Optimization of enzyme-assisted improvement of polyphenols and free radical scavenging activity in red rice bran: A statistical and neural network-based approach

Ashish A. Prabhu, A. Jayadeep
{"title":"Optimization of enzyme-assisted improvement of polyphenols and free radical scavenging activity in red rice bran: A statistical and neural network-based approach","authors":"Ashish A. Prabhu, A. Jayadeep","doi":"10.1080/10826068.2016.1252926","DOIUrl":null,"url":null,"abstract":"ABSTRACT The current study is focused on optimizing the parameters involved in enzymatic processing of red rice bran for maximizing total polyphenol (TP) and free radical scavenging activity (FRSA). The sequential optimization strategies using central composite design (CCD) and artificial neural network (ANN) modeling linked with genetic algorithm (GA) was performed to study the effect of incubation time (60–90 min), xylanase concentration (5–10 mg/g), cellulase concentration (5–10 mg/g) on the response, i.e., total polyphenol and FRSA. The result showed that incubation time has a negative effect on the response, while the square effect of xylanase and cellulase showed positive effect on the response. A maximum TP of 2,761 mg ferulic acid Eq/100 g bran and FRSA of 778.4 mg Catechin Eq/100 g bran was achieved with incubation time (min) = 60.491; xylanase (mg/g) = 5.4633; cellulase (mg/g) = 11.5825. Furthermore, ANN-GA-based optimization showed better predicting capabilities as compared to CCD.","PeriodicalId":20393,"journal":{"name":"Preparative Biochemistry and Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Preparative Biochemistry and Biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10826068.2016.1252926","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24

Abstract

ABSTRACT The current study is focused on optimizing the parameters involved in enzymatic processing of red rice bran for maximizing total polyphenol (TP) and free radical scavenging activity (FRSA). The sequential optimization strategies using central composite design (CCD) and artificial neural network (ANN) modeling linked with genetic algorithm (GA) was performed to study the effect of incubation time (60–90 min), xylanase concentration (5–10 mg/g), cellulase concentration (5–10 mg/g) on the response, i.e., total polyphenol and FRSA. The result showed that incubation time has a negative effect on the response, while the square effect of xylanase and cellulase showed positive effect on the response. A maximum TP of 2,761 mg ferulic acid Eq/100 g bran and FRSA of 778.4 mg Catechin Eq/100 g bran was achieved with incubation time (min) = 60.491; xylanase (mg/g) = 5.4633; cellulase (mg/g) = 11.5825. Furthermore, ANN-GA-based optimization showed better predicting capabilities as compared to CCD.
酶辅助改善红米糠中多酚和自由基清除活性的优化:基于统计和神经网络的方法
摘要:本研究旨在优化红米糠酶处理工艺参数,以最大限度地提高总多酚(TP)和自由基清除活性(FRSA)。采用中心复合设计(CCD)和人工神经网络(ANN)建模与遗传算法(GA)相结合的序列优化策略,研究了培养时间(60 ~ 90 min)、木聚糖酶浓度(5 ~ 10 mg/g)、纤维素酶浓度(5 ~ 10 mg/g)对总多酚和FRSA的影响。结果表明,培养时间对反应有负影响,而木聚糖酶和纤维素酶的平方效应对反应有正影响。孵育时间(min) = 60.491时,最高总磷为2761 mg阿魏酸Eq/100 g麸皮,最高总磷为778.4 mg儿茶素Eq/100 g麸皮;木聚糖酶(mg/g) = 5.4633;纤维素酶(mg/g) = 11.5825。此外,与CCD相比,基于ann - ga的优化具有更好的预测能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信