCM, a fast analytical method using NIRS based on an adaptive fuzzy-neural classifier (FNN) is proposed. The experiment results on Colla CoriiA sini show the proposed method has strong learning and extrapolated abilities in distinguishing the quality of TCM with ambiguous boundary. Compared with method using traditional BP-ANN, its identification result is more accurate. It is showed that the method proposed is fast, convenient, non-destructive, and effective.2. In order to solve the problem of lacking fast method for evaluating quality of TCM injections, the methods using near infrared transmission spectroscopy based on a self-organizing mapping neural network (SOM) and FNN are developed respectively. Distinguishing different manufacturers of Shenmai injection is investigated as an example to test the performance of the methods. The methods developed could be used as new approaches to classify the complex TCM which has serious non-linear phenomena and could not be easily classified by traditional methods.3. Studies on the methodologies of determinating active components of TCM using NIR spectra analysis are systematically carried on. Methods using artificial neural network (ANN) and support vector machine (SVM) combined with different data preprocess methods are proposed to solve the non-linearity in the NIR reflectance spectra of Panax notoginseng root herb. These proposed methods effectively reduce the predictive error and are the suitable tools for non-linear modeling.4. Studies on applications of on-line NIRS technologies and computational analytical methodologies are carried on. Analytical models are successfully established to make a fast on-line measurement of Radix salviae miltiorrhizae's extraction in pilot-scale and industrial process respectively. The BP-ANN models are established to solve the non-linearity in the measured NIR spectra and improved the quantaitive analytical accuracy. A method using the absolute distance of standard deviation of the on-line measured spectra is developed to make fast estimation of process ending point during the optimization of TCM process. The results well inosculates the real industrial process. These methods developed could be applied in
the whole production process of TCM.In conclusion, the studies on computational analytical methodologies of NIRS for TCM help to improve the level of theoretically research and application of NIR technologies. These developed analytical methods could solve the problem of absence of fast methods of quality control for TCM. The results indicate that all the developed methods could be extent to fast quality identification and on-line measurement of TCM, having applicability and innovabality. It provides new approaches in strengthening the quality control in production process and improving the analytical level of TCM.
本文根据中药质量控制关键环节中的不同要求,提出系列相关计算分析方法用于解决NIRS分析技术在中药领域应用的技术难题,探讨利用NIRS分析技术提高中药分析和质量控制水平的途径,以发展形成中药质量快速分析新方法。本文主要研究内容包括:
1.针对复杂中药材质量辨识难题,提出基于模糊神经元分类器(FNN)的NIRS分析方法用于对天然中药材质量的快速鉴别。阿胶实验结果表明,所提出的方法对分类界面含糊的复杂中药材体系辨识的学习能力和外推能力强,精度高,大大优于参比经典的BP-ANN,是一种简便、无损、快速有效的方法。
2.针对目前中药注射剂中缺少快速质量鉴别方法的现状,利用NIR透射光谱分析方法基于自组织映射神经网络(SOM)和模糊神经网络(FNN)实现了对不同厂家参麦注射液质量的快速鉴别,所提方法是适合常规分类困难的中药注射剂质量鉴别的有效工具,可望发展成为中药质量类别快速测定方法。
3.通过中药活性成分含量测定中NIRS分析方法学的研究,提出利用神经
The modernization and internationalization of Traditional Chinese Medicine (TCM) are blocked by its poor consistence and instability. One of the main reasons is the absences of fast and efficient analytical methods for quality control of TCM. Among the key technologies need to be investigated in pharmaceutical analysis field, one of main tasks is to develop fast analytical technologies and methodologies for TCM, establish on-line analytical methodologies for TCM process, realize the optimal control and evaluation of the quality of TCM in its pharmaceutical process and ensure consistence and equality of its quality. Near infrared spectroscopy (Near Infrared Spectroscopy, NIRS) is an advanced computer aided fast technique, and it could be a promising solution to solve the problem of fast measurement for TCM. Since the composition of TCM is quite complex, the traditional methods for modeling and pattern recognition sometimes could not get the ideal quantitative or qualitative results. So it is difficult to use NIR spectra practically in pharmaceutical industry of TCM. Therefore, it is necessary to carry on the studies on computational methodologies of NIRS, especially develop methods for non-linear modeling, feature extraction, chemical pattern information processing, fuzzy classification and etc., develop the new analytical technologies for pharmaceutical process of TCM and realize the quality control for the whole pharmaceutical process of TCM. Such studies have great scientific meaning and remarkable practical value in progress of TCM modernization.In this paper, some computational analytical methods have been developed according to the content and demand of quality control of TCM. These methods could be used to solve the application problems of using NIR technologies for TCM. The approaches improving the level of analysis and quality control of TCM are discussed, and could be used to develop new fast analytical methodologies of quality control for TCM. The main results obtained from the paper are listed as following:
