[1]刘显明,顾焰波,陈冬年,等.蜗牛酶辅助提取石榴皮原花青素的响应面优化[J].中国调味品,2018,(7):1-5.[doi:10.3969/j.issn.1000-9973.2018.07.001]
　LIU Xian-ming,GU Yan-bo,CHEN Dong-nian,et al.Optimization of Snailase-Assisted Extraction Procyanidins from Pomegranate Peels by Response Surface Methodology[J].CHINA CONDIMENT,2018,(7):1-5.[doi:10.3969/j.issn.1000-9973.2018.07.001]
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蜗牛酶辅助提取石榴皮原花青素的响应面优化(/HTML)
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《中国调味品》[ISSN:1000-9973/CN:23-1299/TS]

卷:
期数:
2018年7期
页码:
1-5
栏目:
出版日期:
2018-07-01

文章信息/Info

Title:
Optimization of Snailase-Assisted Extraction Procyanidins from Pomegranate Peels by Response Surface Methodology
文章编号:
1000-9973(2018)07-0001-05
作者:
刘显明; 顾焰波; 陈冬年; 王翼; 王华
南京理工大学泰州科技学院 环境与制药工程学院
Author(s):
LIU Xian-ming; GU Yan-bo; CHEN Dong-nian; WANG Yi; WANG Hua
( of Environmental and Pharmaceutical Engineering,Taizhou Institute of Science and Technology, Nanjing University of Science and Technology,Taizhou 225300,China)
关键词:
石榴皮; 原花青素; 蜗牛酶; 响应曲面法
Keywords:
pomegranate peels;  procyanidins;  snailase;  response surface methodology
分类号:
TS201.25
DOI:
10.3969/j.issn.1000-9973.2018.07.001
文献标志码:
A
摘要:
采用蜗牛酶对石榴皮中原花青素进行提取，以提取温度、提取时间、pH值、酶用量为单因素试验考察变量、原花青素得率为响应值，采用Box-Behnken Design试验设计方法，对石榴皮中原花青素提取条件进行优化，建立石榴皮原花青素提取得率的二次回归方程，得到最优提取条件。结果表明，原花青素的响应面优化工艺条件为：提取时间90 min、提取温度50 ℃、pH 5.0、蜗牛酶用量1.0%，在此条件下，原花青素得率为 0.658%。
Abstract:
The procyanidins of pomegranate peels is extracted by the way of snailase-assisted. On the basis of four single factor tests, response surface analysis methodology (BBD) is used to optimize the extraction yields of procyanidins, including extraction temperature, extraction time, enzyme concentration and pH and yield of procyanidins is taken as response value.A quadric regression equation of PC are established. The results show that the appropriate technical optimal conditions are as follows: extraction time is 90 min, extraction temperature is 50 °C, pH is 5.0, snailase dosage is 1.0%, under these conditions, the proanthocyanidin yield is 0.658%

参考文献/References:

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备注/Memo

备注/Memo:
修改1 2018年01月29日 重复率：12.9% 栏目：基础研究 基金项目：南京理工大学泰州科技学院“校级优秀课程”项目（YK2015B08）基金项目：南京理工大学泰州科技学院“校级优秀课程”项目（YK2015B08）
更新日期/Last Update: 2018-08-08