1.山东大学 齐鲁医学院 药学院,山东 济南 250012
2.山东大学 国家糖工程技术研究中心, 山东 济南 250012
3.山东大学 化学生物学教育部重点实验室,山东 济南 250012
4.华熙生物科技股份有限公司,山东 济南 260000
5.药物制剂技术研究与评价” 国家药品监督管理局重点实验室,山东 济南 250012
臧恒昌,博士,教授,研究方向:药物制剂技术研究与评价、药品监管科学,E-mail:zanghcw@126.com
郭学平,博士,研究员,研究方向:生物制药,微生物发酵技术,E-mail:guoxp@bloomagefreda.com
扫 描 看 全 文
杨向春,陈丽芳,王浩伟等.近红外光谱技术在川麦冬原位检测中的应用研究[J].分析测试学报,2023,42(08):943-951.
YANG Xiang-chun,CHEN Li-fang,WANG Hao-wei,et al.Research on Application of Near Infrared Spectroscopy in Situ Detection of Sichuan Ophiopogon Japonicus[J].Journal of Instrumental Analysis,2023,42(08):943-951.
杨向春,陈丽芳,王浩伟等.近红外光谱技术在川麦冬原位检测中的应用研究[J].分析测试学报,2023,42(08):943-951. DOI: 10.19969/j.fxcsxb.23050606.
YANG Xiang-chun,CHEN Li-fang,WANG Hao-wei,et al.Research on Application of Near Infrared Spectroscopy in Situ Detection of Sichuan Ophiopogon Japonicus[J].Journal of Instrumental Analysis,2023,42(08):943-951. DOI: 10.19969/j.fxcsxb.23050606.
原药材检测费时费力一直是川麦冬质量分析中亟待解决的问题。该文将近红外光谱分析技术应用于川麦冬原药材的质量分析,以漫反射模式对麦冬颗粒进行无损原位检测后,采用光谱预处理方法减少因粒径造成的干扰,通过变量筛选方法提取有效信息,最终建立了快速定量分析模型。结果表明,水分、浸出物和总皂苷含量模型的验证均方根误差(RMSEP)分别为0.165 5%、0.401 9%、0.078 4%,验证集决定系数(,R,,https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=49026909&type=,https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=49026923&type=,2.20133328,3.72533321,)分别为0.965 1、0.696 5、0.803 6,相对分析误差(RPD)分别为4.50、2.68、2.22,3个质量指标的RPD均大于2,说明模型性能较好,能够满足川麦冬质量分析的要求。该法通过近红外光谱技术采集川麦冬颗粒的原位光谱,避免了粉碎,真正意义上实现了川麦冬无损、绿色、快速的含量分析,为川麦冬的质量分析提供了参考。
Sichuan Ophiopogon japonicus is an important medicine and is widely used in clinic as it has the effects of nourishing yin and nourishing fluid,moistening lung and clearing heart.However,time-consumption and no on-site detection of the original medicinal material have always been the urgent problems to solve in its quality analysis.In this paper,near infrared spectroscopy was applied to the quality analysis of Sichuan Ophiopogon japonicus.Different grades of Sichuan Ophiopogon japonicus were collected,and the content data of water,extract and total saponins were determined by segmented experiment.In-situ and non-destructive detection of Sichuan Ophiopogon japonicus granules was performed by diffuse reflectance mode,and its near infrared spectra were collected.Meanwhile,different spectral pretreatment methods were used to deal with the spectrum in order to reduce the interference caused by particle size to the spectrum.The best pretreatment methods for moisture,extract and total saponins were multivariate scattering correction combined with standardization,multivariate scattering correction combined with first-order derivative,SG smoothing and mean center,respectively.Moreover,the variable screening method was used to extract the effective information in the spectrum,the best band screening method for moisture was piecewise random frog,and the best band selection method for extract and total saponins was variable importance projection.Finally,the model was established according to the optimal pretreatment method and the optimal variable screening method.The root mean square errors(RMSEP) of the model for moisture,extract and total saponins were 0.165 5%,0.401 9% and 0.078 4%,respectively,and the determination coefficients for validation(,R,,https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=49026948&type=,https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=49026943&type=,2.53999996,4.31799984,) were 0.965 1,0.696 5 and 0.803 6,respectively.The relative percent deviations(RPDs) were 4.50,2.68 and 2.22,respectively.The RPDs for the three quality indicators were all greater than 2,indicating that the performance of the model was good,and the model built in this paper could meet the requirements for quality analysis.In this paper,a near-infrared quantitative model for water,extract and total saponins in Sichuan Ophiopogon japonicus was established by in-situ detection and parameter optimization,which could meet the needs of “rapid and non-destructive” in collection,processing and product testing,realizing a new real-time and green analysis for the quality control of Sichuan Ophiopogon japonicus,and providing a reference for the quality analysis of Sichuan Ophiopogon japonicus.
