[基于响应面法优化超临界CO₂萃取山杏油的研究]
[Optimization for supercritical CO2 extraction with response surface methodology of Prunus armeniaca oil].
作者信息
Chen Fei-Fei, Wu Yan, Ge Fa-Huan
机构信息
Sun Yat-Sen University, Guangzhou 510275, China.
出版信息
Zhong Yao Cai. 2012 Mar;35(3):479-82.
OBJECTIVE
To optimize the extraction conditions of Prunus armeniaca oil by Supercritical CO2 extraction and identify its components by GC-MS.
METHODS
Optimized of SFE-CO extraction by response surface methodology and used GC-MS to analysis Prunus armeniaca oil compounds.
RESULTS
Established the model of an equation for the extraction rate of Prunus armeniaca oil by supercritical CO2 extraction, and the optimal parameters for the supercritical CO2 extraction determined by the equation were: the extraction pressure was 27 MPa, temperature was 39 degrees C, the extraction rate of Prunus armeniaca oil was 44.5%. 16 main compounds of Prunus armeniaca oil extracted by supercritical CO2 were identified by GC-MS, unsaturated fatty acids were 92.6%.
CONCLUSION
This process is simple, and can be used for the extraction of Prunus armeniaca oil.
目的
优化超临界CO₂萃取苦杏仁油的工艺条件，并采用气相色谱-质谱联用（GC-MS）法对其成分进行鉴定。
方法
采用响应面法优化超临界CO₂萃取（SFE-CO₂）工艺，并运用GC-MS分析苦杏仁油的化合物组成。
结果
建立了超临界CO₂萃取苦杏仁油得率的方程模型，由该方程确定的超临界CO₂萃取最佳参数为：萃取压力27MPa，温度39℃，苦杏仁油得率为44.5%。通过GC-MS鉴定出超临界CO₂萃取的苦杏仁油中的16种主要化合物，其中不饱和脂肪酸占92.6%。
结论
该工艺简单，可用于苦杏仁油的提取。
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