Available online at www.sciencedirect.com Journal of Integrative Agriculture 2012,11(1):151-158 ScienceDirect January 2012 RESEARCH ARTICLE Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction ZHANG Jun-ping.2,HOU Xi-lin1.2,YU Tian',LI Ying1.2 and DONG Hai-yan.2 i State Key Laboratory of Crop Genetics Germplasm Enhancement,Nanjing Agriculture University,Nanjing 210095,P.R.China Key Laboratory of Southern Vegetable Crop Genetic Improvement,Ministry of Agriculture,Nanjing 210095,P.R.China Abstract Supercritical carbon dioxide (SC-CO2)extraction was employed to extract oil from Nigella glandulifera Freyn seed in this study.Response surface methodology(RSM)was applied to evaluate the effects of the process parameters(pressure, temperature,and CO,flow rate)on oil yield of N.glandulifera seed.A Box-Behnken design was used to optimize the extraction parameters.The analysis of variance indicated that the linear coefficients of pressure and CO,flow rate,the quadratic term coefficients of pressure and temperature and the interactions between pressure and temperature,as well as temperature and CO,flow rate,had significant effects on the oil yield(P<0.05).The optimal conditions to obtain the maximum oil yield from N.glandulifera seed were pressure 30.84 MPa,temperature 40.57C,and CO,flow rate 22.00 L h-1. Under these optimal conditions,the yield of oil was predicted to be 38.19%.The validation experiment results agreed with the predicted values.The fatty acid composition of N.glandulifera seed oil extracted using SC-CO2 was compared with that of oil obtained by Soxhlet method.The results showed that the fatty acid compositions of oil extracted by the two methods were similar.Identification of oil compounds with gas chromatography-mass spectrometry(GC-MS)showed that the contents of unsaturated fatty acids linoleic acid(48.30%),oleic acid(22.28%)and saturated fatty acids palmitic acid (16.65%).stearic acid (4.17%)were the most abundant fatty acids in seed oil from N.glandulifera Key words:supercritical carbon dioxide extraction,Nigella glandulifera Freyn seed oil,response surface methodology gas chromatography-mass spectrometry,fatty acids asthma (Xiao et al.2002).They contain about 35- INTRODUCTION 42%oil.which is rich in linoic acid and oleic acid. Linoic acid and oleic acid are unsaturated fatty acids, Nigella glandulifera Freyn,a plant of Nigella genus in and are considered to be beneficial to the health of Ranunculaceae family,is widely distributed in Xinjiang, mankind,so its oil has high value for exploitation and Yunnan,and Tibet of China.The seeds of N.glandulifera utilization and can be used in foods,pharmaceuticals, are well-known as a Uighur's traditional medicine and and cosmetic formulations and so on. food,which are included in Pharmacopoeia of the Oil extraction using supercritical carbon dioxide(SC- People's Republic of China from 1997 to now.These CO,)has gained increasing attention over the traditional seeds are believed to have diuretic,analgesic, techniques,like steam distillation and solvent extraction spasmolytic,galactagogue,and bronchodilator func- SC-CO,has the advantages of using nontoxic,nonex- tions to cure edema,urinary calculus,and bronchial plosive and volatile solvent,which protects extracts from Received 28 October,2010 Accepted 4 July,2011 ZHANG Jun-ping,E-mail:xj2005zhangip@126.com;Correspondence HOU Xi-lin,Tel:+86-25-84395917,E-mail:hxl@njau.edu.cn 2012,CAAS.All rights reserved.Published by ElsevierLtd
Journal of Integrative Agriculture 2012, 11(1): 151-158 January 2012 © 2012, CAAS. All rights reserved. Published by Elsevier Ltd. RESEARCH ARTICLE Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction ZHANG Jun-ping1, 2, HOU Xi-lin1, 2, YU Tian1, LI Ying1, 2 and DONG Hai-yan1, 2 1 State Key Laboratory of Crop Genetics & Germplasm Enhancement, Nanjing Agriculture University, Nanjing 210095, P.R.China 2 Key Laboratory of Southern Vegetable Crop Genetic Improvement, Ministry of Agriculture, Nanjing 210095, P.R.China Abstract Supercritical carbon dioxide (SC-CO2) extraction was employed to extract oil from Nigella glandulifera Freyn seed in this study. Response surface methodology (RSM) was applied to evaluate the effects of the process parameters (pressure, temperature, and CO2 flow rate) on oil yield of N. glandulifera seed. A Box-Behnken design was used to optimize the extraction parameters. The analysis of variance indicated that the linear coefficients of pressure and CO2 flow rate, the quadratic term coefficients of pressure and temperature and the interactions between pressure and temperature, as well as temperature and CO2 flow rate, had significant effects on the oil yield (P<0.05). The optimal conditions to obtain the maximum oil yield from N. glandulifera seed were pressure 30.84 MPa, temperature 40.57°C, and CO2 flow rate 22.00 L h-1. Under these optimal conditions, the yield of oil was predicted to be 38.19%. The validation experiment results agreed with the predicted values. The fatty acid composition of N. glandulifera seed oil extracted using SC-CO2 was compared with that of oil obtained by Soxhlet method. The results showed that the fatty acid compositions of oil extracted by the two methods were similar. Identification of oil compounds with gas chromatography-mass spectrometry (GC-MS) showed that the contents of unsaturated fatty acids linoleic acid (48.30%), oleic acid (22.28%) and saturated fatty acids palmitic acid (16.65%), stearic acid (4.17%) were the most abundant fatty acids in seed oil from N. glandulifera. Key words: supercritical carbon dioxide extraction, Nigella glandulifera Freyn seed oil, response surface methodology, gas chromatography-mass spectrometry, fatty acids INTRODUCTION Nigella glandulifera Freyn, a plant of Nigella genus in Ranunculaceae family, is widely distributed in Xinjiang, Yunnan, and Tibet of China. The seeds of N. glandulifera are well-known as a Uighur’s traditional medicine and food, which are included in Pharmacopoeia of the People’s Republic of China from 1997 to now. These seeds are believed to have diuretic, analgesic, spasmolytic, galactagogue, and bronchodilator functions to cure edema, urinary calculus, and bronchial asthma (Xiao et al. 2002). They contain about 35- 42% oil, which is rich in linoic acid and oleic acid. Linoic acid and oleic acid are unsaturated fatty acids, and are considered to be beneficial to the health of mankind, so its oil has high value for exploitation and utilization and can be used in foods, pharmaceuticals, and cosmetic formulations and so on. Oil extraction using supercritical carbon dioxide (SCCO2 ) has gained increasing attention over the traditional techniques, like steam distillation and solvent extraction. SC-CO2 has the advantages of using nontoxic, nonexplosive and volatile solvent, which protects extracts from Received 28 October, 2010 Accepted 4 July, 2011 ZHANG Jun-ping, E-mail: xj2005zhangjp@126.com; Correspondence HOU Xi-lin, Tel: +86-25-84395917, E-mail: hxl@njau.edu.cn
