萃取(化学)
人工神经网络
超声波传感器
制浆造纸工业
材料科学
色谱法
工艺工程
计算机科学
声学
化学
人工智能
工程类
物理
作者
Xiajing Xu,Shumeng Ren,Dongmei Wang,Jun Ma,Xiaowei Yan,Yongli Guo,Xiaoqiu Liu,Yingni Pan
标识
DOI:10.6084/m9.figshare.14268415
摘要
Abstract In order to obtain the extraction process of defatted walnut powder (DWP), an ultrasound-assisted extraction based on artificial neural network was established, and the activity of the extract was evaluated. The artificial neural network (ANN) was used to model different parameters, including the yield of extraction, the concentrations of glansreginin A and ellagic acid, and obtained the optimal extraction process: solvent to material ratio of 9.5 mL/g, ethanol concentration of 68%, extraction period of 55 min, and extraction three times. Then, the antioxidant scavenging ability of DWP obtained by ANN was compared with other extraction methods. The results showed that DWP extracted by artificial neural network demonstrated good activity in scavenging DPPH and ABTS radicals.
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