广西医科大学学报2024,Vol.41Issue(2) :302-309.DOI:10.16190/j.cnki.45-1211/r.2024.02.020

基于便携式近红外光谱仪建立生姜配方颗粒的一致性评价及定量分析方法

Consistency evaluation and quantitative analysis of ginger formula granules based on porta-ble near infrared spectrometer

覃月莲 彭诗雅 韦红言 黄艳 韦敏灵 韦锦斌 潘诗翰 苏志恒 梁永红
广西医科大学学报2024,Vol.41Issue(2) :302-309.DOI:10.16190/j.cnki.45-1211/r.2024.02.020

基于便携式近红外光谱仪建立生姜配方颗粒的一致性评价及定量分析方法

Consistency evaluation and quantitative analysis of ginger formula granules based on porta-ble near infrared spectrometer

覃月莲 1彭诗雅 1韦红言 2黄艳 2韦敏灵 2韦锦斌 1潘诗翰 1苏志恒 1梁永红1
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作者信息

  • 1. 广西医科大学药学院,南宁 530021
  • 2. 培力南宁药业有限公司,南宁 530007
  • 折叠

摘要

目的:建立生姜配方颗粒的近红外光谱(NIRS)一致性评价及定量分析方法.方法:利用便携式近红外光谱仪采集生姜配方颗粒样品的近红外光谱信息,通过对61批生姜配方颗粒样品的指纹图谱与对照指纹图谱进行一致性检验,采用相关系数进行分析评价.采用高效液相色谱法(HPLC)测定生姜配方颗粒样品中6-姜辣素的含量.考察不同预处理方法对定量模型参数的影响,建立偏最小二乘法(PLS)和支持向量回归(SVR)定量模型.结果:在一致性评价中61批生姜配方颗粒的指纹图谱与对照指纹图谱的相关系数均大于0.97,不同样品批次间一致性良好.在所建立的定量模型中,最优PLS模型的校正均方根误差(RMSEC)为0.071 1、校正相关系数(RC)为0.624 0、预测均方根误差(RMSEP)为0.065 4、预测相关系数(RP)为0.700 9,最优SVR模型的RMSEC为0.044 8、RC为0.919 8、RMSEP为0.066 3、RP为0.776 5.结论:所建立的SVR定量模型较PLS定量模型具有更好的预测性能,能够对6-姜辣素含量进行快速预测.本研究基于便携式近红外光谱仪对生姜配方颗粒进行了有效、快速、无损的质量分析,为生姜配方颗粒的质量控制提供新的方法参考.

Abstract

Objective:To establish a method for the consistency evaluation and quantitative analysis of near in-frared spectroscopy(NIRS)of ginger formula granules.Methods:NIR spectral information of ginger formula granules samples were collected using a portable NIR spectrometer.The fingerprints of 61 batches of ginger for-mula granules samples were tested for consistency with the control fingerprints,and evaluated using correlation coefficients.The content of 6-gingerol in the ginger formula granules samples was determined by high perfor-mance liquid chromatograph(HPLC).The effects of different preprocessing methods on the parameters of the quantitative model were investigated,and the partial least squares(PLS)and support vector regression(SVR)quantitative models were established.Results:In the consistency evaluation,the correlation coefficients between the fingerprints of the 61 batches of ginger formula granules and the control fingerprints were all greater than 0.97 in the consistency test,the batch-to-batch consistency of the ginger formula granules samples was good.Among the established quantitative models,the optimal PLS model had a root mean square error of correction(RMSEC)of 0.0711,along with a correlation coefficient of correction(RC)of 0.6240.Additionally,the root mean square error of prediction(RMSEP)for this model was 0.0654,and the correlation coefficient of prediction(RP)was 0.7009.For the SVR model,the RMSEC was 0.0448 with an RC of 0.9198,while the RMSEP was 0.0663,and the RP stood at 0.7765.Conclusion:The SVR quantitative model has better predictive performance than the PLS quantitative model,and can rapidly predict the content of 6-gingerol.This research performs effective,rapid and nondestructive quality analysis of ginger formulation granules based on the portable near infrared spectrome-ter,which provides a new method reference for the quality control of ginger formula granules.

关键词

生姜配方颗粒/6-姜辣素/近红外光谱/一致性评价/定量分析

Key words

ginger formula granules/6-gingerol/near infrared spectroscopy/consistency evaluation/quantitative analysis

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基金项目

国家自然科学基金(82060763)

广西科技重大专项(2022JBGS042)

出版年

2024
广西医科大学学报
广西医科大学

广西医科大学学报

CSTPCD
影响因子:0.788
ISSN:1005-930X
参考文献量20
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