Establishment of quantitative analysis model for quality control indexes of Farfarae Flos based on NIRS
- VernacularTitle:基于NIRS技术的款冬花药材质控指标定量分析模型的建立
- Author:
Tao GENG
1
;
Wenhui JIANG
1
;
Jialun LIU
1
;
Songping LAN
1
;
Liuying WANG
1
;
Peilin CHEN
1
;
Hanjing YAN
1
;
Shengguo JI
1
Author Information
1. School of Chinese Materia Medica，Guangdong Pharmaceutical University，Guangzhou 510006，China
- Publication Type:Journal Article
- Keywords:
Farfarae Flos;
near-infrared spectroscopy;
tussilagone;
rapid analysis;
quantitative analysis model;
quality evaluation
- From:
China Pharmacy
2024;35(9):1057-1063
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE To establish a quantitative analysis model for the contents of tussilagone， moisture， ethanol-soluble extract and total ash in Farfarae Flos based on near-infrared spectroscopy （NIRS）， providing a new idea for the rapid quality evaluation of Farfarae Flos and its preparations. METHODS Referring to the 2020 edition of the Chinese Pharmacopoeia， the contents of the main quality control indexes tussilagone， moisture， ethanol-soluble extract and total ash in 130 batches of Farfarae Flos from 19 producing areas were determined by HPLC， drying method， hot dip method and ash assay， respectively. The NIRS data information of the medicinal herbs of Farfarae Flos was collected， and then NIRS combined with the partial least squares method was used to establish the individual quantitative analysis models of the above quality control indexes in the samples， and the predictive model of the NIRS content was obtained after sample validation with validation set. RESULTS The range for the contents of tussilagone， moisture， ethanol-soluble extract and total ash in 130 batches of Farfarae Flos were 0.051 4%-0.103 5%， 7.75%-10.93%， 20.17%-31.12%， and 7.68%-12.10%， respectively. The internal cross-validation coefficients of determination （R2） of the established models for the quantitative analysis of tussilagone， moisture， ethanol-soluble extract and total ash in Farfarae Flos were 0.985 8， 0.968 4， 0.973 4， 0.988 0， respectively； the root mean square errors of calibration （RMSEC） were 0.001 54， 0.187， 0.478， 0.127， respectively； the root mean square errors of prediction （RMSEP） were 0.001 81， 0.212， 0.543， 0.149， respectively； RMSEP/RMSEC were 1.175 3， 1.133 7， 1.136 0 and 1.173 2， respectively， which were all within a reasonable range （1＜RMSEP/RMSEC≤1.2）. The mean absolute errors between the true and model-predicted values of the above four quality control indexes in the validation set of samples were －0.000 36， 0.061 43， 0.144 00， and 0.010 43， respectively，and the mean predicted recoveries were 99.65%， 100.72%，100.66%， and 100.15%， respectively. CONCLUSIONS The established NIRS quantitative analysis model has high stability and reliable results， which can be used for the rapid batch prediction of the content of relevant quality control indexes in Farfarae Flos.
