Science & Technology Review
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2016, 34(2): 46-52
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Optimization of the extraction conditions of Elaeagnus mollis kernel oil by response surface methodology
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ZHU Yahong, WANG Junqi, SU Yinquan, HUANG Xiaohua, ZHU Mingqiang
Affiliations
College of Forestry, Northwest A&F University, Yangling 712100, China
Published: 2016-01-28
doi: 10.3981/j.issn.1000-7857.2016.2.006
Outline
In this paper, an experimental method of the central composite design is used to determine the kernel oil content in the Elaeagnus mollis preparation. Based on the Design Expert software, a quadratic model is established with independent variables of the kernel oil content, such as the extraction time, the extraction temperature and the material-liquid ratio. The response values satisfying all expectations are optimized, and the most excellent extraction conditions of the Elaeagnus mollis kernel oil are 45 min for the extraction time, 88℃, for the extraction temperature and 1:5 for the material-liquid ratio. Under these conditions, the actual extraction rate of the kernel oil is 92.44%. The result of the verification experiment for the formulation is consistent with the prediction. The fatty acids in the Elaeagnus mollis kernel oil are analyzed by GC-MS. The results show that 28 kinds of fatty acids and 9 kinds of unsaturated fatty acids are identified. They are mainly composed of 12.86% methyl oleic, 10% methyl palmitate, pentadecanoic, 9.78% acid methyl ester, and 16.57% linoleic acid methyl. This extraction method is an environmentally benign and advantageous scheme for the production of kernel oil from Elaeagnus mollis, which will be further transformed into the value-added biomaterials and bioethanol.
Elaeagnus mollis
/
kernel oil
/
central composite design
/
response surface methodology
朱亚红, 王俊淇, 苏印泉, 黄晓华, 朱铭强.
响应面法优化提取翅果油树种仁油的工艺条件.
科技导报,
2016
, 34
(2)
: 46
-52
.
DOI: 10.3981/j.issn.1000-7857.2016.2.006
ZHU Yahong, WANG Junqi, SU Yinquan, HUANG Xiaohua, ZHU Mingqiang.
Optimization of the extraction conditions of Elaeagnus mollis kernel oil by response surface methodology[J].
Science & Technology Review,
2016
, 34
(2)
: 46
-52
.
DOI: 10.3981/j.issn.1000-7857.2016.2.006
Year 2016 volume 34 Issue 2
PDF
445
68
Cite this Article
BibTeX
Article Info
doi: 10.3981/j.issn.1000-7857.2016.2.006
- Receive Date:2015-07-10
- Online Date:2016-02-04
- Published:2016-01-28