紫外-可见分光光度法及近红外光谱技术在甘草质量快速分析中的应用研究
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摘要
针对目前甘草来源广泛,不同来源甘草在活性成分含量上存在显著性差异,甘草质量参差不齐,而采用HPLC对甘草进行定量分析的方法存在着诸如繁琐费时、分析成本高、在实际工作中较难推广等问题,因此,亟需一种简便、快速的甘草质量分析方法,能够简便快速地测定甘草中活性成分的含量。本文从建立定性、定量数学模型的角度,运用现代数理统计方法和统计分析软件,进一步研究了利用紫外-可见分光光度法、近红外光谱法及紫外光度计色度分析法快速分析甘草质量的方法。主要研究结果如下：
(1)在已有的甘草活性成分含量测定方法的基础上,建立了更为简便、快速的利用紫外-可见分光光度法测定甘草总皂苷、总黄酮含量的方法；建立了利用HPLC双波长法同时测定甘草中5种活性成分(甘草酸、甘草苷、甘草素、异甘草苷和异甘草素)含量的方法。
(2)甘草酸与总皂苷含量之间存在极显著的正相关关系,甘草苷、异甘草苷、甘草素及异甘草素均与总黄酮之间存在极显著的正相关关系；分别建立了通过总皂苷、总黄酮含量来判别甘草酸、甘草苷所属含量范围的判别模型,并对模型的预测结果进行了验证,验证结果表明甘草酸判别模型的平均判别准确率为91.3%,甘草苷判别模型的平均判别准确率为90.0%；分别建立了甘草酸与总皂苷、甘草苷与总黄酮含量之间的回归方程,并对方程的预测结果进行了验证,验证结果表明甘草酸回归方程的平均预测准确率为68.6%,甘草苷回归方程的平均预测准确率为75.3%。
(3)分别建立了野生和栽培甘草的近红外图谱与其甘草酸含量之间的校正模型,其甘草酸实测值和预测值之间的相关系数R均达到0.999以上,模型平均预测准确率分别为91.4%和95.7%；分别建立了野生和栽培甘草的近红外图谱与其甘草苷含量之间的校正模型,其甘草苷实测值和预测值之间的相关系数R分别为0.996和0.998,模型平均预测准确率分别为86.2%和93.2%；分别建立了野生和栽培甘草的近红外图谱与其异甘草苷含量之间的校正模型,其异甘草苷实测值和预测值之间的相关系数R均达到0.999以上,模型平均预测准确率为分别为89.4%和89.0%。
(4)不同表面颜色甘草在总皂苷、总黄酮、甘草酸、甘草苷、异甘草苷、甘草素和异甘草素这7种活性成分含量上均不存在显著性的差异,不同断面颜色甘草在总皂苷含量上存在极显著差异,在甘草酸、甘草苷、异甘草苷和甘草素含量上存在显著性差异；色度分析结果表明,甘草去皮粉末的颜色值中明度值L*与总皂苷含量和异甘草素含量存在显著的负相关关系,说明甘草去皮粉末颜色越白,其总皂苷含量和异甘草素含量越低；黄兰值b*与甘草酸含量存在显著的正相关关系,说明甘草去皮粉末颜色越黄,其甘草酸含量越高；黄色系数Y1分别与总皂苷和甘草酸含量间存在显著的正相关关系,说明甘草去皮粉末的黄色系数越高,总皂苷和甘草酸的含量越高。
(5)从简便、快速、经济、准确性等方面综合比较得出,近红外光谱法在甘草质量快速检测中是最有应用前景的方法,并对甘草酸、甘草苷和异甘草苷的NIR定量分析模型进行了再验证,再验证结果表明,甘草酸和甘草苷NIR定量分析模型的预测准确率较为稳定,可用于实际工作中,而异甘草苷NIR定量分析模型的预测准确率受样品的影响较大,还不够稳定。
In view of the situation that licorice from different sources exists significant differences in the active ingredient contents, Licorice quality is uneven. Now the commonly used detection mean for licorice quanlity is HPLC, but HPLC has several shortages such as time-consuming, high analysis cost and low applicability. So, a simple and rapid quality analysis method to detect the active ingredient in licorice is necessary. This paper starts form the view of establishing qualitative and quantitative mathematical models, with the use of mathematical statistics method and statistic analysis software, in order to develop a simple and rapid quanlity analysis method for licorice with the application of uv-vis spectrophotometry, the near infrared spectroscopy and chromaticity analysis method respective. The main research results are as follows:
(1) On the basis of the existing determination method for licorice active ingredients, this paper has established a more simple and rapid determination method for total Licorice saponins and flavonoids with the use of uv-vis spectrophotometry; has established a method to determinate glycyrrhizin, liquiritin, liquiritigenin, isoliquiritin and isoliquiritigenin simultaneously with the use of HPLC.
