文章基本信息

标题：Optimization of extraction of defatted walnut powder by ultrasonic assisted and artificical neural network
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作者：XU Xiajing ; REN Shumeng ; WANG Dongmei 等
期刊名称：Food Science and Technology (Campinas)
印刷版ISSN：0101-2061
电子版ISSN：1678-457X
出版年度：2022
卷号：42
DOI：10.1590/fst.53320
语种：English
出版社：Sociedade Brasileira de Ciência e Tecnologia de Alimentos
摘要：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.
关键词：ultrasound;assisted extraction;defatted walnut powder;artificial neural network;antioxidant activity