152 ZHANG Jun-ping et al. thermal degradation and solvent contamination(Brunner The regression analysis of the response function with 1994).There are reports on SC-CO,extraction as an statistical analysis are given in Table 2.Statistical test- excellent alternative to the use of chemical solvents in ing of the model was performed in the form of ANOVA the extraction of oils from different plants such as corn Here,the value for Fand P(probability)(P0.05). 2007),cocoa beans(Saldafia et al.2002),green tea indicating that the generated model adequately explained (Chang et al.2000),and ginseng (Wang et al.2001). the data variation and significantly represented the ac- However,no studies have been reported on the oil ex- tual relationship between the reaction parameters.The traction from N.glandulifera seed by SC-CO.extrac- determination coefficient R2=0.9904 indicating that tion to our knowledge.Response surface methodol- 99.04%of the variability in the response could be ex- ogy(RSM)which combines mathematics with statis- plained by the model.From the P-values of each model tics is often used to design experiments,build models, term,we concluded that the linear coefficients of pres- and evaluate the effects of factors (Yue et al.2008). sure and CO.flow rate and the quadratic terms of pres- The main advantage of RSM is the small number of sure and temperature,had highly significant effects on experimental trials needed to evaluate multiple param- the oil yield at the 1%level(P<0.01).The interactions eters and their interactions(Chow et al.1998),and it between pressure and temperature,as well as tempera- has been used successfully in food processing opera- ture and CO,flow rate,had significant effects on the tions(Hierro and Santa-Maria 1992;Reverchon 1997; oil yield at the 5%level (P<0.05). Lee et al.2000;Huang et al.2008;Liu et al.2009). SC-CO,was used to extract seed oil from N.glanelulifera Response surface analysis in this work.The effects of independent factors (pressure,temperature,and CO,flow rate)on the oil From Eq.(1)we can see that the oil yield of N.glandulifera yield of N.glandulifera seed were investigated.RSM seed has a complex relationship with independent was employed to build a model between the oil yield variables.The best way of expressing the effects of and these independent factors as well as to develop a independent variables on the oil yield within the experi- model equation that will predict and determine the opti- mental space under investigation is to generate response mum conditions for the oil yield surface plots of the equation.The three-dimensional response surfaces curves and corresponding contour RESULTS AND DISCUSSION plots were obtained using the Design Expert and are shown in Figs.1,2,and 3 to illustrate the relationship between independent variables and the oil yield. Model fitting Fig.I shows response surface curve and its con- tour plot for the effects of pressure and temperature on Oil yields obtained from all the experiments are listed in the oil yield and their interaction at a fixed flow rate of Table 1.The experimental data were used to calculate 20 L h.The extraction pressure and temperature the coefficients of the second-order polynomial equation. showed a quadratic effect on the response.At low The application of RSM offered,based on parameter pressure,the oil yield was increased with the increase estimates,an empirical relationship between the response of pressure.This is most likely due to the improve- variable,and the test variables under consideration.By ment of oil solubility resulted from the increased CO, applying multiple regression analysis on the experimen- density with the rise of pressure(Lee et al.2000).When tal data,the response variable and the test variables were the pressure was increased to levels greater than ap- related by the following second-order polynomial proximately 30 MPa,the negative quadratic effect be- equation: gan to have an impact.Such effect of pressure is not Y=36.81+0.78x-0.014x,+1.27x,+0.41xx2-0.099xx3 unexpected,when the pressure becomes too high,a +0.32x-2.16x2-1.64x2+0.031x2 (1) reduction in the solvent diffusivity and mass transfer 2012,CAAS.All rights reserved.Published by Elsevier Ltd
152 ZHANG Jun-ping et al. © 2012, CAAS. All rights reserved. Published by Elsevier Ltd. thermal degradation and solvent contamination (Brunner 1994). There are reports on SC-CO2 extraction as an excellent alternative to the use of chemical solvents in the extraction of oils from different plants such as corn (List et al. 1984), soybean (Friedrich et al. 1982) and cotton seeds (Kuk and Hron 1994; Bhattacharjee et al. 2007), cocoa beans (Saldaña et al. 2002), green tea (Chang et al. 2000), and ginseng (Wang et al. 2001). However, no studies have been reported on the oil extraction from N. glandulifera seed by SC-CO2 extraction to our knowledge. Response surface methodology (RSM) which combines mathematics with statistics is often used to design experiments, build models, and evaluate the effects of factors (Yue et al. 2008). The main advantage of RSM is the small number of experimental trials needed to evaluate multiple parameters and their interactions (Chow et al. 1998), and it has been used successfully in food processing operations (Hierro and Santa-Maria 1992; Reverchon 1997; Lee et al. 2000; Huang et al. 2008; Liu et al. 2009). SC-CO2 was used to extract seed oil from N. glanelulifera in this work. The effects of independent factors (pressure, temperature, and CO2 flow rate) on the oil yield of N. glandulifera seed were investigated. RSM was employed to build a model between the oil yield and these independent factors as well as to develop a model equation that will predict and determine the