1. To distinguish quality of complex TCM, a fast analytical method using NIRS based on an adaptive fuzzy-neural classifier (FNN) is proposed. The experiment results on Colla CoriiA sini show the proposed method has strong learning and extrapolated abilities in distinguishing the quality of TCM with ambiguous boundary. Compared with method using traditional BP-ANN, its identification result is more accurate. It is showed that the method proposed is fast, convenient, non-destructive, and effective.2. In order to solve the problem of lacking fast method for evaluating quality of TCM injections, the methods using near infrared transmission spectroscopy based on a self-organizing mapping neural network (SOM) and FNN are developed respectively. Distinguishing different manufacturers of Shenmai injection is investigated as an example to test the performance of the methods. The methods developed could be used as new approaches to classify the complex TCM which has serious non-linear phenomena and could not be easily classified by traditional methods.3. Studies on the methodologies of determinating active components of TCM using NIR spectra analysis are systematically carried on. Methods using artificial neural network (ANN) and support vector machine (SVM) combined with different data preprocess methods are proposed to solve the non-linearity in the NIR reflectance spectra of Panax notoginseng root herb. These proposed methods effectively reduce the predictive error and are the suitable tools for non-linear modeling.4. Studies on applications of on-line NIRS technologies and computational analytical methodologies are carried on. Analytical models are successfully established to make a fast on-line measurement of Radix salviae miltiorrhizae's extraction in pilot-scale and industrial process respectively. The BP-ANN models are established to solve the non-linearity in the measured NIR spectra and improved the quantaitive analytical accuracy. A method using the absolute distance of standard deviation of the on-line measured spectra is developed to make fast estimation of process ending point during the optimization of TCM process. The results well inosculates the real industrial process. These methods developed could be applied in
the whole production process of TCM.In conclusion, the studies on computational analytical methodologies of NIRS for TCM help to improve the level of theoretically research and application of NIR technologies. These developed analytical methods could solve the problem of absence of fast methods of quality control for TCM. The results indicate that all the developed methods could be extent to fast quality identification and on-line measurement of TCM, having applicability and innovabality. It provides new approaches in strengthening the quality control in production process and improving the analytical level of TCM.
引文
[1] 宋立人,中华本草[M],上海科学技术出版社,1999,1:52.
[2] 袁久荣,袁浩,中药质量控制与方法学,中国药学杂志[J],2001,36(8):566-568.
[3] 刘明言,元英进,朱世斌,中药现代化进展,中草药[J],2002,33(3):193-196.
[4] 程翼宇,瞿海斌,信息技术在中药现代化研究中的应用及发展,世界科学—中药现代化高技术应用[J],2002,3(4):37-41.
[5] 曾苏,程翼宇,药物分析研究进展,浙江大学学报(医学出版)[J],2004,33(1):1-6.
[6] Guidance for Industry, PATs Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance, U. S. Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER), Center for Veterinary, Medicine (CVM), Office of Regulatory Affairs (ORA), Pharmaceutical CGMPs, September 2004. http://www.fda.gov/cder/guidance/6419fnl.htm.
[7] Jerome Workman, Jr., Mel Koch, Dave Veltkamp, Process Analytical Chemistry, Anal. Chem. [J], 2005, ASAP Article, DOI: 10.1021/ac050620.
[8] Crocombe R. A. Spectrosc. Eur [J], 2004, 16 (3): 16-19.
[9] Weeks B. L., DeYoreo J. J., Abstr. Pap., 227th ACS National Meeting, Anaheim, CA, March 28-April 1, 2004: COLL-297.
[10] Hui K., Kostiainen R., Kotiaho T., Introduction to Micro-analytical systems: bioanalytical and pharmaceutical applications, Eur J. Pharm. Sci. [J], 2003, 20(2): 149-171.
[11] Koh H. L., Yau W. P., Ong P. S. Hegde, A., Current trends in modem pharmaceutical analysis for drug discovery, Drug Discovery Today[J], 2003, 8 (19): 889-897.
[12] Trojanowicz M., Szewczynska M., Wcislo, M. Electroanalysis[J], 2003, 15 (5-6): 347-365.
[13] 任杰,宋海华.流动注射分析原理及进展,天津化工[J],2003,17(2):22～25]
[14] Qin X. Z., Quality control methods for synthetic drugs: Comparison of separation and non-separation technologies, Process Control and Quality[J], 1997, 10 (1): 1-23.
[15] 王雷,杨新建,寇欣.紫外分光光度法在中药分析中的应用进展,天津药学[J],2003, 15(5):62-64.
[16] 刘立军,姜恒,宫红,苏婷婷.红外光谱分析中样品处理方法的改进,光谱学与光谱分析[J],2004,24(1):62-64.
[17] Crocombe R. A., Spectrosc. Eur.[J], 2004, 16 (3): 16-19.
[18] Fisher M., Bulatov V., Schechter I., Fast analysis of narcotic drugs by optical chemical imaging, J. Lumin. [J], 2003, 102-103, 194-200.]
[19] Wildgoose G. G., Lawrence N. S., Leventis H. C., Li J., Jones T. G. J., Compton R. G. J., Mater. Chem. [J], 2005, 15 (9): 953-959.
