A hybrid RSM‐BPNN‐GA approach for optimizing ultrasound‐assisted deep eutectic solvents extraction conditions for Mesona chinensis benth. and investigation of the extraction mechanism

作者：Ping Xie, Ya‐Hui Ye, Chen‐Qing Wang, Jin‐Hai Shen, Lianghua Chen, Yanan Zhang · 发表于：Journal of Food Science · 年份：2024 · DOI：10.1111/1750-3841.17249 · 被引用次数：5 · 研究领域：Ionic liquids properties and applications、Essential Oils and Antimicrobial Activity、Analytical Chemistry and Chromatography

Mesona chinensis Benth (MCB) is the source of the most commonly consumed herbal beverage in Southeast Asia and China and is thus an economically important agricultural plant. Therefore, optimal extraction and production procedures have significant commercial value. Currently, in terms of green chemistry, researchers are investigating the use of greener solvents and innovative extraction techniques to increase extract yields. This study represents the first investigation of the optimal conditions for ultrasound-assisted deep eutectic solvent (DES) extraction from MCB. The major factors influencing ultrasound-assisted DESs were optimized using the response surface methodcentral-genetic algorithm-back propagation neural networks. This model demonstrated superior predictability and accuracy compared to the RSM model. Various types of DESs were used for the extraction of MCB constituents, with choline chloride-ethylene glycol resulting in the highest yield. The optimal conditions for maximal extraction were the use of choline chloride-ethylene glycol (1:4) as the solvent with a 40% water content, an extraction duration of 60 min at 60°C, and maintaining a leaf-to-solvent ratio of 20 mL/g. Noticeable enhancements in Van der Waals forces and more robust interactions between DESs and the target chemicals were observed relative to those seen with ethanol (70%, v/v) or water. This investigation not only introduced an environmentally friendly approach for highly efficient extraction fro...