optimum conditions for the oil yield. RESULTS AND DISCUSSION Model fitting Oil yields obtained from all the experiments are listed in Table 1. The experimental data were used to calculate the coefficients of the second-order polynomial equation. The application of RSM offered, based on parameter estimates, an empirical relationship between the response variable, and the test variables under consideration. By applying multiple regression analysis on the experimental data, the response variable and the test variables were related by the following second-order polynomial equation: Y=36.81+0.78x1 -0.014x2 +1.27x3 +0.41x1 x2 -0.099x1 x3 . +0.32x2 x3 -2.16x1 2 -1.64x2 2 +0.031x3 2 (1) The regression analysis of the response function with statistical analysis are given in Table 2. Statistical testing of the model was performed in the form of ANOVA. Here, the value for F and P (probability) (P0.05), indicating that the generated model adequately explained the data variation and significantly represented the actual relationship between the reaction parameters. The determination coefficient R2 =0.9904 indicating that 99.04% of the variability in the response could be explained by the model. From the P-values of each model term, we concluded that the linear coefficients of pressure and CO2 flow rate and the quadratic terms of pressure and temperature, had highly significant effects on the oil yield at the 1% level (P<0.01). The interactions between pressure and temperature, as well as temperature and CO2 flow rate, had significant effects on the oil yield at the 5% level (P<0.05). Response surface analysis From Eq. (1) we can see that the oil yield of N. glandulifera seed has a complex relationship with independent variables. The best way of expressing the effects of independent variables on the oil yield within the experimental space under investigation is to generate response surface plots of the equation. The three-dimensional response surfaces curves and corresponding contour plots were obtained using the Design Expert and are shown in Figs. 1, 2, and 3 to illustrate the relationship between independent variables and the oil yield. Fig. 1 shows response surface curve and its contour plot for the effects of pressure and temperature on the oil yield and their interaction at a fixed flow rate of 20 L h-1. The extraction pressure and temperature showed a quadratic effect on the response. At low pressure, the oil yield was increased with the increase of pressure. This is most likely due to the improvement of oil solubility resulted from the increased CO2 density with the rise of pressure (Lee et al. 2000). When the pressure was increased to levels greater than approximately 30 MPa, the negative quadratic effect began to have an impact. Such effect of pressure is not unexpected, when the pressure becomes too high, a reduction in the solvent diffusivity and mass transfer
Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction 153 Table 1 Box-Behnken design and response for the oil yield of N.glandulifera seed Trial no. Factors Responses Pressure (x,MPa) Temperature(x,C) CO:flow rate (x,Lh) Predicted(%) Observed (% -1(25) 0(40の 1(22) 35.270 35.280 2 -1(25) 0(40) -1(18) 32.358 32.540 -1(25) 1(45) 0(20) 31.906 31.818 -1(25) -1(35) 0(20) 32.765 32.662 0(30) 0(40) 0(20) 36.377 36.811 6 0(30) -1(35) -1(18) 34.345 34.266 0(30) 0(40) 0(20) 36.799 36.811 8 0(30 0(40) 0(20) 37.091 36.811 9 0(30) 0(40) 0(20) 37.099 36.811 0(30) 1451 -1(18) 33.690 33.597 11 0(30) 0(40) 0(20) 36.687 36.811 0(30) -1(35) 1(22) 36.075 36.168 13 0(30) 1(45) 1(22) 36.704 36.783 14 1(35) 0(40) -1(18) 34.299 34.290 5 1(35) -1(35) 0(20) 33.309 33.398 1(35) 1(45) 0(20) 34.085 34.188 > 1(35) 0(40) 1(22) 36.817 36.636 Table 2 Analysis of variance for the fitted quadratic polynomial model Source Sum of squares Mean square F-value P-value Model 51.5472 9 5.7275 80.5708 <0.0001 4.8221 4.8220 67.8341 <0.0001 0.0015 1 0.0015 0.0209 0.8891 12.9388 12.9388 182.0156 <0.0001 x 0.6684 1 0.6683 9.4014 0.0182 r 0.03881 1 0.0388 0.5460 0.4840 x 0.4122 0.4122 5.7981 0.0469 2 19.5706 19.5706 275.3080 <0.0001 x22 11.3029 11.3029 159.0027 <0.0001 x 0.0041 1 0.0041 0.0581 0.8164 Residual 0.4976 7 0.0711 Lack of fit 0.1324 0.0441 0.4833 0.7117 Pure error 0.3652 0.0913 Cor total 52.0448 g R-squared:0.9904 Adj R-squared:0.9781 coefficient will occur,which will offset the increase in CO,flow rate is shown in Fig.2 at the fixed extraction extraction rate caused by higher CO,density(Clifford temperature of 40C.How pressure affect the oil yield 1999;Xu et al.2008;Liu et al.2009).At low has been described in Fig.1.The CO,flow rate showed temperature,the oil yield was increased with the in- a positive and significant effect on the oil yield of crease of temperature.This is most likely due to the N.glandulifera seed.At a definite extraction pressure, increased mass transfer speed.However,at higher tem- the yield of oil was increased slightly with the increase perature levels(approximately 40C),the oil yield was of the CO,flow rate,and nearly reached a peak at the decreased with the further increase of temperature.This highest flow rate tested.It might be due to the de- is most likely due to the reduced density of carbon crease of resistance force in mass transfer with the dioxide,with a consequent reduction of solute solubility. increase of flow rate (Yin et al.2005).So,the opti- For a volatile solute,there is competition between its mum flow rate for the maximum yield ofoil was around solubility in SC-CO,and its volatility (Pourmortazavi 22 L h". and Hajimirsadeghi 2007).In this case,the optimum Fig.3 shows the effect of the extraction tempera- extraction pressure and temperature for the maximum ture and the CO,flow rate on the oil yield at a fixed yield of oil were around 30 MPa and 40C. extraction pressure of 30 MPa.How temperature and The interaction between the extraction pressure and CO,flow rate affect the oil yield has been described in 2012,CAAS.All rights reserved.Published by Elsevier Ltd
Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction 153 © 2012, CAAS. All rights reserved. Published by Elsevier Ltd. coefficient will occur, which will offset the increase in extraction rate caused by higher CO2 density (Clifford 1999; Xu et al. 2008; Liu et al. 2009). At low temperature, the oil yield was increased with the increase of temperature. This is most likely due to the increased mass transfer speed. However, at higher temperature levels (approximately 40°C), the oil yield was decreased with the further increase of temperature. This is most likely due to the reduced density of carbon dioxide, with a consequent reduction of solute solubility. For a volatile solute, there is competition between its solubility in SC-CO2 and its volatility (Pourmortazavi and Hajimirsadeghi 2007). In this case, the optimum extraction pressure and temperature for the maximum yield of oil were around 30 MPa and 40°C. The interaction between the extraction pressure and CO2 flow rate is shown in Fig. 2 at the fixed extraction temperature of 40°C. How pressure affect the oil yield has been described in Fig. 1. The CO2 flow rate showed a positive and significant effect on the oil yield of N. glandulifera seed. At a definite extraction pressure, the yield of oil was increased slightly with the increase of the CO2 flow rate, and nearly reached a peak at the highest flow rate tested. It might be due to the decrease of resistance force in mass transfer with the increase of flow rate (Yin et al. 2005). So, the optimum flow rate for the maximum yield of oil was around 22 L h-1. Fig. 3 shows the effect of the extraction temperature and the CO2 flow rate on the oil yield at a fixed extraction pressure of 30 MPa. How temperature and CO2 flow rate affect the oil yield has been described in Table 1 Box-Behnken design and response for the oil yield of N. glandulifera seed Trial no. Factors Responses Pressure (x1, MPa) Temperature (x2, °C) CO2 flow rate (x3, L h-1) Predicted (%) Observed (%) 1 -1 (25) 0 (40) 1 (22) 35.270 35.280 2 -1 (25) 0 (40) -1 (18) 32.358 32.540 3 -1 (25) 1 (45) 0 (20) 31.906 31.818 4 -1 (25) -1 (35) 0 (20) 32.765 32.662 5 0 (30) 0 (40) 0 (20) 36.377 36.811 6 0 (30) -1 (35) -1 (18) 34.345 34.266 7 0 (30) 0 (40) 0 (20) 36.799 36.811 8 0 (30) 0 (40) 0 (20) 37.091 36.811 9 0 (30) 0 (40) 0 (20) 37.099 36.811 10 0 (30) 1 (45) -1 (18) 33.690 33.597 11 0 (30) 0 (40) 0 (20) 36.687 36.811 12 0 (30) -1 (35) 1 (22) 36.075 36.168 13 0 (30) 1 (45) 1 (22) 36.704 36.783 14 1 (35) 0 (40) -1 (18) 34.299 34.290 15 1 (35) -1 (35) 0 (20) 33.309 33.398 16 1 (35) 1 (45) 0 (20) 34.085 34.188 17 1 (35) 0 (40) 1 (22) 36.817 36.636 Table 2 Analysis of variance for the fitted quadratic polynomial model Source Sum of squares df Mean square F-value P-value Model 51.5472 9 5.7275 80.5708 <0.0001 x1 4.8221 1 4.8220 67.8341 <0.0001 x2 0.0015 1 0.0015 0.0209 0.8891 x3 12.9388 1 12.9388 182.0156 <0.0001 x1x2 0.6684 1 0.6683 9.4014 0.0182 x1x3 0.03881 1 0.0388 0.5460 0.4840 x2x3 0.4122 1 0.4122 5.7981 0.0469 x1 2 19.5706 1 19.5706 275.3080 <0.0001 x2 2 11.3029 1 11.3029 159.0027 <0.0001 x3 2 0.0041 1 0.0041 0.0581 0.8164 Residual 0.4976 7 0.0711 Lack of fit 0.1324 3 0.0441 0.4833 0.7117 Pure error 0.3652 4 0.0913 Cor total 52.0448 16 R-squared: 0.9904 Adj R-squared: 0.9781
154 ZHANG Jun-ping et al. Y(oil yield,%) 36.9 1.00 35.625 0.50 34.35 8 33.075 0.00 R图 31.8 -0.50 1.00 1.00 69 59少2水】 0.50 0.50 0.00 0.00 -1.00 0.50 -0.50 X(pressure,MPa) -1.00 -0.50 0.00 0.50 1.00 X(temperature,C) -1.00-1.00 Xi(pressure,MPa】 Fig.1 Response surface curve and its contour plot for the effects of pressure and temperature at a constant CO,flow rate of 20 L h!on the oil yield. Y(oil yield.%) 38.2 1.00 36.775 35.35 372257 33.92 0.00 35352☐ 32.5 34439 362885 100 -0.50 1.00 35352 0.50 0.50 334766 0.00 0.00 -0.50 -0.50 -1.00 (flow rate,Lh) -1.00-1.00 (pressure,MPa) -1.00 -0.50 0.00 0.50 1.00 Xi(pressure,MPa) Fig.2 Response surface curve and its contour plot for the effects of pressure and CO,flow rate at a constant extraction temperature of 40C on the oil yield. Figs.1 and 2,respectively.At a definite extraction CO,flow rate. temperature,the CO,flow rate displayed a linear effect By solving the inverse matrix with Software Design on the response in Fig.3,there was a sharp increase of Expert,the optimum levels of the tested factors were oil yield from about 33.7 to 36.0%as the flow rate extraction pressure at 30.84 MPa,extraction tempera- was increased from 18 to 22 L h. ture at 40.57C,and flow rate at 22 L h.Under these From these three-dimensional response surface conditions,the maximum predicted yield was 38.19%, curves and corresponding contour plots,it is evident and the observed yield was about 37.87-38.25%,the that the CO,flow rate is the most significant factor experimental values agreed with the predicted values. affecting the oil yield in SC-CO,extraction,followed by the extraction pressure and temperature.The inter- Verification of the predictive model actions of extraction pressure and temperature,as well as extraction temperature and CO,flow rate are signifi- In order to validate the model Eq.(1),a total of 15 cant for the oil extraction from N.glandulifera seed. verification experiments were carried out under differ- compared to the interaction of extraction pressure and ent combinations of pressure,temperature,and time 2012.CAAS.All rights reserved.Published by Elsevier Ltd
154 ZHANG Jun-ping et al. © 2012, CAAS. All rights reserved. Published by Elsevier Ltd. Fig. 2 Response surface curve and its contour plot for the effects of pressure and CO2 flow rate at a constant extraction temperature of 40°C on the oil yield. Fig. 1 Response surface curve and its contour plot for the effects of pressure and temperature at a constant CO2 flow rate of 20 L h-1 on the oil yield. Figs. 1 and 2, respectively. At a definite extraction temperature, the CO2 flow rate displayed a linear effect on the response in Fig. 3, there was a sharp increase of oil yield from about 33.7 to 36.0 % as the flow rate was increased from 18 to 22 L h-1. From these three-dimensional response surface curves and corresponding contour plots, it is evident that the CO2 flow rate is the most significant factor affecting the oil yield in SC-CO2 extraction, followed by the extraction pressure and temperature. The interactions of extraction pressure and temperature, as well as extraction temperature and CO2 flow rate are significant for the oil extraction from N. glandulifera seed, compared to the interaction of extraction pressure and CO2 flow rate. By solving the inverse matrix with Software Design Expert, the optimum levels of the tested factors were extraction pressure at 30.84 MPa, extraction temperature at 40.57°C, and flow rate at 22 L h-1. Under these conditions, the maximum predicted yield was 38.19%, and the observed yield was about 37.87-38.25%, the experimental values agreed with the predicted values. Verification of the predictive model In order to validate the model Eq. (1), a total of 15 verification experiments were carried out under different combinations of pressure, temperature, and time
Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction 155 y (oil yield,% 1.00 382 37.025 0.50 ●373729 35.85 i 34.675 0.00 36677 33.5 -0.50 3307内 07④ 1.00 1.00 ●5866 0.50 0.50 0.00 0.00 34☒ -0.50 -1.00 (flow rate.Lh) 0.50 -1.00-1.00 -1.00 -0.50 0.00 0.50 1.00 X(temperature,C) (temperature,C) Fig.3 Response surface curve and its contour plot for the effects of temperature and CO,flow rate at a constant extraction pressure of 30 MPa on the oil yield. and the result is shown in Fig.4.The plot demon- 37.9 strates that the experimental points are evenly distrib- 37.7 uted around the diagonal of horizontal and vertical axis, which indicates that the experimental values are in good 37.5 1-0.9852r+0.573 agreement with the predicted values,and also suggests d that the predicted second order polynomial model is 37.3 accurate and reliable.Thus,a statistically significant 37.1 multiple regression relationship between the indepen- 37 373 37.5 37.7 37.9 dent variables (pressure,temperature,and CO,flow Observed value (% rate)and the response variable(oil yield)was established. The second order polynomial model could therefore be Fig.4 Observed values vs.predicted values for model verification. effectively used to represent the relationship among the parameters selected. consistent with the effect of N.glandulifera seed in activating blood circulation.The essential fatty acids Fatty acid composition of N.glandulifera seed oil like linoleic acid are not easily synthesized in the human body and must be supplied externally through the The fatty acid composition of N.glandulifera seed oil diet,and N.glandulifera seed oil can be a good nutri- extracted by SC-CO,and by Soxhlet method was de- tional supplement as a source of linoleic acid. termined by gas chromatography-mass spectrometry (GC-MS)and is shown in Table 3.The result shows that the fatty acid composition of oil extracted by the CONCLUSION two methods is similar,and the content of linoleic acid and oleic acid reached up to 48.30 and 22.28%, RSM was successfully applied for optimization of SC- respectively.As can be observed,the composition and CO,extraction parameters for N.glandulifera seed oil content in fatty acids do not depend on the extraction yield.The response surface plots indicated that the method.The oil contained 12 fatty acids,among them, three factors(pressure,temperature and CO,flow rate) linoleic acid was the most abundant unsaturated fatty significantly influenced the oil yield,independently and acids.This work also shows that N.glandulifera Freyn interactively.The optimum process parameters were seed oil is a rich source of linoleic acid.Linoleic acid obtained as:pressure 30.84 MPa,temperature 40.57C, has the ability to inhibit platelet aggregation,which is and CO,flow rate 22 L h.Under these conditions,the 2012,CAAS.All rights reserved.Published by Elsevier Ltd
Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction 155 © 2012, CAAS. All rights reserved. Published by Elsevier Ltd. consistent with the effect of N. glandulifera seed in activating blood circulation. The essential fatty acids like linoleic acid are not easily synthesized in the human body and must be supplied externally through the diet, and N. glandulifera seed oil can be a good nutritional supplement as a source of linoleic acid. CONCLUSION RSM was successfully applied for optimization of SCCO2 extraction parameters for N. glandulifera seed oil yield. The response surface plots indicated that the three factors (pressure, temperature and CO2 flow rate) significantly influenced the oil yield, independently and interactively. The optimum process parameters were obtained as: pressure 30.84 MPa, temperature 40.57°C, and CO2 flow rate 22 L h-1. Under these conditions, the Fig. 4 Observed values vs. predicted values for model verification. and the result is shown in Fig. 4. The plot demonstrates that the experimental points are evenly distributed around the diagonal of horizontal and vertical axis, which indicates that the experimental values are in good agreement with the predicted values, and also suggests that the predicted second order polynomial model is accurate and reliable. Thus, a statistically significant multiple regression relationship between the independent variables (pressure, temperature, and CO2 flow rate) and the response variable (oil yield) was established. The second order polynomial model could therefore be effectively used to represent the relationship among the parameters selected. Fatty acid composition of N. glandulifera seed oil The fatty acid composition of N. glandulifera seed oil extracted by SC-CO2 and by Soxhlet method was determined by gas chromatography-mass spectrometry (GC-MS) and is shown in Table 3. The result shows that the fatty acid composition of oil extracted by the two methods is similar, and the content of linoleic acid and oleic acid reached up to 48.30 and 22.28%, respectively. As can be observed, the composition and content in fatty acids do not depend on the extraction method. The oil contained 12 fatty acids, among them, linoleic acid was the most abundant unsaturated fatty acids. This work also shows that N. glandulifera Freyn seed oil is a rich source of linoleic acid. Linoleic acid has the ability to inhibit platelet aggregation, which is Fig. 3 Response surface curve and its contour plot for the effects of temperature and CO2 flow rate at a constant extraction pressure of 30 MPa on the oil yield
