State Key Laboratory of Food Science and Resources, Jiangnan University, 214122 Wuxi, Jiangsu, China; Jiangsu Province International Joint Laboratory on Fresh Food Smart Processing and Quality Monitoring, Jiangnan University, 214122 Wuxi, Jiangsu, China.
State Key Laboratory of Food Science and Resources, Jiangnan University, 214122 Wuxi, Jiangsu, China; China General Chamber of Commerce Key Laboratory on Fresh Food Processing & Preservation, Jiangnan University, 214122 Wuxi, Jiangsu, China.
Food Chem. 2024 Jan 1;430:136990. doi: 10.1016/j.foodchem.2023.136990. Epub 2023 Jul 29.
Using natural deep eutectic solvents (NDES) for green extraction of lentinan from shiitake mushroom is a high-efficiency method. However, empirical and trial-and-error methods commonly used to select suitable NDES are unconvincing and time-consuming. Conductor-like screening model for realistic solvation (COSMO-RS) is helpful for the priori design of NDES by predicting the solubility of biomolecules. In this study, 372 NDES were used to evaluate lentinan dissolution capability via COSMO-RS. The results showed that the solvent formed by carnitine (15 wt%), urea (40.8 wt%), and water (44.2 wt%) exhibited the best performance for the extraction of lentinan. In the extraction stage, an artificial neural network coupled with genetic algorithm (ANN-GA) was developed to optimize the extraction conditions and to analyze their interaction effects on lentinan content. Therefore, COSMO-RS and ANN-GA can be used as powerful tools for solvent screening and extraction process optimization, which can be extended to various bioactive substance extraction.
采用天然深共熔溶剂（NDES）从香菇中绿色提取香菇多糖是一种高效的方法。然而，通常用于选择合适的 NDES 的经验和反复试验方法不够令人信服且耗时。通过预测生物分子的溶解度，用于实际溶剂化的导体样筛选模型（COSMO-RS）有助于对 NDES 进行先验设计。在这项研究中，使用了 372 种 NDES 通过 COSMO-RS 评估香菇多糖的溶解能力。结果表明，由肉碱（15wt%）、尿素（40.8wt%）和水（44.2wt%）形成的溶剂对香菇多糖的提取表现出最佳性能。在提取阶段，开发了人工神经网络与遗传算法（ANN-GA）相结合，以优化提取条件，并分析它们对香菇多糖含量的相互作用影响。因此，COSMO-RS 和 ANN-GA 可以用作溶剂筛选和提取过程优化的有力工具，可将其扩展应用于各种生物活性物质的提取。