[20] Blanco M., Coello J., Eustaquio A., Iturriaga H., Maspoch S. et al., Analytical control of pharmaceutical production steps by near infrared reflectance spectroscopy, Anal Chim. Acta. [J], 1999, 392(2-3): 237-246.
[21] Kramer K., Ebel S., Application of NIR reflectance spectroscopy for the identification of pharmaceutical excipients, Anal. Chim. Acta.[J], 2000, 420(2): 155-161.
[22] Xiangji Z., Patricia H., Matthew W. Borer., Moisture determination in hygroscopic drug substances by near infrared spectroscopy, J. Pharmaceut. Biomed. [J], 1998, 17(2): 219-225.
[23] Blanco M., Gozalez Bano R., Bertran E., Monitoring powder blending in pharmaceutical processes by use of near infrared spectroscopy, Talanta[J], 2002, 56(1): 203-212.
[24] Blanco M., Coello J., Iturriaga H., et al., Quantitation of the active compound and major excipients in a pharmaceutical formulation by near infrared diffuse reflectance spectroscopy with fibre optical probe, Anal Chim. Acta. [J], 1996, 333(1): 147-156.
[25] Wan-zhen L., Hong-fu Y., Guang-tong X., et al., Modem analysis technique of NIR[M], Beijing: Sinica Petro-Chemistry Press, 2000: 193-249.
[26] Report Group, Official Methods of Analysis (AOAC), 1990: 1: 553.
[27] 吴玉田,柴逸峰,陆峰,体系药物分析对现代分析仪器的呼唤,生命科学仪器[J],2003, 1(2):8-11.
[28] 肖树雄,李陭岳,陈家雄,几种现代技术在中药检验中的应用概况,中药材[J],25(11):838-841.
[29] Philos W. H., Trans. R. Soc., 1800, 90: 255.
[30] Brackett F. S., Proc. Natl. Acad. Sei. (US) [J], 1928, 14: 857.
[31] Kaye W. I., Spectrochim Acta[J], 1955, 7: 181.
[32] Kaye W. I., Near Infrared Spectroscopy in the Encyclopedia Of Spectroscopy, G L Clark(ed.) Reinhold., 1960, 409-414.
[33] Norris K. H., J. Anim. Sci[J], 1976, 43: 4.
[34] Norris K. H. et al..J. Food Sci. [J]. 1968. 33: 64.
[35] 扬英,范凌,王明仙等,NIR分析技术在饲料工业中的发展,饲料工业[J],2000,21(2):2l-23.
[36] 万钧,近红外品质分析技术在油脂工业中的应用,四川粮油科技[J],2000,3:13-16.
[37] Stefanis E De, Sgrulletta D., Use of NIT(near infrared transmission) spectroscopy for semolina analysis, Tocnica Molitoria[J], 1996, 47(9): 861-866.
[38] Wehrle K., Seibel W., Gerstenkom P., et al., Rapid methods for qualitative evaluation of durum wheat, J. NIR Analysis. [J], 1996, 5(30): 181-185.
[39] 彭玉魁,李菊英,祁振英,NIR分析技术在小麦营养成份鉴定上的应用,麦类作物[J],1997,17(2):33-35.
[40] 王成,傅立叶变换近红外漫反射光谱法测定大麦粗蛋白含量,新疆农业科学[J],2000(2):68-70.
[41] 陈邵苹,近红外漫反射光谱测定饲料中粗纤维,饲料工业[J],1996,17(6):32-33.
[42] 何东健,杨青,薛少平等,农产品分光反射特性及近红外图像处理在农业中的应用,农业工程学报[J],1996,12(4):80-84.
[43] Slaugter D., Barreti D., Boersig M., et al., Nondestructive determination of soluble solids in tomatoes using near infrared spectroscopy, J. FoodSci. [J], 1996, 61(4): 695-697.
[44] Tanaka M., Ojima T., Near infrared monitoring to the grouth period of Japanese pear fruit based on constituent sugar concentrations, J. Agr Food Chem. [J], 1996, 44(8): 2272-2277.
[45] Fujiwara T., Honjo T., Determination of constituents in fruit juice by near infrared spectroscopy Ⅱ., Journal of Japanese Scociety of Food Science and Technology[J], 1996, 43(7): 841-848.
[46] Ridway C., Chambers J., Detection of external and internal insect infestation in wheat by near infrared reflectance spectroscopy. J. Sci. Food Agr. [J], 1996, 71(2): 251-264.
[47] 吴秀琴,金达生,刘旭明,NIR分析技术在农作物抗虫鉴定中的应用研究,中国农业科学[J],1995,28(5):92.
[48] Cozzlino D., Murray J., Paterson R., et al., Visible and Near infrared reflectance spectroscopy for determination of moisture, fat and protein in chicken breast and thigh muscle. J. Near Infrared Spec. [J], 1996, 4(1): 213-223.
[49] Wamecke H. W., Lehmarm R., Schwager K., et al., Effects of additives on results of near infrared analyses. Fleischwirtschaft[J], 1997, 77(6): 538-540.