156 ZHANG Jun-ping et al. Table 3 Fatty acid compositiona(%)of N.glandulifera seed oil Supercritical carbon dioxide extraction extracted with SC-CO,extraction and Soxhlet extraction Fatty acid composition(%) SC-CO,extraction Soxhlet extraction(8 h) Myristic acid 0.18 0.18 Supercritical fluid extraction was performed on a Hua'an 9-Hexadecenoic acid 0.28 0.28 supercritical fluid extractor(Model HA121-50-01,Jiangsu, Heptadecanoic acid 0.24 0.12 China).In each experiment,150 g sample with particle size Palmitic acid 16.65 16.71 of 0.45 mm was loaded into a 1 000 mL extraction vessel. Linoleic acid 48.30 47.85 Oleic acid 22.28 22.82 The operating conditions were set as follows:pressure 7-Octadecenoic acid 2.20 2.13 (25-35 MPa),temperature (35-45C),and CO,flow rate(18- stearic acid 4.17 4.13 22 L h).The temperatures were controlled automatically, 10.13-Octadecadienoic acid 0.39 0.37 and the CO,flow rate and the pressures in both the extrac- Arachidic acid 0.15 0.18 tor and separator were controlled manually using a back- 11,13-Eicosadienoic acid 4.47 4.51 11-Eicosenoic acid 0.70 0.72 pressure regulator.When the desired pressure, temperature,and CO,flow rate were reached,the extrac- GC area percentage. tion was started.In this experiment,we found that the oil yield reached to maximum within 30 min of extraction for all the experiments studied.This may be due to the fact that experimental values agreed with the predicted value. the extractable components were easily accessible by the The adequacy of the predictive model was verified by solvent.So,each extraction run lasted for 60 min since the validation experiments.The fatty acids composi- longer extraction times did not significantly increase the tion of N.glandulifera seed oil extracted by SC-CO. yield of oil.The oil dissolved in the SC-CO,was discharged into the separator where carbon dioxide was depressurized; was similar to that of oil extracted by hexane the oil was separated from the carbon dioxide and col- lected in the separator.The seed oil was recovered and MATERIALS AND METHODS the oil yield was determined gravimetrically Response surface experimental design Materials RSM was applied to optimize the operating conditions of Seeds of N.glandulifera were purchased from Xinjiang SC-CO,extraction to obtain a high yield of oil from Uigur Hospital at Urumqi in 2008,the moisture content of N.glandulifera seed in this study.Three independent which was 6.6 wt%as determined by an infrared moisture variables studied were extraction pressure (X,)extraction meter (A-D4714.A&D Co.Ltd.,Japan).The seeds were temperature (X,)and CO,flow rate (X)for uncoded vari- crushed to particle size of 0.45 mm.The carbon dioxide(99.5%) able levels.These independent variables and their levels were selected based on our preliminary experiments(data used in supercritical fluid extraction(SFE)was supplied by not shown).Each independent variable was coded at three Hongjian Co.(Nanjing,China).All the chemicals used were levels:-1,0,and +1,their corresponding levels were as of analytical grade. follows(low,medium,and high values):pressure of 25,30, and 35 MPa;temperature of 35,40,and 45C;CO,flow rate Soxhlet extraction of 18,20,and 22 L h.The dependent variable was the oil yield.The coded and corresponding uncoded indepen- dent variables used in the RSM design are listed in Table 4. Soxhlet extraction was carried out in triplicate for each ex- A Box-Behnken design was applied to optimize these perimental run.10 g of N.glandulifera seed powder (with three independent variables,and is shown in Table 1.In the particle size of 0.45 mm and moisture content of 6.6 wt%) this study,the experimental design contained 17 trials and was weighted and packed in a Soxhlet apparatus and then the value of the responses was the mean of triplications. continuously extracted for 8 h at one time using n-hexane Five replicates at the centre of the design were used for (60-80C)as the solvent.After extraction,the solvent was evaporated by rotary vacuum evaporator (30C)and the Table 4 Independent variables and their levels for RSM design extract was dried at 103C to remove residual solvent until Level Independent variable Symbols a constant weight(Zaidul et al.2006).The fatty acid com- Codedi) Uncoded -1 0 Pressure (MPa) X 25 30 35 ponents of the N.glandulifera seed oil obtained by Soxhlet Temperature(C) 35 40 45 extraction were analyzed and compared with the oil extracted CO:flow rate (Lh) X 18 20 22 by SC-CO,. xX-305:x=(X-455:x=(-20/2 2012,CAAS.All rights reserved.Published by Elsevier Ltd
156 ZHANG Jun-ping et al. © 2012, CAAS. All rights reserved. Published by Elsevier Ltd. experimental values agreed with the predicted value. The adequacy of the predictive model was verified by the validation experiments. The fatty acids composition of N. glandulifera seed oil extracted by SC-CO2 was similar to that of oil extracted by hexane. MATERIALS AND METHODS Materials Seeds of N. glandulifera were purchased from Xinjiang Uigur Hospital at Urumqi in 2008, the moisture content of which was 6.6 wt% as determined by an infrared moisture meter (A-D4714, A&D Co. Ltd., Japan). The seeds were crushed to particle size of 0.45 mm. The carbon dioxide (99.5%) used in supercritical fluid extraction (SFE) was supplied by Hongjian Co. (Nanjing, China). All the chemicals used were of analytical grade. Soxhlet extraction Soxhlet extraction was carried out in triplicate for each experimental run, 10 g of N. glandulifera seed powder (with the particle size of 0.45 mm and moisture content of 6.6 wt%) was weighted and packed in a Soxhlet apparatus and then continuously extracted for 8 h at one time using n-hexane (60-80°C) as the solvent. After extraction, the solvent was evaporated by rotary vacuum evaporator (30°C) and the extract was dried at 103°C to remove residual solvent until a constant weight (Zaidul et al. 2006). The fatty acid components of the N. glandulifera seed oil obtained by Soxhlet extraction were analyzed and compared with the oil extracted by SC-CO2 . Supercritical carbon dioxide extraction Supercritical fluid extraction was performed on a Hua’an supercritical fluid extractor (Model HA121-50-01, Jiangsu, China). In each experiment, 150 g sample with particle size of 0.45 mm was loaded into a 1 000 mL extraction vessel. The operating conditions were set as follows: pressure (25-35 MPa), temperature (35-45°C), and CO2 flow rate (18- 22 L h-1). The temperatures were controlled automatically, and the CO2 flow rate and the pressures in both the extractor and separator were controlled manually using a backpressure regulator. When the desired pressure, temperature, and CO2 flow rate were reached, the extraction was started. In this experiment, we found that the oil yield reached to maximum within 30 min of extraction for all the experiments studied. This may be due to the fact that the extractable components were easily accessible