食品工业科技Issue(11)：301-304,4.
基于神经网络法制备牡蛎呈味肽工艺优化研究
Study on the processing optimization of taste peptide enzymatic-production from oyster base on a neural network method
摘要
Abstract
In order to obtain oyster hydrolysis product with good flavor and rich in peptide,enzymatic process optimization was investigated by using flesh oyster as material based on a neutral network method,which built by some parameters obtained from orthogonal experiments（enzymatic time,enzymatic temperature,enzyme concentration,ratio of material to water,peptide concentration and sensory score）.The optimized operation condition obtained by the neutral network method was：enzymatic time 5.4h,enzymatic temperature 58.6℃,enzyme concentration 1.03%,ratio of oyster muscle to water 1∶ 2.8,and its predictive peptide ratio reached to 80.81%,while the result of its confirmatory experiment was 78.35%.The another optimized operation condition was：enzymatic time 6.0h,enzymatic temperature 53.8℃,enzyme concentration 0.95%,ratio of oyster muscle to water 1∶ 2.1,and its predict sensory scores was 6.67,while the result of its confirmatory experiment was 6.39.The relative errors between predict value and confirmatory experiment were all less than 5%,indicated that the neutral network method was an effective tool for optimizing enzymatic process condition for oyster to obtain desired target value.关键词
牡蛎/呈味肽/BP神经网络/遗传算法Key words
oyster/taste peptide/BP neural network/genetic algorithm分类
轻工纺织引用本文复制引用
侯清娥,秦小明,林华娟,章超桦,刘慧,尤久勇..基于神经网络法制备牡蛎呈味肽工艺优化研究[J].食品工业科技,2011,(11):301-304,4.基金项目
农业部948项目 （）
现代农业产业技术体系建设专项 （）
