Establishment of a NIR on-line Quatitative Analysis Method Based on NHCl

WANG Yun-li; SHI Xin-yuan; WU Zhi-sheng; CHENG Wei; QIAO Yan-jiang

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Establishment of a NIR on-line Quatitative Analysis Method Based on NHCl

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- Establishment of a NIR on-line Quatitative Analysis Method Based on NHCl
- Chinese Journal of Experimental Traditional Medical Formulae Vol. 18, Issue 1, Pages: 43-47(2012)
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- Published：2012
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WANG Yun-li, SHI Xin-yuan, WU Zhi-sheng, et al. Establishment of a NIR on-line Quatitative Analysis Method Based on NHCl[J]. Chinese journal of experimental traditional medical formulae, 2012, 18(1): 43-47.
DOI：

WANG Yun-li, SHI Xin-yuan, WU Zhi-sheng, et al. Establishment of a NIR on-line Quatitative Analysis Method Based on NHCl[J]. Chinese journal of experimental traditional medical formulae, 2012, 18(1): 43-47. DOI：

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。

Abstract

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.

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