Optimization of the Oil Extraction from Camelina (Camelina sativa) Seeds Using Response Surface Methodology

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1 Optimization of the Oil Extraction from Camelina (Camelina sativa) Seeds Using Response Surface Methodology MALINA AVRAM, MARTA STROESCU 1 *, ANICUTA STOICA-GUZUN, OCTAVIAN FLOAREA University Politehnica of Bucharest, Faculty of Applied Chemistry and Material Science, Department of Chemical and Biochemical Engineering, 1-7 Polizu Str., , Bucharest, Romania Camelina sativa, also known as German sesame or Siberian oilseed, is a cruciferous oilseed plant and has recently gained considerable interest because of the healthy properties of the oil, its potential as a biofuel and its soy quality meal. Camelina oil due to its relatively high content (>50%) in omega-3 and 6 fatty acids and low saturated fatty acids, is considered to be a high quality edible oil. The objectives of this study are to determine the optimum conditions for the solvent extraction of Camelina oil using a three-level three-factor Box-Behnken design under response surface methodology (RSM). The experimental data obtained were analyzed by Pareto analysis of variance (ANOVA) and fitted to a second-order polynomial equation using multiple regression analysis. The experimental values agreed with those predicted values. Keywords: Camelina seeds oil, solvent extraction, optimization, Box-Behnken Design Camelina (Camelina sativa L.) is a cruciferous oilseed plant belonging to the Brassicaceae (mustard) family, which include important food crops. Considered once a weed nowadays it gained a growing interest due to its high oil content with healthy properties and its potential as biofuel. It is a promising sustainable alternative energy crop because it can be grown as an annual summer or biannual winter crop under different climatic conditions, having lower water, pesticide, and fertilizer requirements compared to rapeseed/canola, soybeans or sunflowers [1,2]. Camelina produces soy quality meal and canola quality oil. Camelina meal contains oil, proteins, and carbohydrates. Because of its excellent omega 3 and 6 content, it could be used as feed for animals [3]. Camelina oil, due to its relatively high (>50%) content in omega-3 and 6 fatty acids and low in saturated fatty acids, is considered to be a high quality edible oil [4-6]. Camelina oil contains also tocopherols, sterols, and polyphenols, which makes it more resistant to oxidation. The health effects, technical stability and almond-like tasty aroma make camelina an important edible oil for the future. Recently, camelina oil was evaluated as a viable fuel alternative [7]. C. sativa biodiesel presents serious drawbacks for biodiesel applications due to its weak oxidation stability. To make C. sativa a good row material for use in biofuels it is necessary to reduce the high degree of unsaturation and the molecular weight of the oil. Camelina oil is extracted from the seeds by various processes such as cold pressing, solvent extraction or supercritical CO 2 extraction [8]. Artificial neural network and response surface methodology are the most used methods for modelling and optimization of active compounds extraction from plants [9, 10]. Response surface methodology (RSM) is a collection of statistical techniques widely used in designing experiments, modeling and optimization of processes allowing getting valuable information with a minimum of experiences. An experimental design, such as three level factorial Box-Behnken (BBD) or central composite (CCD) design are used to fit a second-order polynomial, to evaluate the quality of the fitted model and its accuracy to make previsions in relation to the obtained experimental data. These techniques are widely used in optimizing extraction processes [11-17]. The aim of this paper is to find out optimal process parameters for camelina oil solvent extraction using response surface methodology (RSM) with a three-variablethree-level Box-Behnken design (BBD). From our best knowledge no references were yet published concerning the optimization of solvent extraction of camelina oil. Experimental part Materials and chemicals Camelina seeds were purchased from Research and Development Station for