近红外光谱法测定片仔癀中皂苷类成分的含量
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摘要
应用近红外光谱技术(near infrared spectroscopy,NIRS)对片仔癀锭剂及粉末中的皂苷类成分进行快速定量分析。采集片仔癀锭剂及其粉末的近红外光谱,采用高效液相色谱法(high performance liquid chromatography,HPLC)测定片仔癀中三七皂苷R1、人参皂苷Rg1和人参皂苷Rb1的含量作为参考值,通过OPUS处理软件将片仔癀的近红外光谱图与皂苷类成分含量的参考值进行关联,结合偏最小二乘法(partial least squares,PLS)分别建立各待测组分的定量分析模型,并对模型进行验证。结果显示,锭剂模型中三七皂苷R1、人参皂苷Rg1、人参皂苷Rb1及其总和的内部交叉验证均方差RMSECV(root mean square error of cross-validation)分别为0. 095 1,0. 555,0. 414,0. 960 mg·g-1,粉末模型的RMSECV分别为0. 085 6,0. 443,0. 405,0. 913mg·g-1,经外部验证,锭剂模型中三七皂苷R1、人参皂苷Rg1、人参皂苷Rb1及其总和的预测均方差RMSEP(root mean square error of prediction)分别为0. 111,0. 274,0. 276,0. 807 mg·g-1,粉末模型的RMSEP分别为0. 059 2,0. 322,0. 327,0. 705 mg·g-1,预测值与化学测定值的平均相对标准偏差均小于2. 0%,在α=0. 05水平进行配对t检验,预测集样品预测值与实测值间无显著性差异。该研究所建立的模型性能较好,对片仔癀中皂苷类成分含量预测准确,且该法操作简便、快速无损、环保,可用于片仔癀中皂苷类成分的快速检测和质量控制。
Near infrared spectroscopy(NIRS) was used for rapid quantitative analysis of saponins in Pien Tze Huang troches and powders. The near infrared spectra of Pien Tze Huang were collected,and the contents of notoginsenoside R1,ginsenoside Rg1 and ginsenoside Rb1 in Pien Tze Huang were determined by high performance liquid chromatography(HPLC) as the reference values. Then the near infrared spectra of the samples were associated with the reference values to establish the quantitative analysis models by using partial least squares(PLS) method. Finally,the models were verified by unknown samples. The results showed that root mean square error of cross-validation(RMSECV) of R1,Rg1,Rb1 and the total content was 0.095 1,0.555,0.414,0.960 mg·g-1 for the troches models,0.085 6,0.443,0.405,0.913 mg·g-1 for the powders models. After external validations,root mean square error of prediction(RMSEP) of R1,Rg1,Rb1 and the total content was 0.111,0.274,0.276,0.807 mg·g-1 for the troches models,0. 059 2,0. 322,0. 327,0. 705 mg·g-1 for the powders models. The averages of relative standard deviation between the predicted values and the chemical measured values were all less than 2.0%. According to the results of paired-t tests at the level of α = 0.05,there were no significant differences between the predicted values and the measured values. The established quantitative analysis models can be used to predict the contents of saponins in Pien Tze Huang accurately and the proposed method is simple,fast,non-destructive and environmentally friendly for the rapid detection and quality control of saponins in Pien Tze Huang.
Near infrared spectroscopy(NIRS) was used for rapid quantitative analysis of saponins in Pien Tze Huang troches and powders. The near infrared spectra of Pien Tze Huang were collected,and the contents of notoginsenoside R1,ginsenoside Rg1 and ginsenoside Rb1 in Pien Tze Huang were determined by high performance liquid chromatography(HPLC) as the reference values. Then the near infrared spectra of the samples were associated with the reference values to establish the quantitative analysis models by using partial least squares(PLS) method. Finally,the models were verified by unknown samples. The results showed that root mean square error of cross-validation(RMSECV) of R1,Rg1,Rb1 and the total content was 0.095 1,0.555,0.414,0.960 mg·g-1 for the troches models,0.085 6,0.443,0.405,0.913 mg·g-1 for the powders models. After external validations,root mean square error of prediction(RMSEP) of R1,Rg1,Rb1 and the total content was 0.111,0.274,0.276,0.807 mg·g-1 for the troches models,0. 059 2,0. 322,0. 327,0. 705 mg·g-1 for the powders models. The averages of relative standard deviation between the predicted values and the chemical measured values were all less than 2.0%. According to the results of paired-t tests at the level of α = 0.05,there were no significant differences between the predicted values and the measured values. The established quantitative analysis models can be used to predict the contents of saponins in Pien Tze Huang accurately and the proposed method is simple,fast,non-destructive and environmentally friendly for the rapid detection and quality control of saponins in Pien Tze Huang.
引文
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[12]唐海姣,匡艳辉,张偲偲,等.复方丹参片丹酚酸B和冰片近红外光谱测定和相关性模型建立[J].中国中药杂志,2018,43(14):2857.
[13]赖长江,周融融,余意,等.基于近红外分析和化学计量学方法对不同产地灵芝快速鉴别及多糖含量测定的研究[J].中国中药杂志,2018,43(16):3243.
[14]李勇,魏益民,王锋.影响近红外光谱分析结果准确性的因素[J].核农学报,2005,19(3):236.
[15]吴志生,杜敏,潘晓宁,等.粒径对多类中药材NIR频谱区的检测研究[J].中国中药杂志,2015,40(2):287.
[2]李冠烈.三七的现代研究与进展㈡[J].世界中西医结合杂志,2008,3(11):687.
[3]严衍禄,赵龙莲,韩东海,等.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005.
[4]王艳龙,王胜宝,李新生.近红外光谱技术在农业领域的应用及展望[J].安徽农学通报,2012,18(15):33.
[5]李宗朋,王健,宋全厚,等.近红外光谱技术在食品检测与质量控制中的应用[J].食品与发酵工业,2012,38(8):125.
[6]肖雪,梁琼麟,王义明,等.近红外光谱技术在医药领域中的应用进展[J].现代仪器,2011,17(5):9.
[7]孙通,耿响,刘木华.基于近红外光谱和变量优选的棉麻混纺织物棉含量快速检测[J].光谱学与光谱分析,2014,34(12):3257.
[8]何楚文,王立.近红外光谱的发展背景及在石油行业中的应用[J].广州化工,2015,43(7):44.
[9]钟英杰,李亮,庞云露,等.近红外光谱技术在中药研究中的应用[J].药物分析杂志,2015,35(10):1697.
[10]陈国权,潘红烨,刘雪松,等.感冒灵提取过程近红外光谱在线检测技术研究[J].中国中药杂志,2016,41(8):1383.
[11]白钢,丁国钰,侯媛媛,等.引进近红外技术用于中药材品质的快速评价[J].中国中药杂志,2016,41(19):3501.
[12]唐海姣,匡艳辉,张偲偲,等.复方丹参片丹酚酸B和冰片近红外光谱测定和相关性模型建立[J].中国中药杂志,2018,43(14):2857.
[13]赖长江,周融融,余意,等.基于近红外分析和化学计量学方法对不同产地灵芝快速鉴别及多糖含量测定的研究[J].中国中药杂志,2018,43(16):3243.
[14]李勇,魏益民,王锋.影响近红外光谱分析结果准确性的因素[J].核农学报,2005,19(3):236.
[15]吴志生,杜敏,潘晓宁,等.粒径对多类中药材NIR频谱区的检测研究[J].中国中药杂志,2015,40(2):287.