文献类型：期刊文献

中文题名：神经网络优化番木瓜籽油的超临界CO_2萃取工艺

英文题名：Optimization of Extraction Process of Papaya Seed Oil by Supercritical Carbon Dioxide Based on Neural Network

作者：邓楚津[1];董强[2];张常松[1];张良[1];刘书成[1]

机构：[1]广东海洋大学食品科技学院,湛江524088;[2]西安市产品质量监督检验院,西安710006

年份：2012

卷号：27

期号：2

起止页码：47

中文期刊名：中国粮油学报

外文期刊名：Journal of the Chinese Cereals and Oils Association

收录：CSTPCD、、北大核心2011、Scopus、CSCD2011_2012、北大核心、CSCD

基金：广东海洋大学自然科学基金(0812093)

语种：中文

中文关键词：超临界CO2萃取;神经网络;番木瓜籽油;理化性质

外文关键词：supercritical CO2 extraction; neural network; papaya seed oil; physical and chemical properties

中文摘要：采用超临界CO2萃取法萃取番木瓜籽油,利用JMP 7.0软件中的神经网络平台,建立超临界CO2萃取番木瓜籽油的神经网络模型,并优化了萃取过程的工艺参数。结果表明:番木瓜籽破碎后过20目筛,CO2流量为25 L/h,萃取压力27 MPa,萃取温度54℃,萃取时间3 h,油脂得率达30%以上;超临界CO2萃取的番木瓜籽油的理化性质达到了食用油脂的标准。

外文摘要：Papaya seed oil was extracted by supercritical CO2.A neural network model of supercritical CO2 extracting papaya seed oil was established to optimize extracting process parameters in JMP 7.0 software.The parameters were that grinded papaya seeds were screened through a 20-inch boult,flow of CO2 was 25 L/h,extraction pressure was 27 Mpa,extraction temperature was 54 ℃,and extraction time was 3 h.Under these conditions,the extraction rate was above 30%.Papaya seed oil extracted by supercritical CO2 can meet the standard of edible oils and fats.