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基于氯化铵溶液的近红外在线定量分析方法的建立 被引量:2

Establishment of a NIR on-line Quatitative Analysis Method Based on NH_4Cl
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摘要 目的:采用近红外光谱技术建立氯化铵溶液中氯化铵含量的在线分析方法,并探讨气泡对于检测结果的影响,从而指导中药活性成分的在线检测。方法:以氯化铵水溶液为载体,采集近红外光谱,以偏最小二乘法(PLS)建立模型,基于残差剔除离群值,进行模型优化,通过人工制造气泡考察对模型的影响,并对未知样品进行预测。结果:近红外测量值与实际值相近,预测效果良好,所建氯化铵定量校正模型的相关系数(R2)、内部交叉验证均方差(RMSECV)分别为0.991,0.493。经外部验证,模型的预测均方差(RMSEP)为0.222。当氯化铵浓度大于1.504 g.L-1时,预测相对误差(RESP)控制在10%以内。结果表明气泡对于模型影响不大。结论:采用近红外光谱技术建立的在线分析模型,预测结果的相对偏差满足中药活性成分在线检测的要求,为近红外光谱技术应用于药物在线生产与分析提供了有效的方法和依据。 Objective:In order to guide the on-line detection of active components of Traditional Chinese Medicine,the on-line analysis method of NIRS was established for NH4Cl solution by using the near infrared spectroscopy technology.In addition,the impact of bubbles on the detection result was evaluated.Method:The near-infrared spectroscopy technique was used to determine the content of NH4Cl.The prediction model was established using partial least squares(PLS) method after rejecting outliers.Result:The predicted value calculated by the established model was quite close to the true value,which indicated a nice performance of the near infrared spectrometer in quantitative ability.The correlation coefficients(R2) and the root-mean-square error of cross-validation(RMSECV) of the quantitative calibration model were 0.991,0.493 respectively.The root-mean-square error of prediction(RMSEP) was 0.222.The relative prediction error(RESP) was less than 10% when the concentration of NH4Cl was higher than 1.504 g·L-1.In addition,the results showed that the impact of the bubble on the detection result was so small that it could be neglected.Conclusion:The error level of near-infrared spectroscopy technology could satisfy the on-line detection of traditional chinese medicine.
出处 《中国实验方剂学杂志》 CAS 北大核心 2012年第1期43-47,共5页 Chinese Journal of Experimental Traditional Medical Formulae
基金 重大新药创制项目(2010ZX09502-002)
关键词 近红外光谱法 氯化铵 在线检测 偏最小二乘 near infrared spectroscopy ammonium chloride on-line PLS
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  • 1倪力军,朱静,张立国.近红外光谱法测定缓释制剂中冰片释放量[J].光谱学与光谱分析,2006,26(1):67-69. 被引量:7
  • 2Chong IG,Jun CH. Performance of some variable selection methods when multicollinearity is present. Chemometrics and Intelligent Laboratory Systems, 2005, 78(1-2):103-112.
  • 3Lindgren F, Geladi P,Rnnar S, et al. Interactive variable selection (IVS) for PLS. Part 1: Theory and algorithms. Journal of Chemometrics, 1994, 8(5):349-363.
  • 4Olah M,C Bologa, TI Oprea. An automated PLS search for biologically relevant QSAR descriptors. Journal of Computer-Aided Molecular Design, 2004, 18(7):437-449.
  • 5Sorol N, Arancibia E, Bortolato SA, et al. Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods. Chemometrics and Intelligent Laboratory Systems, 2010, 102(2):100-109.
  • 6Gosselin R, D Rodrigue, C Duchesne. A Bootstrap - VIP approach for selecting wavelength intervals in spectral imaging applications. Chemometrics and Intelligent Laboratory Systems, 2010, 100(1)-12-21.
  • 7Vannucci M, N Sha,PJ Brown. NIR and mass spectra classification: Bayesian methods for wavelet - based feature selection. Chemometrics and Intelligent Led)oratory Systems, 2005, 77(1-2):139-148.
  • 8Li H,Liang Y,Xu Q, et al. Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration .Analytic a Chimica Acta, 2009, 648(1)^77-84.
  • 9于宝珠,辛明,施朝晟,刘全.微型近红外分析仪用于药物制剂混合中的在线检测[J].中国药事,2008,22(7):560-563. 被引量:6
  • 10王小亮,傅强,绳金房,杨欣.近红外光谱技术在制药过程分析中的应用进展[J].西北药学杂志,2009,24(3):228-230. 被引量:18

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