基于近红外光谱结合化学计量学的气滞胃痛颗粒中芍药苷的检测研究
Determination of Paeoniflorin in Qizhiweitong Granules Based on Near Infrared Spectroscopy Combined with Chemometrics
DOI: 10.12677/PI.2021.106042, PDF,    科研立项经费支持
作者: 程 杰, 杨炳朝, 史 泳, 潘 英, 韩 凌, 邵 平:辽宁华润本溪三药有限公司,辽宁 本溪;陈 洁, 黄家鹏, 王 钧, 李页瑞:苏州泽达兴邦医药科技有限公司,江苏 苏州
关键词: 气滞胃痛颗粒一步制粒近红外光谱技术偏最小二乘法在线监测Qizhi Weitong Granules One-Step Granulation Near Infrared Spectroscopy Partial Least Squares Method Online Analytical Technology
摘要: 目的:研究近红外光谱在一步制粒过程中监测气滞胃痛颗粒芍药苷含量的可行性。方法:利用近红外在线检测系统,非接触式探头对制粒过程进行全程近红外光谱扫描,对采集到的光谱进行预处理和波段选择,并结合偏最小二乘法(partial least squares, PLS)建立芍药苷含量快速无损检测方法。结果:所建立的模型的决定系数R为0.9172,交叉验证均方根差值为0.535,验证集样品预测统计分析得出预测值与真实值之间无显著差异(P > 0.05)。结论:所建立的模型准确度高,适用于气滞胃痛一步制粒过程中芍药苷含量的实时预测。
Abstract: Objective: To study the feasibility of paeoniflorin content in Qizhiweitong granules by near infrared spectroscopy in one-step granulation process. Methods: Using near infrared online detection system, the non-contact probe was used to scan the whole process of granulation by near-infrared spectroscopy. The spectra of the samples were pretreated and the bands were selected. A fast and nondestructive method for the paeoniflorin content was established by using partial least squares (PLS). Results: The determination coefficient R of the established model was 0.9172, and the root mean square difference of cross-validation was 0.535. The samples of the validation set were predicted and statistically analyzed, and there was no significant difference between the predicted value and the true value (P > 0.05). Conclusion: The established model has high accuracy and is suitable for real-time prediction of paeoniflorin content in one-step granulation process of Qizhi Weitong granules.
文章引用:程杰, 陈洁, 杨炳朝, 黄家鹏, 史泳, 潘英, 韩凌, 邵平, 王钧, 李页瑞. 基于近红外光谱结合化学计量学的气滞胃痛颗粒中芍药苷的检测研究[J]. 药物资讯, 2021, 10(6): 339-345. https://doi.org/10.12677/PI.2021.106042

参考文献

[1] 孙方圆. 气滞胃痛颗粒治疗功能性消化不良的脑肠轴机制研究[D]: [硕士学位论文]. 天津: 天津医科大学, 2017.
[2] 于婷, 王帅, 孟宪生, 等. 气滞胃痛颗粒防治反流性胃炎的药效及作用机制初步研究[J]. 中药材, 2015, 38(9): 1933-1936.
[3] 姚东, 孟宪生, 潘英, 等. 气滞胃痛颗粒镇痛作用研究及机制初探[J]. 中成药, 2012, 34(3): 556-558.
[4] 国家药典委员会. 中国药典[M]. 北京: 中国医药科技出版社, 2020: 699.
[5] Wu, S.H., Wu, D.G. and Chen, Y.W. (2010) Chemical Constituents and Bioactivities of Plants from the Genus Paeonia. Chem Biodivers, 7, 90-104.
[6] 孙丽荣, 曹雄, 候凤青, 等. 芍药苷研究进展[J]. 中国中药杂志, 2008, 33(18): 2028-2032.
[7] 汪宝成. 固体制剂不同制粒方法的常见问题及特点分析[J]. 机电信息, 2018, 563(29): 39-42.
[8] 屈凌波, 相秉仁, 吴拥军, 等. 近红外反射光谱分析在抗生素片剂质量控制中的应用[J]. 计算机与应用化学, 2002, 19(3): 320-322.
[9] 康绍建, 罗茜. HPLC法测定感冒疏风片中芍药苷的含量[J]. 中国民族民间医药, 2021, 30(13): 67-68+74.
[10] 冯艳春, 张琪, 胡昌勤. 药品近红外光谱通用性定量模型评价参数的选择[J]. 光谱学与光谱分析, 2016, 36(8): 2447-2454.
[11] Williams, P.C. and Norris, K. (2001) Near-Infrared Technology in the Agricultural and Food Industries. American Association of Cereal Chemists Press, 9, 145-149.
[12] Bleye, C.D., Chavez, P.F., Man-tanus, J., et al. (2012) Critical Review of Near-Infrared Spectroscopic Methods Validations in Pharmaceutical Applica-tions. Journal of Pharmaceutical & Biomedical Analysis, 69, 125-132. [Google Scholar] [CrossRef] [PubMed]