Agriculture, Secuieni, Neamt. The seeds were grinded to get particles powder with diameters in the range of about μm and then sieved. n-hexane (analytical grade) purchased from SIGMA ALDRICH was used as solvent in all extraction experiments. Extraction procedure Laboratory Soxhlet-extraction with n-hexane as solvent was used to determine the initial oil content in C. sativa seeds. About 5 g of grinded seeds was weight and subject to extraction with 150 ml n-hexane for 8 h. The extraction was done in triplicate. The average of the initial oil content was ± 0.68%. Moisture content of the seeds (4.90% ± 0.02%) was determined using a thermo-balance OHAUS MB23. Batch extraction was used in all experiments. In a typical experiment 10 g of grinded camelina seeds was weighed and placed into a glass vessel foreseen with water condenser. A magnetic stirrer with heating plate was used in order to ensure a good contact between the phases and to set up the working temperature. After a predetermined time the mixture was filtered under vacuum and the solvent distilled at low pressure. The extracted oil was dried until constant weight. Finally the relative oil extraction yield (Y) was calculated from the following equation: * marta_stroescu@yahoo.com; Tel.: REV. CHIM. (Bucharest) 66 No

2 Table 1 EXPERIMENTAL RANGE, LEVEL AND CODE OF INDEPENDENT VARIABLES FOR OIL EXTRACTION FROM CAMELINA SEEDS Fig.1. Chromatogram of the oil extracted from C. sativa seeds Table 2 COMPOSITION (wt.%) OF CAMELINA SATIVA OIL COMPARED WITH LITERATURE DATA All extraction experiments were performed in triplicate. Analysis of the extracts Chromatographic analysis was performed in order to establish the extracted oil composition. Fatty acid methyl esters were prepared by transesterification using 14% boron trifluoride in methanol as catalyst. The esters analysis was performed with a Termo-GC (Thermo Scientific) equipped with MS detector DSQ P 5000 using Macrogol R column (30 m length, 0.25 mm i.d. and film thickness 0.2 μm). The carrier gas was helium (1.0 ml/ min). The column and detector temperature were set at 250 and 270 o C respectively. One microliter of the methyl esters was injected into the column, and the fatty acids were identified by comparison of obtained data with those of the computer library. Experimental design In a preliminary research a single factor experimental method was used to study the effect of process variables (particle size, extraction temperature, liquid/solid ratio and extraction time) on the relative oil extraction yield. These experiments allowed establishing the main process parameters (temperature, liquid/solid ratio and time) and the range for each independent variable. In all performed experiments grinded seeds with a particle diameter of 0.63 mm were used. A three level, three factors Box Behnken response surface experimental design (BBD) was employed to investigate the individual and interactive effects of process variables on the relative oil extraction yield. The uncoded and coded independent variables and experimental design are listed in table 1. A quadratic model was chosen for predicting the values of response variable, according to the following equation: where: Y is the response (relative extraction yield); β 0 a constant term; (1) β are coefficients of linear terms; i β coefficients of quadratic terms; ii β the coefficients of cross product terms. Linear, ij quadratic, and interaction coefficients were determined by the least square regression followed by analysis of variance (ANOVA). Values of p < 0.05 were considered significant. For experimental design analysis and data processing the statistical package software Statistica (Trial version 10.0 Stat Soft Inc., Tulsa, USA) was used. The optimal extraction conditions for camelina oil obtained with the desirability profile using Statistica software were compared with those calculated from the following equation: where i=1, 2, 3; j=1, 2, 3; k=1, 2, 3; i j k. Results and discussions Composition of Camelina sativa oil The extracted oil using hexane as solvent after transesterification were GC analyzed. A typical chromatograph is presented in figure 1. Table 2 presents the main compounds of the analyzed oil sample compared with data reported in the literature. One