基于近红外光谱技术的黄柏药材定量分析

苏秀红; 谢惠英; 王丰青; 雷敬卫; 王丽娜; 谢彩侠

doi:10.13422/j.cnki.syfjx.2016080087

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基于近红外光谱技术的黄柏药材定量分析

近红外光谱学专题 | 更新时间：2024-01-04

- 基于近红外光谱技术的黄柏药材定量分析
- Quantitative Analysis of Phellodendron Bark Based on Near Infrared Spectroscopy
- 中国实验方剂学杂志 2016年22卷第8期页码：87-91
- 作者机构：
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目(81473299);河南中医学院科技创新人才计划项目(2012XCXRC03)
- DOI：10.13422/j.cnki.syfjx.2016080087
  中图分类号： R284.1
- 纸质出版日期：2016
- 稿件说明：
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苏秀红, 谢惠英, 王丰青, 等. 基于近红外光谱技术的黄柏药材定量分析[J]. 中国实验方剂学杂志, 2016,22(8):87-91.

SU Xiu-hong, XIE Hui-ying, WANG Feng-qing, et al. Quantitative Analysis of Phellodendron Bark Based on Near Infrared Spectroscopy[J]. Chinese journal of experimental traditional medical formulae, 2016, 22(8): 87-91.
苏秀红, 谢惠英, 王丰青, 等. 基于近红外光谱技术的黄柏药材定量分析[J]. 中国实验方剂学杂志, 2016,22(8):87-91. DOI： 10.13422/j.cnki.syfjx.2016080087.

SU Xiu-hong, XIE Hui-ying, WANG Feng-qing, et al. Quantitative Analysis of Phellodendron Bark Based on Near Infrared Spectroscopy[J]. Chinese journal of experimental traditional medical formulae, 2016, 22(8): 87-91. DOI： 10.13422/j.cnki.syfjx.2016080087.

摘要

目的: 建立一种能够同时快速测定黄柏药材中小檗碱和黄柏碱含量的方法。方法: 以HPLC所测样品中小檗碱和黄柏碱的含量为参考值

利用近红外光谱分析技术

将参考值与样品的近红外光谱进行关联

采用偏最小二乘法(PLS)建立黄柏中小檗碱和黄柏碱的定量分析模型。结果: 所建立的小檗碱和黄柏碱的定量分析模型的内部交叉验证决定系数(R2)分别为0.99713

0.98923

校正均方差(RMSEC)分别为0.0823

0.0215

验证均方差(RMSEP)分别为0.0717

0.0166

性能指数PI分别为95.6

93.5。结论: 利用近红外光谱技术建立的定量分析模型

能够对黄柏药材中小檗碱和黄柏碱的含量进行无损快速测定。

Abstract

Objective: To establish a method for simultaneous rapid determination of berberine content and phellodendrine content in Phellodendron Bark. Method: With the berberine content and phellodendrine content determined in high performance liquid chromatography (HPLC) as the reference values

near infrared spectra of the samples were associated with the reference values above

and then the quantitative analysis models of berberine and phellodendrine were established by using partial least squares (PLS) method. Result: The correlation coefficient (R2) was 0.99713 and 0.98923 respectively for quantitative analysis model of berberine and phellodendrine. The root mean square error of calibration (RMSEC) was 0.0823 and 0.0215 respectively. The root mean square error of predication (RMSEP) was 0.0717 and 0.0166 respectively. The performance index (PI) was 95.6 and 93.5 respectively. Conclusion: The quantitative analysis model established by using near-infrared spectroscopy is rapid and nondestructive to determine the content of berberine and phellodendrine in Phellodendron Bark.

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