[50] Difoggio R., Sadhukhan M., Ranc M. L., Oil & Gas J[J], 1993, 91(21): 87.
[51] Bohacs Gy, Ovadi Z., J. Near Infrared Spectrosc. [J], 1998, 6: 341-348]
[52] DiazA., Barsamian J. A., Meet changing fuel requirements with online blend optim ization, Hydrocarbon Processing[J], 1996, 2: 71-76.
[53] Popkow A. S., Barsamian A., New gasoline blending unit started at Poland refinery, Oil&Gas J[J], 1999, 97(27): 64-67.
[54] 孙根旺,赵小强,王亚玲,张敏,汽油在线优化调合控制模型与其应用,石油炼制与化工[J],1999,11:33-36.
[55] 岳俊奇,袁洪福,陆婉珍,分析化学[J],1998,26(5):603.
[56] 徐广通,袁洪福,陆婉珍,分析化学[J],1999,27(1):29-33.
[57] Ward Howard W. Ⅱ, Sekulic S. Sonja, Wheeler M., J. Appl. Spectrosc.[J], 1998, 52(1): 17-21.
[58] 安登魁等,现代药物分析选论,中国医药科技出版社,2001.
[59] Wu W., Walczak B., Massart, D. L., Prebble, K. A., Last I. R., Spectral transformation and wavelength selection in near-infrared Spectra classification, Anal. Chim. Acta. [J], 1995, 315.
[60] Dresssi E., et al., Near-infrared reflectance spectrometry in the determination of the physical state of primary materials in pharmaceutical production, Analyst[J], 1995: 120.
[61] Jouan-Rimband D. et al., Combination line adjustment to facilitate the use of synthetic calibration samples in near-infrared spectrometric analysis of Pharmaceutical production samples, Anal. Chim. Acta.[J], 1995: 315.
[62] Morisseau K. M. et al., Pharmaceutical uses of near-infrared Spectroscopy, Drug De. Ind. Pharm. [J], 1995, 21(9): 36-45.
[63] Lodder R. A. et al, Detection of capsule tampering by near-infrared reflectance analysis, Anal. Chem. [J], 1987: 59.
[64] Peuchant E. et al., Determination of serum cholesterol, Anal. Chem. [J], 1987: 59.
[65] Dreassi E. et al., Application of near-infrared reflectance analysis to the intergraed control of antibiotic tablet production, Analyst[J], 1995: 120
[66] Sekulic S. S. et al., On-line monitoring of power blend homogeneity by near-infrared spectroscopy, Anal. Chem. [J], 1996: 68.
[67] 刘荔荔,相秉仁,盛龙生,近红外漫反射光谱可视化褶合指纹谱对中药材的定性鉴别,中国药科大学学报[J],2003,34:105-108.
[68] 刘荔荔,邢旺兴,贾暖,近红外漫反射光谱聚类分析用于中药红曲的鉴别,第二军医大学学报[J],2002,23(12):1230-1232.
[69] 刘荔荔,原源,陈万生,近红外反射光谱法在羊蹄类生药分类中的应用,中草药,2001,32(1):1024-1026.
[70] 刘荔荔,李力,邢旺兴,不同种丹参药材的近红外漫反射光谱模式识别法鉴别,医药服务与研究[J],2002,2(1):23-25.
[71] 刘荔荔,贾暖,吴玉田,中药材的近红外漫反射光谱峰位鉴别法,光谱仪器与分析[J],2000,2:23-29.
[72] 邢旺兴,刘荔荔,贾暖,不同产地红曲的近红外漫反射光谱聚类分析鉴别,中药材[J],2001,24:561-563.
[73] 吴拥军,李伟,相秉仁,NIR技术用于白芷类中药的鉴定研究,中药材[J],2001,24(1):26-28.
[74] 何淑华,孙瑞岩,任玉秋,近红外漫反射光谱法对吉林人参的分类探讨,吉林大学自然科学学报[J],2001,1:96-98.
[75] 魏道智,郭澄,吴秋业,蝼蛄的NIR鉴别研究,中国中药杂志[J],2004,29: 639-640.
[76] 黄宝康,朱斌,郑汉臣,不同产地楮实子及伪品的近红外漫反射指纹图谱聚类分析,中药材[J],2002,25:874-875.
[77] 朱斌,郑清明,秦路平,20种金丝桃属植物的近红外漫反射光谱法鉴别,第二军医大学学报[J],2003,24:455-456.
[78] 钟蕾,范国荣,陆峰,近红外漫反射光谱的可视化褶合变换技术用于血竭的鉴别,药学服务与研究[J],2004,4:111-113.
[79] Laasonen M., Harmia-Pulkkinen T., Christine L S., et al., Fast Identification of Echinacea purpurea Dried Roots Using Near Infrared Spectroscopy, Anal. Chem. [J], 2002, 74: 2493-2499.