by the solvent. So, each extraction run lasted for 60 min since longer extraction times did not significantly increase the yield of oil. The oil dissolved in the SC-CO2 was discharged into the separator where carbon dioxide was depressurized; the oil was separated from the carbon dioxide and collected in the separator. The seed oil was recovered and the oil yield was determined gravimetrically. Response surface experimental design RSM was applied to optimize the operating conditions of SC-CO2 extraction to obtain a high yield of oil from N. glandulifera seed in this study. Three independent variables studied were extraction pressure (X1 ), extraction temperature (X2 ) and CO2 flow rate (X3 ) for uncoded variable levels. These independent variables and their levels were selected based on our preliminary experiments (data not shown). Each independent variable was coded at three levels: -1, 0, and +1, their corresponding levels were as follows (low, medium, and high values): pressure of 25, 30, and 35 MPa; temperature of 35, 40, and 45°C; CO2 flow rate of 18, 20, and 22 L h-1. The dependent variable was the oil yield. The coded and corresponding uncoded independent variables used in the RSM design are listed in Table 4. A Box-Behnken design was applied to optimize these three independent variables, and is shown in Table 1. In this study, the experimental design contained 17 trials and the value of the responses was the mean of triplications. Five replicates at the centre of the design were used for Table 3 Fatty acid compositiona (%) of N. glandulifera seed oil extracted with SC-CO2 extraction and Soxhlet extraction Fatty acid composition (%)1) SC-CO2 extraction Soxhlet extraction (8 h) Myristic acid 0.18 0.18 9-Hexadecenoic acid 0.28 0.28 Heptadecanoic acid 0.24 0.12 Palmitic acid 16.65 16.71 Linoleic acid 48.30 47.85 Oleic acid 22.28 22.82 7-Octadecenoic acid 2.20 2.13 stearic acid 4.17 4.13 10,13-Octadecadienoic acid 0.39 0.37 Arachidic acid 0.15 0.18 11,13-Eicosadienoic acid 4.47 4.51 11-Eicosenoic acid 0.70 0.72 1) GC area percentage. Table 4 Independent variables and their levels for RSM design Independent variable Symbols Level Coded1) Uncoded -1 0 1 Pressure (MPa) x1 X1 25 30 35 Temperature (°C) x2 X2 35 40 45 CO2 flow rate (L h-1) x3 X3 18 20 22 1) x1 =(X1 -30)/5; x2 =(X2 -45)/5; x3 =(X3 -20)/2
Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction 157 estimation of a pure error sum of square.All experiments carbon dioxide extraction of cottonseed oil.Journal of were carried out in a randomized order to minimize the ef- Food Engineering,79,892-898. fect of unexpected variability in the observed response Brunner G.1994.Gas extraction:An Introduction to due to extraneous factors.A second-order polynomial Fundamentals of Supercritical Fluids and the model was used to express the oil yield (Y)as a function of Application to Separation Processes.Springer the independent variables, Publishing,New York. Y=B+Bx+Bx2+B:x:+B2xx2+Bxx:+B23X2X3 Chang C J,Chiu KL,Chen YL,Chang C Y.2000.Separation +B1x2+B2zx22+B2 (2) of catechins from green tea using carbon dioxide Where,Y is predicted response;B is a constant;B,B2, extraction.Food Chemistry,68,109-113. B,are linear coefficients;B2 B B2 are cross-product Chow E T S,Wei L S,de Vor R E,Steinberg M P.1998 coefficients;and B BB are quadratic coefficients;x, Performance of ingredients in a soybean whipped x2,x,are input variables. topping.Journal of Food Science,52,1761-1765. A software Design-Expert 7.1.4 trial (Stat-Ease Inc., Chu B S,Quek S Y,Baharin B S.2003.Optimization of Minneapolis,MN,USA)was used to obtain the coeffi- enzymatic hydrolysis for concentration of vitamin E in cients of the second-order polynomial model.The good- palm fatty acid distillate.Food Chemistry,80,295-302. ness of fit of the model was evaluated by the analysis of Clifford T.1999.Fundamentals of Supercritical Fluids variance (ANOVA)and the coefficient of determination Oxford Science Publications,New York,USA (R2)(Chu et al.2003). Friedrich J P,List G R,Heakin A J.1982.Petroleum-free extraction of oil from soybean with supercritical CO, Gas chromatography-mass spectrometry Journal of the American Oil Chemists'Society,59 282-292. analysis Hierro M T G,Santa-Maria G.1992.Supercritical fluid extraction of vegetable and animal fats with CO,-a The preparation of fatty acid methyl ester(FAME)was mini review.Food Chemistry,45,189-192. carried out as follows:for saponification of free fatty acids, Huang W,Li Z,Niu H,Li D,Zhang J.2008.Optimization of 5 g of the oil was added into 30 mL of 1 mol L KOH/ operating parameters for supercritical carbon dioxide ethanol;after mixed well,5 g of the mixture was dissolved extraction of lycopene by response surface in 30 mL of 2%(v/v)H,SO/methanol for esterification of methodology.Journal of Food Engineering,89,298- free fatty acids.The analysis of FAME was performed on 302. an Agilent 5975 inert-GC-MSD equipped with a DB-5MS Kuk M S,Hron R J.1994.Supercritical carbon dioxide column (30 mx0.32 mmx0.25 um).The sample (1 uL)was extraction of cottonseed with co-solvents.Journal of injected at a split ratio of 30:1 and the injector temperature American Oil Chemists Society,71,1353-1356. was set at 280C.The GC oven temperature was pro- Lee J,Ye L,Landen WO,Eitenmiller RR.2000.Optimization grammed isothermal at 60C for I min,and then increased of an extraction procedure for the quantification of from 60C to 280C at 10C min.The final temperature was vitamin E in tomato and broccoli using response surface maintained for 50 min.The flame ionization detector(FID) methodology.Journal of Food Composition and Analysis,13,45-57 was maintained at 230C.The carrier gas was helium,at a flow rate of 0.8 mL min.Electron impact mass spectra Lee WY,Cho Y J,Oh SL,Park J H,Cha WS,Jung J Y.2000 (70 eV)were acquired in the m/z range 20-550 amu.Then, Extraction of grape seed oil by supercritical CO2 and ethanol modifier.Food Science and Biotechnology,9. the compounds were identified using mass spectrometric 174-178. analysis.Spectra of the compounds were compared with List G R.Friedrich J P.Christianson DD.1984.Properties those in the US National Institute of Standards and Tech- and processing of corn oils obtained by extraction with nology Library (NIST02.L).The composition was ex- supercritical carbon dioxide.Journal of the American pressed in percentage