(2) There exsits a very significant positive correlation between glycyrrhizin and total saponins, there also exsits a very significant positive correlation between liquiritin, liquiritigenin, isoliquiritin, isoliquiritigenin and total flavonoids. This paper has established discriminant models, through which we can discriminant the contents range of glycyrrhizin and liquiritin only if we get the contents of total saponins and total flavonoids, the discriminant accuracy of glycyrrhizin discriminant model is91.3%, and the discriminant accuracy of liquiritin discriminant model is90.0%; this paper has established linear regression models, through which we can estimiate the contents of glycyrrhizin and liquiritin only if we get the contents of total saponins and total flavonoids, the estimiate accuracy of glycyrrhizin discriminant model is68.6%and the estimiate accuracy of liquiritin discriminant model is75.3%.
(3) This paper has established calibration models between glycyrrhizin content and NIR spectrum of wild and cultivated licorice, the R of the wild and cultivated calibration models are both above0.999, the predicting accuracy are91.4%and95.7%respective; has eatabliseh calibration models between liquirtin content and NIR spectrum of wild and cultivated licorice, the R of the wild and cultivated calibration models are0.996and0.998respective, the the predicting accuracy are86.2%and93.2%respective; has eatabliseh calibration models between isoliquirtin content and NIR spectrum of wild and cultivated licorice, the R of the wild and cultivated calibration models are both above0.999, the the predicting accuracy are89.4%and89.0%respective.
(4) There don't exist significant differences between licorice with different surface colour in total saponins, total flavonoids, glycyrrhizin, liquiritin, liquiritigenin, isoliquiritin and isoliquiritigenin contents, but licorice with different Section color has very significant differences in total saponins contents and has significant differences in glycyrrhizin, liquiritin, liquiritigenin and liquiritin, contents. The chromaticity analysis results shows that the Lightness value L*of the licorice powder with shin off has significant negative correlation with total saponins and isoliquiritigenin content, and the yellow value b*has significant positive correlation with glycyrrhizin content, and the yellow index Y1has significant positive correlation with total saponins and glycyrrhizin content.
(5) NIR is the most suitable method in the Licorice quality fast detection from the speediness, simplification, economy and accuracy aspects. This paper has revalidated the glycyrrhizin, liquiritin and isoliquiritin NIR models. The results show that the glycyrrhizin and liquiritin NIR models are stable, but the isoliquirtin NIR model is unstable.
(1)在已有的甘草活性成分含量测定方法的基础上,建立了更为简便、快速的利用紫外-可见分光光度法测定甘草总皂苷、总黄酮含量的方法；建立了利用HPLC双波长法同时测定甘草中5种活性成分(甘草酸、甘草苷、甘草素、异甘草苷和异甘草素)含量的方法。
(2)甘草酸与总皂苷含量之间存在极显著的正相关关系,甘草苷、异甘草苷、甘草素及异甘草素均与总黄酮之间存在极显著的正相关关系；分别建立了通过总皂苷、总黄酮含量来判别甘草酸、甘草苷所属含量范围的判别模型,并对模型的预测结果进行了验证,验证结果表明甘草酸判别模型的平均判别准确率为91.3%,甘草苷判别模型的平均判别准确率为90.0%；分别建立了甘草酸与总皂苷、甘草苷与总黄酮含量之间的回归方程,并对方程的预测结果进行了验证,验证结果表明甘草酸回归方程的平均预测准确率为68.6%,甘草苷回归方程的平均预测准确率为75.3%。
(3)分别建立了野生和栽培甘草的近红外图谱与其甘草酸含量之间的校正模型,其甘草酸实测值和预测值之间的相关系数R均达到0.999以上,模型平均预测准确率分别为91.4%和95.7%；分别建立了野生和栽培甘草的近红外图谱与其甘草苷含量之间的校正模型,其甘草苷实测值和预测值之间的相关系数R分别为0.996和0.998,模型平均预测准确率分别为86.2%和93.2%；分别建立了野生和栽培甘草的近红外图谱与其异甘草苷含量之间的校正模型,其异甘草苷实测值和预测值之间的相关系数R均达到0.999以上,模型平均预测准确率为分别为89.4%和89.0%。
(4)不同表面颜色甘草在总皂苷、总黄酮、甘草酸、甘草苷、异甘草苷、甘草素和异甘草素这7种活性成分含量上均不存在显著性的差异,不同断面颜色甘草在总皂苷含量上存在极显著差异,在甘草酸、甘草苷、异甘草苷和甘草素含量上存在显著性差异；色度分析结果表明,甘草去皮粉末的颜色值中明度值L*与总皂苷含量和异甘草素含量存在显著的负相关关系,说明甘草去皮粉末颜色越白,其总皂苷含量和异甘草素含量越低；黄兰值b*与甘草酸含量存在显著的正相关关系,说明甘草去皮粉末颜色越黄,其甘草酸含量越高；黄色系数Y1分别与总皂苷和甘草酸含量间存在显著的正相关关系,说明甘草去皮粉末的黄色系数越高,总皂苷和甘草酸的含量越高。
(5)从简便、快速、经济、准确性等方面综合比较得出,近红外光谱法在甘草质量快速检测中是最有应用前景的方法,并对甘草酸、甘草苷和异甘草苷的NIR定量分析模型进行了再验证,再验证结果表明,甘草酸和甘草苷NIR定量分析模型的预测准确率较为稳定,可用于实际工作中,而异甘草苷NIR定量分析模型的预测准确率受样品的影响较大,还不够稳定。