[80] Woo Y. A., Kim H. J., Cho J., et al., Discrimination of herbal medicines according to the geographical origin with near infrared reflectance spectroscopy and pattern recognition techniques. J Pharmaceut Biomed[J], 1999, 21(2): 407-413.
[81] Woo Y. A., Cho C. H., Kim H. J., et al., Classification of cultivation area of ginseng by near infrared spectroscopy and ICP-AES, Microchem. J [J], 2002, 73(3): 299-306.
[82] 刘国林,蔡金娜,李伟,NIR技术在中药蛇床子分类中的应用,计算机与应用化学[J],2000,17(2):109-110.
[83] 王平,陈泽琴,谢洪平,不同产地中药材的NIR初步研究,西华师范大学学报(自然科学版)[J],2004,25:92-95.
[84] 刘福强,赵文萃,刘革,人工神经网络-NIR法非破坏监测芦丁药品的质量,化学分析计量[J],2003,12:11-13.
[85] Ren G. X., Chen F., Simultaneous quantification of ginsenosides in American ginseng (Panax quinquefolium) root powder by visible/near-infrared reflectance spectroscopy, J. Agri. Food Chem. [J], 1999, 47 (7): 2771-2775.
[86] Gray D. E., Crop. Sci, 2001, 41: 1159-1161.
[87] 瞿海斌,刘全,程翼宇,近红外漫反射光谱法测定黄连浸膏粉中生物碱含量,分析化学[J],2004,32:477-480.
[88] 杨南林,程翼宇,吴永江,中药材三七中皂苷类成分的NIR快速无损分析新方法,化学学报[J],2002,61(3):393-398.
[89] 杨南林,翟海斌,程翼宇,NIR法快速测定三七总皂苷的方法研究,浙江大学学报(工学版)[J],2002,36(4):463-466.
[90] 刘荔荔,邢旺兴,贾暖,近红外漫反射光谱法测定西洋参中人参的掺入量,中国中药杂志[J],2003,28:178-179.
[91] 陈斌,赵龙莲,李军会,NIR法快速分析葛根中的有效成分,光谱学与光谱分析[J],2002,22(6):976-979.
[92] 杜德国,孙素琴,周群,芦丁和维生素C的近红外漫反射光谱技术定量分析研究,光谱学与光谱分析[J],2000,20(4):474-475.
[93] 任玉林,李伟,郭晔,近红外漫反射光谱法与偏最小二乘法结合作芦丁粉末药品的非破坏性分析,分析仪器[J],1998,2:43-46.
[94] 谷筱玉,徐可欣,冰片的NIR法检测,光谱学与光谱分析[J],2004,24:155-157.
[95] 胡钢亮,吕秀阳,罗玲,NIR法同时测定银杏提取液中总黄酮和总内酯含量,分析化学[J],2004,32:1061-1063.
[96] 刘国林,陈国广,相秉仁,NIR技术在元胡止痛散定曦分析中的初步应用研究,中国现代应用药学[J],2000,17:383-385.
[97] 杨南林,程翼宇,翟海斌,用人工神经网络—NIR法测定冬虫夏草中的甘露醇,分析化学[J],2003,31:664-668.
[98] 赵琛,翟海斌,程翼宇,虫草氨基酸的人工神经网络NIR快速测定方法,光谱学与光谱分析[J].2004 24:50-53.
[99] 瞿海斌,刘晓宣,程翼宇,中药材三七提取液NIR的支持向量机回归校正方法,高等学校化学学报[J],2004,25:39-43.
[100] 杨南林,程翼宇,瞿海斌,一种用于中药纯化过程的NIR分析新方法,化学学报[J],2003,61:742-747.
[2] 袁久荣,袁浩,中药质量控制与方法学,中国药学杂志[J],2001,36(8):566-568.
[3] 刘明言,元英进,朱世斌,中药现代化进展,中草药[J],2002,33(3):193-196.
[4] 程翼宇,瞿海斌,信息技术在中药现代化研究中的应用及发展,世界科学—中药现代化高技术应用[J],2002,3(4):37-41.
[5] 曾苏,程翼宇,药物分析研究进展,浙江大学学报(医学出版)[J],2004,33(1):1-6.
[6] Guidance for Industry, PATs Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance, U. S. Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER), Center for Veterinary, Medicine (CVM), Office of Regulatory Affairs (ORA), Pharmaceutical CGMPs, September 2004. http://www.fda.gov/cder/guidance/6419fnl.htm.
[7] Jerome Workman, Jr., Mel Koch, Dave Veltkamp, Process Analytical Chemistry, Anal. Chem. [J], 2005, ASAP Article, DOI: 10.1021/ac050620.
[8] Crocombe R. A. Spectrosc. Eur [J], 2004, 16 (3): 16-19.
[9] Weeks B. L., DeYoreo J. J., Abstr. Pap., 227th ACS National Meeting, Anaheim, CA, March 28-April 1, 2004: COLL-297.
[10] Hui K., Kostiainen R., Kotiaho T., Introduction to Micro-analytical systems: bioanalytical and pharmaceutical applications, Eur J. Pharm. Sci. [J], 2003, 20(2): 149-171.