values calculated directly from GC Oil Chemists'Society,61,1849-1851. peak areas,in a base without solvent and without applying Liu S C,Yang F,Zhang C H,Ji H W,Hong PZ,Deng C J. correction factors.All above oil analysis was finished in 2009.Optimization of process parameters for the Modern Analysis Center of Nanjing University,China supercritical carbon dioxide extraction of Passiflora seed oil by response surface methodology.Journal of Acknowledgements Supercritical Fluids,48,9-14. This work was supported by the Public Welfare Industry Pourmortazavi S M,Hajimirsadeghi SS.2007.Supercritical (Agriculture)Research Program,China(200903018). fluid extraction in plant essential and volatile oil analysis.Journal of Chromatography (A),1162,2-24. Reverchon E.1997.Supercritical fluid extraction and References fractionation of essential oils and related products Bhattacharjee P,Singhal R S,Tiwari S R.2007.Supercritical Journal of Supercritical Fluids,10.1-37. 2012,CAAS.All rights reserved.Published by Elsevier Ltd
Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction 157 © 2012, CAAS. All rights reserved. Published by Elsevier Ltd. estimation of a pure error sum of square. All experiments were carried out in a randomized order to minimize the effect of unexpected variability in the observed response due to extraneous factors. A second-order polynomial model was used to express the oil yield (Y) as a function of the independent variables, Y=B0+B1 x 1+B2 x 2+B3 x 3+B1 2 x 1 x 2+B1 3 x 1 x 3+B2 3 x 2 x 3 . +B11x1 2 +B22x2 2 +B33x3 2 (2) Where, Y is predicted response; B0 is a constant; B1 , B2 , B3 are linear coefficients; B12, B13, B23 are cross-product coefficients; and B11, B22, B33 are quadratic coefficients; x1 , x2 , x3 are input variables. A software Design-Expert 7.1.4 trial (Stat-Ease Inc., Minneapolis, MN, USA) was used to obtain the coefficients of the second-order polynomial model. The goodness of fit of the model was evaluated by the analysis of variance (ANOVA) and the coefficient of determination (R2 ) (Chu et al. 2003). Gas chromatography-mass spectrometry analysis The preparation of fatty acid methyl ester (FAME) was carried out as follows: for saponification of free fatty acids, 5 g of the oil was added into 30 mL of 1 mol L-1 KOH/ ethanol; after mixed well, 5 g of the mixture was dissolved in 30 mL of 2% (v/v) H2 SO4 /methanol for esterification of free fatty acids. The analysis of FAME was performed on an Agilent 5975 inert-GC-MSD equipped with a DB-5MS column (30 m×0.32 mm×0.25 µm). The sample (1 µL) was injected at a split ratio of 30:1 and the injector temperature was set at 280°C. The GC oven temperature was programmed isothermal at 60°C for 1 min, and then increased from 60°C to 280°C at 10°C min-1. The final temperature was maintained for 50 min. The flame ionization detector (FID) was maintained at 230°C. The carrier gas was helium, at a flow rate of 0.8 mL min-1. Electron impact mass spectra (70 eV) were acquired in the m/z range 20-550 amu. Then, the compounds were identified using mass spectrometric analysis. Spectra of the compounds were compared with those in the US National Institute of Standards and Technology Library (NIST02.L). The composition was expressed in percentage values calculated directly from GC peak areas, in a base without solvent and without applying correction factors. All above oil analysis was finished in the Modern Analysis Center of Nanjing University, China. Acknowledgements This work was supported by the Public Welfare Industry (Agriculture) Research Program, China (200903018). References Bhattacharjee P, Singhal R S, Tiwari S R. 2007. Supercritical carbon dioxide extraction of cottonseed oil. Journal of Food Engineering, 79, 892-898. Brunner G. 1994. Gas extraction: An Introduction to Fundamentals of Supercritical Fluids and the Application to Separation Processes. Springer Publishing, New York. Chang C J, Chiu K L, Chen Y L, Chang C Y. 2000. Separation of catechins from green tea using carbon dioxide extraction. Food Chemistry, 68, 109-113. Chow E T S, Wei L S, de Vor R E, Steinberg M P. 1998. Performance of ingredients in a soybean whipped topping. Journal of Food Science, 52, 1761-1765. Chu B S, Quek S Y, Baharin B S. 2003. Optimization of enzymatic hydrolysis for concentration of vitamin E in palm fatty acid distillate. Food Chemistry, 80, 295-302. Clifford T. 1999. Fundamentals of Supercritical Fluids. Oxford Science Publications, New York, USA. Friedrich J P, List G R, Heakin A J. 1982. Petroleum-free extraction of oil from soybean with supercritical CO2. Journal of the American Oil Chemists’ Society, 59, 282-292. Hierro M T G, Santa-Maria G. 1992. Supercritical fluid extraction of vegetable and animal fats with CO2 - a mini review. Food Chemistry, 45, 189-192. Huang W, Li Z, Niu H, Li D, Zhang J. 2008. Optimization of operating parameters for supercritical carbon dioxide extraction of lycopene by response surface methodology. Journal of Food Engineering, 89, 298- 302. Kuk M S, Hron R J. 1994. Supercritical carbon dioxide extraction of cottonseed with co-solvents. Journal of American Oil Chemists Society, 71, 1353-1356. Lee J, Ye L, Landen W O, Eitenmiller R R. 2000. Optimization of an extraction procedure for the quantification of vitamin E in tomato and broccoli using response surface methodology. Journal of Food Composition and Analysis, 13, 45-57. Lee W Y, Cho Y J, Oh S L, Park J H, Cha W S, Jung J Y. 2000. Extraction of grape seed oil by supercritical CO2 and ethanol modifier. Food Science and Biotechnology, 9, 174-178. List G R, Friedrich J P, Christianson D D. 1984. Properties and processing of corn oils obtained by extraction with supercritical carbon dioxide. Journal of the American Oil Chemists’ Society, 61, 1849-1851. Liu S C, Yang F, Zhang C H, Ji H W, Hong P Z, Deng C J. 2009. Optimization of process parameters for supercritical carbon dioxide extraction of Passiflora seed oil by response surface methodology. Journal of Supercritical Fluids, 48, 9-14. Pourmortazavi S M, Hajimirsadeghi S S. 2007. Supercritical fluid extraction in plant essential and volatile oil analysis. Journal of Chromatography (A), 1162, 2-24. Reverchon E. 1997. Supercritical fluid extraction and fractionation of essential oils and related products. Journal of Supercritical Fluids, 10, l-37
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