Response Surface Optimization for Water-Assisted Extraction of Two Saponins from Paris polyphylla var. yunnanensis Leaves

Molecules. 2024 Apr 6;29(7):1652. doi: 10.3390/molecules29071652.

Abstract

The process of extracting polyphyllin II and polyphyllin VII by water-assisted extraction was established and optimized in this study. Response surface methodology was used to establish a prediction model to optimize the extraction conditions. Based on the one-way test, the Box-Behnken design with three factors and three levels was used for the experimental program, and the composition analysis was carried out by high-performance liquid chromatography (HPLC). The optimal extraction conditions for polyphyllin II and polyphyllin VII were as follows: extraction time of 57 and 21 min, extraction temperature of 36 and 32 °C, solid-to-liquid ratio of 1:10 and 1:5 g/mL, respectively, and the yields of polyphyllin II and polyphyllin VII were 1.895 and 5.010%, which was similar to the predicted value of 1.835 and 4.979%. The results of the ANOVA showed that the model fit was good, and the Box-Behnken response surface method could optimize the water-assisted extraction of saponins from the leaves of Paris polyphylla var. yunnanensis. This study provides a theoretical basis for the application of polyphyllin II and polyphyllin VII in pharmaceutical production.

Keywords: Box–Behnken response surface methodology; Paris polyphylla var. yunnanensis; extraction process; saponins; water-assisted extraction.

MeSH terms

  • Chromatography, High Pressure Liquid
  • Liliaceae*
  • Plant Leaves
  • Saponins*
  • Water

Substances

  • Saponins
  • Water

Grants and funding

This study was supported by the Project of Yunnan Provincial Department of Education Science Research Fund (2022J0503), the Opening Project of Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education (KLESWFU201903 and KLESWFU-202010), Yunnan Fundamental Research Projects (202201AU070072 and 202301AT070216), and Foundation of Yunnan Agricultural Basic Research (202101BD070001-033).