Dataset Information

Optimization of Ultrasonic-Assisted Extraction Conditions for Bioactive Components and Antioxidant Activity of Poria cocos (Schw.) Wolf by an RSM-ANN-GA Hybrid Approach.

ABSTRACT: In this study, a response surface methodology and an artificial neural network coupled with a genetic algorithm (RSM-ANN-GA) was used to predict and estimate the optimized ultrasonic-assisted extraction conditions of Poria cocos. The ingredient yield and antioxidant potential were determined with different independent variables of ethanol concentration (X₁; 25-75%), extraction time (X₂; 30-50 min), and extraction solution volume (mL) (X₃; 20-60 mL). The optimal conditions were predicted by the RSM-ANN-GA model to be 55.53% ethanol concentration for 48.64 min in 60.00 mL solvent for four triterpenoid acids, and 40.49% ethanol concentration for 30.25 min in 20.00 mL solvent for antioxidant activity and total polysaccharide and phenolic contents. The evaluation of the two modeling strategies showed that RSM-ANN-GA provided better predictability and greater accuracy than the response surface methodology for ultrasonic-assisted extraction of P. cocos. These findings provided guidance on efficient extraction of P. cocos and a feasible analysis/modeling optimization process for the extraction of natural products.

SUBMITTER: Chen S

PROVIDER: S-EPMC9914185 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Optimization of Ultrasonic-Assisted Extraction Conditions for Bioactive Components and Antioxidant Activity of Poria cocos (Schw.) Wolf by an RSM-ANN-GA Hybrid Approach.

Chen Shiqi S Zhang Huixia H Yang Liu L Zhang Shuai S Jiang Haiyang H

Foods (Basel, Switzerland) 20230201 3

In this study, a response surface methodology and an artificial neural network coupled with a genetic algorithm (RSM-ANN-GA) was used to predict and estimate the optimized ultrasonic-assisted extraction conditions of Poria cocos. The ingredient yield and antioxidant potential were determined with different independent variables of ethanol concentration (X1; 25-75%), extraction time (X2; 30-50 min), and extraction solution volume (mL) (X3; 20-60 mL). The op ...[more]

PMID: 36766147

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Project description:(1)Objective: In this study, a quantitative analysis of chemical groups (the triterpenoids, water-soluble polysaccharides, and acidic polysaccharides) and quantitative high liquid performance chromatography (HPLC) fingerprint of Poria cocos (Schw.) Wolf (PC) for quality control was developed. (2)&nbsp;Methodology: First, three main chemical groups, including triterpenoids, water-soluble polysaccharides, and acidic polysaccharides, in 16 batches of PC were evaluated by ultraviolet spectrophotometry. Afterward, the quantitative fingerprint of PC was established, and the alcohol extract of PC was further evaluated. The method involves establishing 16 batches of PC fingerprints by HPLC, evaluating the similarity of different batches of PC, and identifying eight bioactive components, including poricoic acid B (PAB), dehydrotumulosic acid (DTA), poricoic acid A (PAA), polyporenic acid C (PAC), 3-epidehydrotumulosic acid (EA), dehydropachymic acid (DPA), dehydrotrametenolic acid (DTA-1), and dehydroeburicoic acid (DEA), in PC by comparison with the reference substance. Combined with the quantitative analysis of multi-components by a single marker (QAMS), six bioactive ingredients, including PAB, DTA, PAC, EA, DPA, and DEA, in PC from different places were established. In addition, the multivariate statistical analyses, such as principal component analysis and heatmap hierarchical clustering analysis are more intuitive, and the visual analysis strategy was used to evaluate the content of bioactive components in 16 batches of PC. Finally, the analysis strategy of three main chemical groups in PC was combined with the quantitative fingerprint strategy, which reduced the error caused by the single method. (3)&nbsp;Results: The establishment of a method for the quantification of chemical groups and quantitative HPLC fingerprint of PC was achieved as demonstrated through the quantification of six triterpenes in PC by a single marker. (4)&nbsp;Conclusions: Through qualitative and quantitative chemical characterization, a multi-directional, simple and efficient routine evaluation method of PC quality was established. The results reveal that this strategy can provide an analytical method for the quality evaluation of PC and other Chinese medicinal materials.

Project description:Poria cocos (Schw.) Wolf is a saprophytic fungus that grows around the roots of old, dead pine trees. Fushen, derived from the sclerotium of P. cocos but also containing a young host pine root, has been widely used as a medicine and food in China, Japan, Korea, Southeast Asian countries, and some European countries. However, the compound variations at the different growth periods and in the different parts of Fushen have not previously been investigated. In this study, an untargeted metabolomics approach based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) and targeted quantitative analysis was utilized to characterize the temporal and spatial variations in the accumulation of specialized metabolites in Fushen. There were 119 specialized metabolites tentatively identified using the UPLC-Q/TOF-MS. The nine growth periods of Fushen were divided into four groups using partial least squares discrimination analysis (PLS-DA). Four different parts of the Fushen [fulingpi (FP), the outside of baifuling (BO), the inside of baifuling (BI), and fushenmu (FM)] were clearly discriminated using a PLS-DA and orthogonal partial least squares discrimination analysis (OPLS-DA). Markers for the different growth periods and parts of Fushen were also screened. In addition, the quantitative method was successfully applied to simultaneously determine 13 major triterpenoid acids in the nine growth periods and four parts. The quantitative results indicated that the samples in January, March, and April, i.e., the late growth period, had the highest content levels for the 13 triterpenoid acids. The pachymic acid, dehydropachymic acid, and dehydrotumulosic acid contents in the FM were higher than those in other three parts in March, whereas the poricoic acid B, poricoic acid A, polyporenic acid C, dehydrotratrametenolic acid, dehydroeburicoic acid, and eburicoic acid in FP were higher beginning in October. These findings reveal characteristics in temporal and spatial distribution of specialized metabolites in Fushen and provide guidance for the identification of harvesting times and for further quality evaluations.

Dataset Information

Optimization of Ultrasonic-Assisted Extraction Conditions for Bioactive Components and Antioxidant Activity of Poria cocos (Schw.) Wolf by an RSM-ANN-GA Hybrid Approach.

Publications

Optimization of Ultrasonic-Assisted Extraction Conditions for Bioactive Components and Antioxidant Activity of <i>Poria cocos</i> (Schw.) Wolf by an RSM-ANN-GA Hybrid Approach.

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