can see from table 2 the high level of unsaturation of the oil, which depends on its origin. The analyzed extracted oil has maintained his composition in all experiments. Fitting the model The three variables (temperature, liquid/solid ratio, time) and three factorial levels Box Behnken design was applied for response function fitting. The whole design consisted of 17 experimental points carried out in random order. Five replicates (experiments 13-17) at the center of the design were used for estimating of a pure error sum of squares.the uncoded and coded independent variables and the experimental Box-Behnken design matrix are listed in table 3. (2) REV. CHIM. (Bucharest) 66 No

3 Table 3 THREE LEVEL BOX BEHNKEN DESIGN WITH THREE INDEPENDENT VARIABLES, EXPERIMENTAL AND PREDICTED RESULTS Table 4 ESTIMATED COEFFICIENTS OF THE SECOND ORDER POLYNOMIAL EQUATION OF RESPONSE SURFACE OF YIELD OIL EXTRACTED FROM CAMELINA SATIVA SEEDS The regression coefficients, related to coded variables, obtained by fitting experimental data to the second order response model for the investigated response (relative extraction efficiency) are presented in table 4. It can be seen that only the linear parameter corresponding to temperature is significant, while all quadratic parameters and the interaction parameter between the liquid/solid ratio and time are significant (p < 0.05 or p < 0.01). These results indicate that the major contributing factor to the relative extraction efficiency is the temperature. This is confirmed also by the Pareto chart, presented in figure 2. By employing multiple regression analysis on the experimental data an empirical relationship between the experimental variables and the response was obtained: where X 1, X 2, and X 3 are in terms of coded factors of the test variables, extraction temperature, liquid/solid ratio and extraction time, respectively. Fig. 2. Pareto chart for the effects of temperature (Temp), liquid/ solid ratio (L/S ratio), extraction time (Time) and of their interactions on the relative extraction efficiency of camelina oil (3) Eliminating the insignificant terms from equation (3) the predicted response Y for relative extraction efficiency can be obtained by the following second-order polynomial equation: The analysis of variance for the experimental results of the BBD is shown in table 5. The Model F-value (35.74) implied that the obtained model is valid. The sufficiency and fitness of the model was verified by computing the coefficient of determination (R 2 ) and adjusted-r 2. The value of R 2 coefficient (0.9787) revealed a satisfactory adjustment of the quadratic model to the experimental data. Also the value of adjusted R 2 (0.9513) indicates a good correlation between the experimental and the predicted values. The relatively high coefficient of determination and very small p-value (<0.0001) demonstrate that the quadratic polynomial model is significant to characterize the relationship between the model response and the process variables and adequate for predicting the relative extraction efficiency of seeds oil. The model adequacy is also sustained by diagnostic plots such as the experimental data versus predicted ones, presented in figure 3. One can see that the data points are positioned close to the straight line, signifying that there is a satisfactory agreement between experimental and model data. The three-dimensional (3D) response surfaces that are the graphical representations of regression equation obtained from the calculated response surface are indicated in figure 4. They showed the influence of two variables on the process while the third variable was maintained as constant. From figure 4a where the effect of extraction temperature (X 1 ) and liquid/solid ratio (X 2 ) is presented, the extraction being constant at zero level, it could be observed that the liquid/solid ratio has a very slightly effect, while the temperature increase until a value, corresponding (4) REV. CHIM. (Bucharest) 66 No