川麦冬近红外光谱质量分析原位检测水分浸出物总皂苷
Sichuan Ophiopogon japonicusnear infrared spectroscopyquality analysisin situ detectionwaterextracttotal saponins
Yang N,Zhang F,Yu M H,Yang J D,Zhu J X,Sun H F.Asia-Pacific Tradit. Med. (杨娜,张帆,于明慧,杨居东,朱俊秀,孙慧峰.亚太传统医药),2023,19(3):170-173.
Liu K H,Tang S Y,Zhao L Y,Zhang Q Y,Zhu L L,Zhu B,Zhang Q L,Sun Y Q,Qin L P.Chin. Tradit. Herb. Drugs(刘考铧,唐诗怡,赵露颖,张巧艳,朱露林,朱波,张泉龙,孙艺琦,秦路平.中草药),2021,52(6):1765-1771.
Li H Y,Cai X Y,Yang R S,Tao L,Li M.Chin. Tradit. Pat. Med. (李红彦,蔡晓洋,杨瑞山,陶玲,李敏.中成药),2023,45(2):641-646.
Gu Z R,Li Q,Lü X,Sun L P,Qi M,Ge B.Chin. Tradit. Pat. Med. (顾志荣,李芹,吕鑫,孙岚萍,祁梅,葛斌.中成药),2021,43(6):1513-1520.
Yang Z Y,Cai L W,Han L J,Fan X,Liu X.J. Near Infrared Spectrosc.,2021,29(6):313-320
Sun J Y,Pang R C,Chen S S,Chen H C,Xie Y R,Chen D D,Wu K,Liang J B,Yan K C,Hao Z F.J. Innovative Opt. Health Sci.,2021,14(6):2130006.
Qi M,Gu Z R,Li Q,Wang A H,Ge B.Chin. J. Inf. Tradit. Chin. Med. (祁梅,顾志荣,李芹,王安红,葛斌.中国中医药信息杂志),2023,30(3):114-120.
Zhang H M,Liu X,Li D K,Zhou D Z,Ju A C,Ye Z L.J. Tianjin Tradit. Chin. Med. Univ. (张会梅,刘雪,李德坤,周大铮,鞠爱春,叶正良.天津中医药大学学报),2018,37(5):416-419.
Zhang J J,Wang Y.Chin. J. Spectrosc. Lab. (张娟娟,王远.光谱实验室),2012,29(1):551-555.
Wang Y,Qin M J,Qi J,Yu B Y,Tang L.Spectrosc. Spectral Anal. (王远,秦民坚,戚近,余伯阳,唐莉.光谱学与光谱分析),2009,29(10):2677-2680.
Chinese Pharmacopoeia Commission. Pharmacopoeia of the People’s Republic of China. Beijing:China Medical Science Press(国家药典委员会. 中华人民共和国药典. 北京:中国医药科技出版社),2020:162.
Luo L,Tuo X G,Zhang G Y,Zhai S,Zhu X M,Gao J,Luo Q.J. Food Saf. Qual. 罗林,庹先国,张贵宇,翟双,朱雪梅,高婧,罗琪.食品安全质量检测学报),2022,13(9):3017-3025.
Chen Y F,Nie B,Zhan G P,Zhou G R,Li H,He Y.J. Jiangxi Tradit. Chin. Med. Univ. (陈裕凤,聂斌,詹国平,周冠芮,李欢,何雁.江西中医药大学学报),2022,34(2):120-124.
Zhao J Y,Xiong Z X,Ning J M,Xie D H.J. Anal. Sci. (赵静远,熊智新,宁井铭,谢德红.分析科学学报),2021,37(5):611-617.
Zhang J,Hu Y,Zhou L X,Li B Y.J. Instrum. Anal. (张进,胡芸,周罗雄,李博岩.分析测试学报),2020,39(10):1196-1203.
Dantas D A M W,Oliveira D F D,Câmara C R,Gomes D L K M,Carlos C J L,Henriqued A T G.J. Sci. Food Agric.,2018,98(15):5750-5755.
Zhang J,Guo Z,Ren Z S,Wang S H,Yue M H,Zhang S S,Yin X,Gong K J,Ma C Y.J. Food,2023,117:105134.
Li H H,Zhu J J,Jiao T H,Wang B,Wei W Y,Ali S J,Ouyang Q,Zuo M,Chen Q S.J. Spectrochim. Acta A,2020,243:118765.
0
浏览量
9
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构