[11] Koh H. L., Yau W. P., Ong P. S. Hegde, A., Current trends in modem pharmaceutical analysis for drug discovery, Drug Discovery Today[J], 2003, 8 (19): 889-897.
[12] Trojanowicz M., Szewczynska M., Wcislo, M. Electroanalysis[J], 2003, 15 (5-6): 347-365.
[13] 任杰,宋海华.流动注射分析原理及进展,天津化工[J],2003,17(2):22～25]
[14] Qin X. Z., Quality control methods for synthetic drugs: Comparison of separation and non-separation technologies, Process Control and Quality[J], 1997, 10 (1): 1-23.
[15] 王雷,杨新建,寇欣.紫外分光光度法在中药分析中的应用进展,天津药学[J],2003, 15(5):62-64.
[16] 刘立军,姜恒,宫红,苏婷婷.红外光谱分析中样品处理方法的改进,光谱学与光谱分析[J],2004,24(1):62-64.
[17] Crocombe R. A., Spectrosc. Eur.[J], 2004, 16 (3): 16-19.
[18] Fisher M., Bulatov V., Schechter I., Fast analysis of narcotic drugs by optical chemical imaging, J. Lumin. [J], 2003, 102-103, 194-200.]
[19] Wildgoose G. G., Lawrence N. S., Leventis H. C., Li J., Jones T. G. J., Compton R. G. J., Mater. Chem. [J], 2005, 15 (9): 953-959.
[20] Blanco M., Coello J., Eustaquio A., Iturriaga H., Maspoch S. et al., Analytical control of pharmaceutical production steps by near infrared reflectance spectroscopy, Anal Chim. Acta. [J], 1999, 392(2-3): 237-246.
[21] Kramer K., Ebel S., Application of NIR reflectance spectroscopy for the identification of pharmaceutical excipients, Anal. Chim. Acta.[J], 2000, 420(2): 155-161.
[22] Xiangji Z., Patricia H., Matthew W. Borer., Moisture determination in hygroscopic drug substances by near infrared spectroscopy, J. Pharmaceut. Biomed. [J], 1998, 17(2): 219-225.
[23] Blanco M., Gozalez Bano R., Bertran E., Monitoring powder blending in pharmaceutical processes by use of near infrared spectroscopy, Talanta[J], 2002, 56(1): 203-212.
[24] Blanco M., Coello J., Iturriaga H., et al., Quantitation of the active compound and major excipients in a pharmaceutical formulation by near infrared diffuse reflectance spectroscopy with fibre optical probe, Anal Chim. Acta. [J], 1996, 333(1): 147-156.
[25] Wan-zhen L., Hong-fu Y., Guang-tong X., et al., Modem analysis technique of NIR[M], Beijing: Sinica Petro-Chemistry Press, 2000: 193-249.
[26] Report Group, Official Methods of Analysis (AOAC), 1990: 1: 553.
[27] 吴玉田,柴逸峰,陆峰,体系药物分析对现代分析仪器的呼唤,生命科学仪器[J],2003, 1(2):8-11.
[28] 肖树雄,李陭岳,陈家雄,几种现代技术在中药检验中的应用概况,中药材[J],25(11):838-841.
[29] Philos W. H., Trans. R. Soc., 1800, 90: 255.
[30] Brackett F. S., Proc. Natl. Acad. Sei. (US) [J], 1928, 14: 857.
[31] Kaye W. I., Spectrochim Acta[J], 1955, 7: 181.
[32] Kaye W. I., Near Infrared Spectroscopy in the Encyclopedia Of Spectroscopy, G L Clark(ed.) Reinhold., 1960, 409-414.
[33] Norris K. H., J. Anim. Sci[J], 1976, 43: 4.
[34] Norris K. H. et al..J. Food Sci. [J]. 1968. 33: 64.
[35] 扬英,范凌,王明仙等,NIR分析技术在饲料工业中的发展,饲料工业[J],2000,21(2):2l-23.
[36] 万钧,近红外品质分析技术在油脂工业中的应用,四川粮油科技[J],2000,3:13-16.
[37] Stefanis E De, Sgrulletta D., Use of NIT(near infrared transmission) spectroscopy for semolina analysis, Tocnica Molitoria[J], 1996, 47(9): 861-866.
[38] Wehrle K., Seibel W., Gerstenkom P., et al., Rapid methods for qualitative evaluation of durum wheat, J. NIR Analysis. [J], 1996, 5(30): 181-185.
[39] 彭玉魁,李菊英,祁振英,NIR分析技术在小麦营养成份鉴定上的应用,麦类作物[J],1997,17(2):33-35.
[40] 王成,傅立叶变换近红外漫反射光谱法测定大麦粗蛋白含量,新疆农业科学[J],2000(2):68-70.
[41] 陈邵苹,近红外漫反射光谱测定饲料中粗纤维,饲料工业[J],1996,17(6):32-33.
