مطالعه تجربي و بهينه سازي فرآيند استخراج فوق بحراني گالگين از گياه گالگا آفيسيناليس به روش طراحي آزمايشات و مدل سازي رياضي

چكيده انگليسي :

Experimental Investigation and Optimization of Supercritical Extraction of Galegine from Galega officinalis L Using Design of Experiments and Mathematical Modeling Pooya Davoodi p davoodi@ce iut ac ir April 5 2011 Department of Chemical Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Seyyed M Ghoreishi Assoc Prof Email ghoreshi@cc iut ac ir Ali A Dadkhah Assist Prof Email dadkhah@cc iut ac ir Abstract The use of plants as therapeutic tools especially those used to relieve chronic pathologies have had a remarkable role in the popular medicine of different countries Galega officinalis L commonly called Gout s Rue is a member of legume family Fabaceae It is native to southern Europe and Western Asia Historically it has been a popular garden plant in both Europe and the United States partly because of its religious and medicinal associations G officinalis L grows along stream banks and in moist areas It prefers full sun but will tolerate light shade An active principle galegine was first isolated from this plant by Tanret and recognized as a guanidine derivate 3 methylbut 2 en ethyl guanidine by Sp th and Perkop The preliminary studies claim galegine can increase milk production in sheep Additionally there are some more studies in which the effect of water extraction of G officinalis L on human platelet aggregation in vitro and body weight were examined As an alternative technique in pharmaceutical processing in contrast to chemical reaction the supercritical fluid extraction of galegine from G officinalis L was investigated in this study In comparison to conventional liquid solvent extraction the quality of extracted components by supercritical fluids is more suitable and preferable for pharmaceutical industry Thus for separation of essential oil from G officinalis L supercritical CO2 extraction was carried out on a laboratory scale under the following operating conditions 40 50 C 15 25 Mpa 1 2 ml min CO2 flow rate 60 120 min extraction dynamic time The constant static time of 20 min was applied for all extraction runs Liquid chromatography mass spectrometry LC MS was applied to identify and quantify galegine in each extracted sample In order to obtain maximum galegine yield as the objective function of this research the effective extraction parameters were optimized using statistical techniques response surface methodology and analysis of variance Response surface methodology RSM defined as the statistical method that uses quantitative data from an appropriate experimental design to determine and simultaneously solve multivariate equations is an effective and powerful statistical method for optimizing experimental conditions and investigation of critical processes while reducing the number of experimental trials Most RSM applications come from areas such as chemical or engineering processes industrial research and biological investigations The optimum conditions were found to be the extraction dynamic time of 150 min 23 Mpa 42 3 C and 1 15 ml min to achieve galegine yield of 3 398 mg g Response surface analysis showed that the data were adequately fitted to second order polynomial model and The statistical analysis also showed that the linear terms of pressure temperature and extraction dynamic time the quadratic terms of pressure extraction dynamic time and CO2 flow rate as well as the interactions of pressure and temperature and temperature and flow rate have considerable effects on the yield A general mathematical model for supercritical CO2 extraction was developed Its results showed that extraction vessel had some non ideality due to channeling across the vessel and dead zone in some part of it that decrease the yield Keywords Galega Officinalis L Galegine Supercritical CO2 extraction Response surface methodology Optimization mathematical modeling

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مطالعه تجربي و بهينه سازي فرآيند استخراج فوق بحراني گالگين از گياه گالگا آفيسيناليس به روش طراحي آزمايشات و مدل سازي رياضي

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