Efficient extraction and optimization procedures of polyphyllins from Paris polyphylla var chinensis by deep eutectic solvent coupled with ultrasonic-assisted extraction

Xiao-Li Tian,Ju-Zhao Liu, Li-Jie Jiang, Wei-Hua Kong,Yu-Jie Fu,Lu-Ping Qin,Qi Cui

MICROCHEMICAL JOURNAL(2024)

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摘要
As a rare and valuable Chinese herb, Paris polyphylla var chinensis has good pharmacological effects, among which Polyphyllins (PNs) are widely studied as the main active ingredients. Recently, alternative solvents namely, ionic liquids and deep eutectic solvents (DESs) have been used to extract active ingredients with remarkable efficiency. Compared to ionic liquids, deep eutectic solvents (DESs) were found to be effective with the added advantages of ease of production, economy and environment-protecting solvents to substitute common organic ones and have gradually become the research focus of green chemistry. In the present research, twelve varieties of DESs were tailored and PNs were successfully extracted by ultrasound assistance. Among them, combined with single-factor experiments and optimized using response surface methodology (RSM) and artificial neural network (ANN), a liquid-solid ratio of 41.72 mL/g, extraction temperature of 55.97 degrees C, extraction time of 30.21 min were the optimum extraction method with the overall PNs extraction yield of 52.56 mg/g. Moreover, DESs displayed superior extraction performance in PNs extraction than those traditional solvents. Overall, this study implied that DESs were more conducive to the full utilization and development of the resources of Paris polyphylla, which also confirmed the ability of DESs to effectively extract biologically active ingredients for next step adhibition.
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关键词
Artificial neural network,Deep eutectic solvent,Green extraction,Paris polyphylla,Polyphyllin,Response surface methodology
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