[42] 何东健,杨青,薛少平等,农产品分光反射特性及近红外图像处理在农业中的应用,农业工程学报[J],1996,12(4):80-84.
[43] Slaugter D., Barreti D., Boersig M., et al., Nondestructive determination of soluble solids in tomatoes using near infrared spectroscopy, J. FoodSci. [J], 1996, 61(4): 695-697.
[44] Tanaka M., Ojima T., Near infrared monitoring to the grouth period of Japanese pear fruit based on constituent sugar concentrations, J. Agr Food Chem. [J], 1996, 44(8): 2272-2277.
[45] Fujiwara T., Honjo T., Determination of constituents in fruit juice by near infrared spectroscopy Ⅱ., Journal of Japanese Scociety of Food Science and Technology[J], 1996, 43(7): 841-848.
[46] Ridway C., Chambers J., Detection of external and internal insect infestation in wheat by near infrared reflectance spectroscopy. J. Sci. Food Agr. [J], 1996, 71(2): 251-264.
[47] 吴秀琴,金达生,刘旭明,NIR分析技术在农作物抗虫鉴定中的应用研究,中国农业科学[J],1995,28(5):92.
[48] Cozzlino D., Murray J., Paterson R., et al., Visible and Near infrared reflectance spectroscopy for determination of moisture, fat and protein in chicken breast and thigh muscle. J. Near Infrared Spec. [J], 1996, 4(1): 213-223.
[49] Wamecke H. W., Lehmarm R., Schwager K., et al., Effects of additives on results of near infrared analyses. Fleischwirtschaft[J], 1997, 77(6): 538-540.
[50] Difoggio R., Sadhukhan M., Ranc M. L., Oil & Gas J[J], 1993, 91(21): 87.
[51] Bohacs Gy, Ovadi Z., J. Near Infrared Spectrosc. [J], 1998, 6: 341-348]
[52] DiazA., Barsamian J. A., Meet changing fuel requirements with online blend optim ization, Hydrocarbon Processing[J], 1996, 2: 71-76.
[53] Popkow A. S., Barsamian A., New gasoline blending unit started at Poland refinery, Oil&Gas J[J], 1999, 97(27): 64-67.
[54] 孙根旺,赵小强,王亚玲,张敏,汽油在线优化调合控制模型与其应用,石油炼制与化工[J],1999,11:33-36.
[55] 岳俊奇,袁洪福,陆婉珍,分析化学[J],1998,26(5):603.
[56] 徐广通,袁洪福,陆婉珍,分析化学[J],1999,27(1):29-33.
[57] Ward Howard W. Ⅱ, Sekulic S. Sonja, Wheeler M., J. Appl. Spectrosc.[J], 1998, 52(1): 17-21.
[58] 安登魁等,现代药物分析选论,中国医药科技出版社,2001.
[59] Wu W., Walczak B., Massart, D. L., Prebble, K. A., Last I. R., Spectral transformation and wavelength selection in near-infrared Spectra classification, Anal. Chim. Acta. [J], 1995, 315.
[60] Dresssi E., et al., Near-infrared reflectance spectrometry in the determination of the physical state of primary materials in pharmaceutical production, Analyst[J], 1995: 120.
[61] Jouan-Rimband D. et al., Combination line adjustment to facilitate the use of synthetic calibration samples in near-infrared spectrometric analysis of Pharmaceutical production samples, Anal. Chim. Acta.[J], 1995: 315.
[62] Morisseau K. M. et al., Pharmaceutical uses of near-infrared Spectroscopy, Drug De. Ind. Pharm. [J], 1995, 21(9): 36-45.
[63] Lodder R. A. et al, Detection of capsule tampering by near-infrared reflectance analysis, Anal. Chem. [J], 1987: 59.
[64] Peuchant E. et al., Determination of serum cholesterol, Anal. Chem. [J], 1987: 59.
[65] Dreassi E. et al., Application of near-infrared reflectance analysis to the intergraed control of antibiotic tablet production, Analyst[J], 1995: 120
[66] Sekulic S. S. et al., On-line monitoring of power blend homogeneity by near-infrared spectroscopy, Anal. Chem. [J], 1996: 68.
[67] 刘荔荔,相秉仁,盛龙生,近红外漫反射光谱可视化褶合指纹谱对中药材的定性鉴别,中国药科大学学报[J],2003,34:105-108.
[68] 刘荔荔,邢旺兴,贾暖,近红外漫反射光谱聚类分析用于中药红曲的鉴别,第二军医大学学报[J],2002,23(12):1230-1232.
[69] 刘荔荔,原源,陈万生,近红外反射光谱法在羊蹄类生药分类中的应用,中草药,2001,32(1):1024-1026.
[70] 刘荔荔,李力,邢旺兴,不同种丹参药材的近红外漫反射光谱模式识别法鉴别,医药服务与研究[J],2002,2(1):23-25.
[71] 刘荔荔,贾暖,吴玉田,中药材的近红外漫反射光谱峰位鉴别法,光谱仪器与分析[J],2000,2:23-29.
