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[Optimization for supercritical CO2 extraction with response surface methodology of Prunus armeniaca oil]
Fei-Fei Chen1, Yan Wu, Fa-Huan Ge
1Sun Yat-Sen University, Guangzhou 510275, China.
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.
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01:28Methods of Medium Optimization
01:16Response Surface Methodology
The process of RSM involves several key steps: