近红外光谱法同时快速鉴别3种麻黄药材品种

目的：建立同时快速鉴别3种药典收载麻黄药材的近红外光谱法。方法：测量药典品种麻黄药材草麻黄、中麻黄和木贼麻黄，以及混淆品种丽江麻黄的傅里叶变换近红外漫反射光谱，采用化学计量学技术，提取不同药典品种麻黄药材共有的且区别于混淆品种丽江麻黄的光谱特征信息，建立同时鉴别不同药典品种麻黄药材与混淆品种丽江麻黄的判别分析（discriminant analysis，DA）模型和对向传播人工神经网络（counterpropagation artificial neural network，CP-ANN）模型，并比较2种模型的性能。结果：所建DA模型校正集和验证集的预测准确率均为100.0%；CP-ANN模型校正集、交叉验证和验证集的预测准确率均为100.0%。虽然2种模型具有相同的预测准确率，但是非线性CP-ANN模型使用较少的主成分建模，性能略优于线性DA模型。结论：所建近红外光谱法能够同时快速鉴别3种药典收载麻黄药材。

Objective: To identify three species of Ephedra authorized in pharmacopoeia simultaneously and rapidly using near-infrared(NIR)spectroscopy.Methods: The Fourier transform NIR diffuse reflectance spectra of the Ephedra authorized in pharmacopoeia(Ephedra sinica Stapf, Ephedra intermedia Schrenk et C. A. Mey. and Ephedra equisetina Bge.)and those of the adulterant species(Ephedra likiangensis Florin)were collected. The common spectral features, which differed from adulterant species, were extracted from different species of Ephedra authorized in pharmacopoeia using chemometric techniques. The discriminant analysis(DA)model and the counterpropagation artificial neural network(CP-ANN)model were built for identifying the different species of Ephedra authorized in pharmacopoeia from Ephedra likiangensis Florin. The performances of two models were compared.Results: The prediction accuracy of the DA model was 100.0% for both calibration and validation.And the prediction accuracy of the CP-ANN model was 100.0% for all of calibration, cross-validation and validation. Although the two models had the same prediction accuracy, the nonlinear CP-ANN model was slightly better than the linear DA model since it used less principal components(PCs).Conclusion: The three species of Ephedra authorized in pharmacopoeia could be simultaneously and rapidly identified by using the established NIR spectroscopy method.

[1] National Center for Complementary and Integrative Health. Bethesda, National Institutes of Health. Ephedra[EB/OL]. 2016[2017-01-04]. https://nccih.nih.gov/health/ephedra
[2] 中国药典2015年版.一部[S]. 2015:320 ChP 2015. Vol Ⅰ[S]. 2015:320
[3] EP 8. 0[S]. 2013:1236
[4] JP 16[S]. 2011:1637
[5] 张建生,李胜华.国产麻黄的形态组织学研究:Ⅱ.西南主产种及其它种[J].药学学报, 1990,25(1):54 ZHANG JS, LI SH. Morphological and histological studies of Chinese Ephedra, Ma Huang Ⅱ. Species produced in southwestern China and other species[J]. Acta Pharm Sin,1990, 25(1):54
[6] 中国科学院中国植物志编辑委员会.中国植物志[M].北京:科学出版社, 1978:478 Delectis Florae Reipublicae Popularis Sinicae Agendae Academiae Sinicae Edita. Flora Reipublicae Popularis Sinicae[M]. Beijing:Science Press,1978:478
[7] 王丽琼,范琦,易珍奎,等. HPLC指纹图谱结合反向传播人工神经网络和判别分析鉴定不同的麻黄药材[J].西南师范大学学报(自然科学版), 2012,37(5):73 WANG LQ, FAN Q, YI ZK, et al. Identification of different Ephedra plants using HPLC fingerprints in combination with backpropagation artificial neural network and discriminant analysis[J]. J Southwest China Normal Univ(Nat Sci Ed), 2012, 37(5):73
[8] REN XF,LIANG YZ, LI XN,et al. Chemical fingerprint analysis for quality control of Herba Ephedrae based on HPLC-DAD combined with chemometrics methods[J]. Anal Lett,2012, 45(13):1824
[9] 中国药典2015年版.四部[S]. 2015:379 ChP 2015. Vol Ⅳ[S]. 2015:379
[10] DA SILVA VH, GONÇALVES JL, VASCONCELOS FVC, et al. Quantitative analysis of mebendazole polymorphs in pharmaceutical raw materials using near-infrared spectroscopy[J]. J Pharm Biomed Anal, 2015, 115:587
[11] DONG YH, LI J, ZHONG XX, et al. High-throughput prediction of tablet weight and trimethoprim content of compound sulfamethoxazole tablets for controlling the uniformity of dosage units by NIR[J]. Spectrochim Acta A, 2016, 159:78
[12] LI WL, CHENG ZW, WANG YF, et al. Quality control of Lonicerae Japonicae Flos using near infrared spectroscopy and chemometrics[J]. J Pharm Biomed Anal,2013, 72:33
[13] 杨海龙,臧恒昌,胡甜,等.近红外漫反射光谱法对不同产地山楂的定性鉴别和定量分析[J].药物分析杂志, 2014,34(3):396 YANG HL,ZANG HC,HU T,et al. Classification and quantification analysis of hawthorn from different origins with near-infrared diffuse reflection spectroscopy[J]. Chin J Pharm Anal, 2014, 34(3):396
[14] 李化,苏建春,柯华香,等.基于近红外漫反射光谱和多元数据分析的黄芩质量标准的快速评价方法研究[J].药物分析杂志, 2015,35(3):518 LI H,SU JC,KE HX,et al. Study on fast assessment method of quality standard of Radix Scutellariae by near infrared spectroscopy and multivariate analysis[J]. Chin J Pharm Anal,2015,35(3):518
[15] FAN Q,WANG YL, SUN P, et al. Discrimination of Ephedra plants with diffuse reflectance FT-NIRS and multivariate analysis[J]. Talanta,2010, 80(3):1245
[16] 易珍奎,范琦,王丽琼,等.近红外漫反射光谱法结合CP-ANN和PLS高通量分析草麻黄药材[J].药物分析杂志, 2012, 32(8):1402 YI ZK, FAN Q, WANG LQ, et al. High-throughput analysis of Ephedra sinica plants by NIR diffuse reflectance spectroscopy combined with CP-ANN and PLS[J]. Chin J Pharm Anal, 2012, 32(8):1402
[17] WORKMAN J, WEYER L. Practical Guide to Interpretive Nearinfrared Spectroscopy[M]. USA:CRC Press, 2008:9