[72] 邢旺兴,刘荔荔,贾暖,不同产地红曲的近红外漫反射光谱聚类分析鉴别,中药材[J],2001,24:561-563.
[73] 吴拥军,李伟,相秉仁,NIR技术用于白芷类中药的鉴定研究,中药材[J],2001,24(1):26-28.
[74] 何淑华,孙瑞岩,任玉秋,近红外漫反射光谱法对吉林人参的分类探讨,吉林大学自然科学学报[J],2001,1:96-98.
[75] 魏道智,郭澄,吴秋业,蝼蛄的NIR鉴别研究,中国中药杂志[J],2004,29: 639-640.
[76] 黄宝康,朱斌,郑汉臣,不同产地楮实子及伪品的近红外漫反射指纹图谱聚类分析,中药材[J],2002,25:874-875.
[77] 朱斌,郑清明,秦路平,20种金丝桃属植物的近红外漫反射光谱法鉴别,第二军医大学学报[J],2003,24:455-456.
[78] 钟蕾,范国荣,陆峰,近红外漫反射光谱的可视化褶合变换技术用于血竭的鉴别,药学服务与研究[J],2004,4:111-113.
[79] Laasonen M., Harmia-Pulkkinen T., Christine L S., et al., Fast Identification of Echinacea purpurea Dried Roots Using Near Infrared Spectroscopy, Anal. Chem. [J], 2002, 74: 2493-2499.
[80] Woo Y. A., Kim H. J., Cho J., et al., Discrimination of herbal medicines according to the geographical origin with near infrared reflectance spectroscopy and pattern recognition techniques. J Pharmaceut Biomed[J], 1999, 21(2): 407-413.
[81] Woo Y. A., Cho C. H., Kim H. J., et al., Classification of cultivation area of ginseng by near infrared spectroscopy and ICP-AES, Microchem. J [J], 2002, 73(3): 299-306.
[82] 刘国林,蔡金娜,李伟,NIR技术在中药蛇床子分类中的应用,计算机与应用化学[J],2000,17(2):109-110.
[83] 王平,陈泽琴,谢洪平,不同产地中药材的NIR初步研究,西华师范大学学报(自然科学版)[J],2004,25:92-95.
[84] 刘福强,赵文萃,刘革,人工神经网络-NIR法非破坏监测芦丁药品的质量,化学分析计量[J],2003,12:11-13.
[85] Ren G. X., Chen F., Simultaneous quantification of ginsenosides in American ginseng (Panax quinquefolium) root powder by visible/near-infrared reflectance spectroscopy, J. Agri. Food Chem. [J], 1999, 47 (7): 2771-2775.
[86] Gray D. E., Crop. Sci, 2001, 41: 1159-1161.
[87] 瞿海斌,刘全,程翼宇,近红外漫反射光谱法测定黄连浸膏粉中生物碱含量,分析化学[J],2004,32:477-480.
[88] 杨南林,程翼宇,吴永江,中药材三七中皂苷类成分的NIR快速无损分析新方法,化学学报[J],2002,61(3):393-398.
[89] 杨南林,翟海斌,程翼宇,NIR法快速测定三七总皂苷的方法研究,浙江大学学报(工学版)[J],2002,36(4):463-466.
[90] 刘荔荔,邢旺兴,贾暖,近红外漫反射光谱法测定西洋参中人参的掺入量,中国中药杂志[J],2003,28:178-179.
[91] 陈斌,赵龙莲,李军会,NIR法快速分析葛根中的有效成分,光谱学与光谱分析[J],2002,22(6):976-979.
[92] 杜德国,孙素琴,周群,芦丁和维生素C的近红外漫反射光谱技术定量分析研究,光谱学与光谱分析[J],2000,20(4):474-475.
[93] 任玉林,李伟,郭晔,近红外漫反射光谱法与偏最小二乘法结合作芦丁粉末药品的非破坏性分析,分析仪器[J],1998,2:43-46.
[94] 谷筱玉,徐可欣,冰片的NIR法检测,光谱学与光谱分析[J],2004,24:155-157.
[95] 胡钢亮,吕秀阳,罗玲,NIR法同时测定银杏提取液中总黄酮和总内酯含量,分析化学[J],2004,32:1061-1063.
[96] 刘国林,陈国广,相秉仁,NIR技术在元胡止痛散定曦分析中的初步应用研究,中国现代应用药学[J],2000,17:383-385.
[97] 杨南林,程翼宇,翟海斌,用人工神经网络—NIR法测定冬虫夏草中的甘露醇,分析化学[J],2003,31:664-668.
[98] 赵琛,翟海斌,程翼宇,虫草氨基酸的人工神经网络NIR快速测定方法,光谱学与光谱分析[J].2004 24:50-53.
[99] 瞿海斌,刘晓宣,程翼宇,中药材三七提取液NIR的支持向量机回归校正方法,高等学校化学学报[J],2004,25:39-43.
[100] 杨南林,程翼宇,瞿海斌,一种用于中药纯化过程的NIR分析新方法,化学学报[J],2003,61:742-747.