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作 者:金旭东 王俊淇 曹朝清 王碧 丁浩淼[1] 汪财生[1] 钱国英[1] JIN Xudong;WANG Junqi;CAO Chaoqing;WANG Bi;DING Haomiao;WANG Caisheng;QIAN Guoying(College of Biological and Environmental Sciences,Zhejiang Wanli University,Ningbo 315100,China)
机构地区:[1]浙江万里学院生物与环境学院,浙江宁波315100
出 处:《食品工业科技》2021年第17期170-178,共9页Science and Technology of Food Industry
基 金:宁波市“十三五”海洋经济创新发展示范项目资助(NBHY-2017-S5,NBHY-2017);浙江省“生物工程”一流学科(A类)学生创新计划项目(CX2019009)。
摘 要:为探索循环超声提取冰鲜羊栖菜中岩藻黄质生产工艺。实验以羊栖菜中岩藻黄质提取量为指标,在单因素实验基础上,采用响应曲面模型与遗传算法优化的BP神经网络模型进行拟合优选提取参数。结果表明:响应曲面模型优选最佳提取工艺为提取时间119 min,超声功率600 W,液料比26.5:1 L/kg,循环流速8.6 L/min,此条件下实际岩藻黄质提取量为0.2195 g/kg,产品纯度3.42%;神经网络模型筛选最优提取工艺为提取时间118 min,超声功率680 W,液料比23.5:1 L/kg,循环流速7.0 L/min,此条件下实际岩藻黄质提取量为0.2318 g/kg,产品纯度3.41%。采用神经网络优选提取工艺条件可行且略优于响应曲面法,在规模化藻类提取岩藻黄质中具有一定的参考价值。The purpose of this study was to explore the extraction process of fucoxanthin from frozen Hizikia fusiforme by cyclic ultrasound.Based on single factor test,the response surface model and BP neural network model optimized by genetic algorithm were used to optimize the extraction parameters on the basis of single factor experiment.The results showed that the optimal extraction conditions,obtained by response surface model,were as follows:Extraction time 119 min,ultrasonic power 600 W,liquid-solid ratio 26.5:1 L/kg,circulating flow rate 8.6 L/min.Under these conditions,the actual extraction rate of fucoxanthin was 0.2195 g/kg,and the purity of the product was 3.42%.The optimal extraction conditions,obtained by BP neural network model,were as follows:Extraction time 118 min,ultrasonic power 680 W,liquid-solid ratio 23.5:1 L/kg,circulating flow rate 7.0 L/min.Under these conditions,the actual extraction rate of fucoxanthin was 0.2318 g/kg,and the purity of the product was 3.41%.The neural network model is feasible and slightly better than the response surface modelconcerning the extraction conditions,which has a certain reference value in large-scale algae extraction of fucoidin.
关 键 词:羊栖菜 岩藻黄质 循环超声 响应曲面 BP神经网络
分 类 号:TS201.2[轻工技术与工程—食品科学]
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