In view of the situation that licorice from different sources exists significant differences in the active ingredient contents, Licorice quality is uneven. Now the commonly used detection mean for licorice quanlity is HPLC, but HPLC has several shortages such as time-consuming, high analysis cost and low applicability. So, a simple and rapid quality analysis method to detect the active ingredient in licorice is necessary. This paper starts form the view of establishing qualitative and quantitative mathematical models, with the use of mathematical statistics method and statistic analysis software, in order to develop a simple and rapid quanlity analysis method for licorice with the application of uv-vis spectrophotometry, the near infrared spectroscopy and chromaticity analysis method respective. The main research results are as follows:
(1) On the basis of the existing determination method for licorice active ingredients, this paper has established a more simple and rapid determination method for total Licorice saponins and flavonoids with the use of uv-vis spectrophotometry; has established a method to determinate glycyrrhizin, liquiritin, liquiritigenin, isoliquiritin and isoliquiritigenin simultaneously with the use of HPLC.
(2) There exsits a very significant positive correlation between glycyrrhizin and total saponins, there also exsits a very significant positive correlation between liquiritin, liquiritigenin, isoliquiritin, isoliquiritigenin and total flavonoids. This paper has established discriminant models, through which we can discriminant the contents range of glycyrrhizin and liquiritin only if we get the contents of total saponins and total flavonoids, the discriminant accuracy of glycyrrhizin discriminant model is91.3%, and the discriminant accuracy of liquiritin discriminant model is90.0%; this paper has established linear regression models, through which we can estimiate the contents of glycyrrhizin and liquiritin only if we get the contents of total saponins and total flavonoids, the estimiate accuracy of glycyrrhizin discriminant model is68.6%and the estimiate accuracy of liquiritin discriminant model is75.3%.
(3) This paper has established calibration models between glycyrrhizin content and NIR spectrum of wild and cultivated licorice, the R of the wild and cultivated calibration models are both above0.999, the predicting accuracy are91.4%and95.7%respective; has eatabliseh calibration models between liquirtin content and NIR spectrum of wild and cultivated licorice, the R of the wild and cultivated calibration models are0.996and0.998respective, the the predicting accuracy are86.2%and93.2%respective; has eatabliseh calibration models between isoliquirtin content and NIR spectrum of wild and cultivated licorice, the R of the wild and cultivated calibration models are both above0.999, the the predicting accuracy are89.4%and89.0%respective.
(4) There don't exist significant differences between licorice with different surface colour in total saponins, total flavonoids, glycyrrhizin, liquiritin, liquiritigenin, isoliquiritin and isoliquiritigenin contents, but licorice with different Section color has very significant differences in total saponins contents and has significant differences in glycyrrhizin, liquiritin, liquiritigenin and liquiritin, contents. The chromaticity analysis results shows that the Lightness value L*of the licorice powder with shin off has significant negative correlation with total saponins and isoliquiritigenin content, and the yellow value b*has significant positive correlation with glycyrrhizin content, and the yellow index Y1has significant positive correlation with total saponins and glycyrrhizin content.
(5) NIR is the most suitable method in the Licorice quality fast detection from the speediness, simplification, economy and accuracy aspects. This paper has revalidated the glycyrrhizin, liquiritin and isoliquiritin NIR models. The results show that the glycyrrhizin and liquiritin NIR models are stable, but the isoliquirtin NIR model is unstable.
引文
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