School of Pharmacy, Quanzhou Medical College, Quanzhou 362011, China.
College of Veterinary Medicine, Northeast Agricultural University, Harbin 150006, China.
Molecules. 2024 Aug 21;29(16):3953. doi: 10.3390/molecules29163953.
The dried ripe fruit of Retz. is a common Chinese materia medica, and ellagic acid (EA), isolated from the plant, is an important bioactive component for medicinal purposes. This study aimed to delineate the optimal extraction parameters for extracting the EA content from Chebulae Fructus (CF), focusing on the variables of ethanol concentration, extraction temperature, liquid-solid ratio, and extraction time. Utilizing a combination of the response surface methodology (RSM) and an artificial neural network (ANN), we systematically investigated these parameters to maximize the EA extraction efficiency. The extraction yields for EA obtained under the predicted optimal conditions validated the efficacy of both the RSM and ANN models. Analysis using the ANN-predicted data showed a higher coefficient of determination () value of 0.9970 and a relative error of 0.79, compared to the RSM's 2.85. The optimal conditions using the ANN are an ethanol concentration of 61.00%, an extraction temperature of 77 °C, a liquid-solid ratio of 26 mL g and an extraction time of 103 min. These findings significantly enhance our understanding of the industrial-scale optimization process for EA extraction from CF.
诃子是一种常见的中药，从植物中分离得到的鞣花酸（EA）是一种具有重要药用价值的生物活性成分。本研究旨在确定从诃子中提取 EA 含量的最佳提取参数，重点研究乙醇浓度、提取温度、液固比和提取时间等变量。利用响应面法（RSM）和人工神经网络（ANN）相结合的方法，系统地研究了这些参数，以最大限度地提高 EA 的提取效率。在预测的最佳条件下，EA 的提取产率验证了 RSM 和 ANN 模型的有效性。使用 ANN 预测数据进行分析，结果显示，决定系数（）值为 0.9970，相对误差为 0.79，而 RSM 的 为 2.85。使用 ANN 的最佳条件为乙醇浓度 61.00%、提取温度 77°C、液固比 26 mL/g 和提取时间 103 min。这些发现显著提高了我们对 CF 中 EA 提取的工业规模优化过程的理解。
