Optimization of extracting technology of iridoid glycosides and phenylethanoid glycosides from Pedicularis decora Franch. by G1-entropy-coupled response surface methodology and rapid identification by UPLC-Q/TOF-MS

Abstract

Quality control and clarifying ingredients are the foundation of pharmacodynamic material basis research. Pedicularis decora Franch. (P. decora) is clinically used to treat Alzheimer’s disease and exerts significant antioxidative, anti-inflammatory and neuroprotective effects. However, there is little systematic research on the extraction and composition and the current research on P. decora focused on the quality control and extraction with aucubin as only quality marker. It reported that Iridoid glycosides (IGs) and phenylpropanoid glycosides (PeGs), which are characteristic components of the Pedicularis species, have been reported to have various anti-Alzheimer’s activity. This study focused on the extraction and rapid qualitative analysis of IGs and PeGs in P. decora. First, HPLC-UV method was established to detect five IGs and PeGs analytes simultaneously and assess the effect of the extraction technology. Then, the G1-entropy method with the Box-Behnken response surface design methodology was used to optimized extraction technology. The optimum conditions were determined to be reflux with 55% methanol aqueous solutions, at 75 °C for 50 min. Finally, by establishing UPLC-Q/TOF-MS, 15 IGs and 15 PeGs in P. decora were rapidly identified and characterized for the first time. The results will provide a reverence of a higher quality standard and the pharmacodynamic material basis research.

Graphical Abstract

Keywords:

• Box-Behnken response surface design
• G1-entropy weight method
• iridoid glycosides
• phenylethanoid glycosides
• Pedicularis decora Franch.
• UPLC-Q/TOF-MS

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was funded by National Natural Science Foundations of China (no. 81603376), and the Natural Science Foundations of Shaanxi Province, China (no. 2020JM-017).