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响应面优化泡沫法提取紫苏饼粕蛋白的工艺

吴存兵 张钰涓 邵伯进 陶维春 吴君艳 姜娟 浦静

安徽农业大学学报2017,Vol.44Issue(4):574-579,6.
安徽农业大学学报2017,Vol.44Issue(4):574-579,6.DOI:10.13610/j.cnki.1672-352x.20170811.032

响应面优化泡沫法提取紫苏饼粕蛋白的工艺

Optimization of foam separation of protein from perilla seed meal using the response surface method

吴存兵 1张钰涓 1邵伯进 1陶维春 2吴君艳 3姜娟 1浦静1

作者信息

  • 1. 江苏财经职业技术学院粮食工程与食品药品学院,淮安223003
  • 2. 淮安市粮油质量监测所,淮安223001
  • 3. 江苏食品药品职业技术学院,淮安223001
  • 折叠

摘要

Abstract

To optimize protein extraction technology of protein from perilla,the effects of temperature,liquid-solid ratio and time on the extraction rate of perilla protein were investigated.The optimum protein extraction technology from perilla meal was developed through the response surface method.A quadratic regression model for the extraction rate of perilla protein on temperature,liquid-solid ratio and time was set up as Y=13.21-2.21A-0.21B-1.38C-0.15AB-2.43AC-1.78BC-3.37A2-4.43B2-1.99C2 (R2=0.9544) with a good fitting degree.Soaking temperature and time had extremely significant (P<0.01,the same below) and significant (P<0.05) effects on the extraction rate.The interaction between temperature and time and 1 iquid-solid ratio and time also had extremely significant and significant effects on the extraction rate.The optimum conditions for the protein extraction from perilla seed meal were:temperature,53 ℃;liquid-solid ratio,10:1 mL·g-1;soaking time,114 min.Under this condition,the practical extraction rate of perilla protein was 13.91%.Compared with the predictive value,the relative error was about 2.10%.The technology model for extracting protein from perilla seed meal was fit well with the measured value.The results showed that the response surface method for extracting perilla protein is effective.

关键词

响应面分析/紫苏饼粕/泡沫法/提取

Key words

response surface method/perilla seed meal/foam fractionation/extraction technology

分类

轻工纺织

引用本文复制引用

吴存兵,张钰涓,邵伯进,陶维春,吴君艳,姜娟,浦静..响应面优化泡沫法提取紫苏饼粕蛋白的工艺[J].安徽农业大学学报,2017,44(4):574-579,6.

基金项目

江苏高校“青蓝工程”,泡沫分离紫苏蛋白及功能性研究(SN12046),江苏省饲料(食品)营养分析与质量安全检测公共服务平台(HAP201429),江苏省科技厅项目江苏省淮安饲料安全公共技术服务中心(BM2009831)共同资助. (SN12046)

安徽农业大学学报

OACSCDCSTPCD

1672-352X

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