An integrated strategy of spectrum–effect relationship and near-infrared spectroscopy rapid evaluation based on back propagation neural network for quality control of Paeoniae Radix Alba

The quantitative analysis of near-infrared spectroscopy in traditional Chinese medicine has still deficiencies in the selection of the measured indexes. Then Paeoniae Radix Alba is one of the famous "Eight Flavors of Zhejiang" herbs, however, it lacks the pharmacodynamic support, and canno...

Full description

Saved in:
Bibliographic Details
Published in:Analytical sciences 2023-08, Vol.39 (8), p.1233-1247
Main Authors: Wang, Qi, Li, Huaqiang, You, Jinling, Yan, Binjun, Jin, Weifeng, Shen, Menglan, Sheng, Yunjie, He, Bingqian, Wang, Xinrui, Meng, Xiongyu, Qin, Luping
Format: Article
Language:English
Subjects:
Analytical Chemistry
Chemistry
Chemistry and Materials Science
Drugs, Chinese Herbal - chemistry
Drugs, Chinese Herbal - pharmacology
Neural Networks, Computer
Original Paper
Quality Control
Spectroscopy, Near-Infrared
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The quantitative analysis of near-infrared spectroscopy in traditional Chinese medicine has still deficiencies in the selection of the measured indexes. Then Paeoniae Radix Alba is one of the famous "Eight Flavors of Zhejiang" herbs, however, it lacks the pharmacodynamic support, and cannot reflect the quality of Paeoniae Radix Alba accurately and reasonably. In this study, the spectrum–effect relationship of the anti-inflammatory activity of Paeoniae Radix Alba was established. Then based on the obtained bioactive component groups, the genetic algorithm, back propagation neural network, was combined with near-infrared spectroscopy to establish calibration models for the content of the bioactive components of Paeoniae Radix Alba. Finally, three bioactive components, paeoniflorin, 1,2,3,4,6-O-pentagalloylglucose, and benzoyl paeoniflorin, were successfully obtained. Their near-infrared spectroscopy content models were also established separately, and the validation sets results showed the coefficient of determination (R 2  > 0.85), indicating that good calibration statistics were obtained for the prediction of key pharmacodynamic components. As a result, an integrated analytical method of spectrum–effect relationship combined with near-infrared spectroscopy and deep learning algorithm was first proposed to assess and control the quality of traditional Chinese medicine, which is the future development trend for the rapid inspection of traditional Chinese medicine. Graphical abstract
ISSN:0910-6340
1348-2246
DOI:10.1007/s44211-023-00334-4