中国现代中药2024，Vol.26Issue(12)：2042-2048,7.DOI:10.13313/j.issn.1673-4890.20240116001
当归和独活的数字化鉴定方法研究
Digital Identification of Angelicae Sinensis Radix and Angelicae Pubescentis Radix
摘要
Abstract
Objective:To explore a method for the digital identification and analysis of Angelicae Sinensis Radix(ASR)and Angelicae Pubescentis Radix(APR)based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-QTOF-MS)analysis and quantization processing.Methods:UPLC-QTOF-MS was utilized to analyze ASR and APR.Progenesis QI software was used for peak correction and extraction,converting the mass spectra of ASR and APR into data matrices(retention time-mass to charge ratio-ionic intensity).Feature screening was further conducted based on information gain and information gain ratio.Data identification models were then established using artificial neural networks(ANNs),support vector machines(SVM),logistic regression(LR),and K-nearest neighbors(KNN)machine learning algorithms.Cross-validation and model analysis were employed to select the best model for the digital identification and analysis of ASR and APR.Results:A total of 603 feature data variables were obtained through feature screening.Compared with the SVM,LR,and KNN algorithm models,the identification model constructed with the screened feature data and ANNs algorithm demonstrated the best recognition effect,with both accuracy and precision rates of 100%and an area under the ROC curve of 1.000.External validation confirmed that the model could accurately identify ASR and APR.Conclusion:The digital identification of ASR and APR can be efficiently and accurately achieved based on UPLC-QTOF-MS quantized data combined with the ANNs algorithm.This method can provide a reference for the digital identification and analysis of Chinese medicine.关键词
当归/独活/机器学习/特征筛选/数字化/超高效液相色谱-四级杆飞行时间质谱法Key words
Angelicae Sinensis Radix/Angelicae Pubescentis Radix/machine learning/feature screening/digitization/UPLC-QTOF-MS分类
医药卫生引用本文复制引用
付娆,程显隆,魏锋,张明童,马潇,张佳婷,贺方良,王献瑞,郭晓晗,荆文光,李明华,余坤子,杨建波..当归和独活的数字化鉴定方法研究[J].中国现代中药,2024,26(12):2042-2048,7.基金项目
国家重点研发计划"中医药现代化"重大专项(2023YFC3504105) （2023YFC3504105）
中药材及饮片质量控制重点实验室项目(2022GSMPA-KL03) （2022GSMPA-KL03）
中国食品药品检定研究院学科带头人培养基金项目(2023X10) （2023X10）