4 Table 5 ANALYSIS OF VARIANCE (ANOVA) OF THE MODELED RESPONSE Fig 3. Comparison between predicted and experimental values for the camelina oil relative extraction efficiency Fig. 4. Response surfaces of camelina oil relative extraction efficiency as a function of: (a) temperature and L/S ratio; (b) temperature and time and (c) L/S ratio and time Fig. 5. Profiles for predicted relative extraction efficiency and the desirability level for different influencing factors for optimum oil extraction from Camelina sativa seeds. to the zero coded value of the variable, rise the relative extraction efficiency, after that it causes its decrease. Figure 4b shows the 3D surface and contour plot of the effect of extraction temperature (X 1 ) and extraction time (X 3 ) upon the relative extraction efficiency, while the liquid/ solid ratio is kept constant at zero level. It can be observed that the relative extraction efficiency increases with the increase of temperature and extraction time. A complex 420 influence of the liquid/solid ratio (X 2 ) and extraction time (X 3 ) on the relative extraction efficiency of camelina oil could be observed from the 3D surface and contour plot presented in figure 4c. Optimization of the camelina oil extraction The desirability profiles (fig. 5), indicates that the optimal extraction conditions (maximum of relative extraction efficiency with a minimum of liquid/solid ratio) can be REV. CHIM. (Bucharest) 66 No

5 achieved in the central point of coded variables, which in uncoded it means variables an extraction temperature of 40 C, a liquid/solid ratio of 6/1 ml/g and an extraction time of 2 h. Similar results were obtained from eq. (3) meaning X 1 = 0.114, X 2 = and X 3 = , namely 42.3 C extraction temperature, a liquid solid ratio of 5.8 ml/g and 1.9 h extraction time. In order to validate the model prediction, experiments were performed under the above conditions obtaining for the relative extraction efficiency a value of 88,10 ± 0.25%, being in a good agreement with theoretical prediction. Conclusions The oil extraction from camelina (Camelina sativa) seeds was studied using a statistical method based on the response surface methodology (RSM) in order to identify and quantify the variables which may maximize the relative extraction efficiency. The response surface methodology (RSM) has several advantages compared to the classical methods giving a large amount of information from a small number of experiments and allowed to observe the interaction effect of the independent parameters on the response. A second order polynomial model was chosen to describe and predict the relative extraction efficiency with process parameters changing. The most significant contribution to the relative oil extraction efficiency are the linear (X 1 ) and quadratic(x 12 ) terms of temperature, the quadratic terms of the liquid/solid ratio (X 22 ) and extraction time (X 32 ) and the interaction term between the liquid/ solid ratio and extraction time (X 2 X 3 ). The optimum process parameters determined were: 42.3 C extraction temperature, a liquid/ solid ratio of 5.8 ml/g and 1.9 h extraction time, that are in good agreement with the predicted values obtained using RSM. This study could be a starting point in developing processes to a higher valorization of camelina oil rich in unsaturated fatty acids, especially omega 3 and omega 6. References 1. MOSER, B. R., Lipid Technology, 22(12), 2010, p FAN L., ESKIN M. N. A., Recent Res. Devel. Lipids, 9, 2013, p REDDY N, JIN E, CHEN L, JIANG X, YANG Y., J Agric Food Chem., 60(19), 2012, p SAMPATH A., Chemical characterization of camelina seed oil, MSc Thesis, The State University of New Jersey, TONCEA I., NECSERIU D., PRISECARU T., BALINT L.-N., GHILVACS M.-I., POPA M., Romanian Biotechnological Letters, 18(5), 2013, p MOSER, B.R., VAUGHN, S.F. Bioresour. Technol. 2010, 101, [ 7. CIUBOTA-ROSIE C., RUIZ J. R., RAMOS M. J., PEREZ A., Fuel, 105, 2013, p MOSLAVAC T., JOKIC S., SUBARIC D., ALADIC K., VUKOJA J., PRCE N., Ind. Crops Prod, 54, 2014, p TOBOC, A.A., LAVRIC, V., Rev. Chim. (Bucharest), 63, no. 7, 2012, p KHAJEH M., J. of Supercritical Fluids, 55, 2011, p SZYD OWSKA-CZERNIAK A., TROKOWSKI K., SZ YK E., Ind. Crops Prod., 33, 2011, p STROESCU M., STOICA-GUZUN A., GHERGU S., CHIRA N., JIPA I., Ind. Crops Prod., 43, 2013, p MILIC P. S., RAJKOVIC K. M., STAMENKOVIC O. S., VELJKOVIC V. B., Ultrason. Sonochem., 20, 2013, p LIU Z., MEI L., WANG Q., SHAO Y., TAO Y., LWT - Food Sci. Technol., 56, 2014, p SWAMY G. J., SANGAMITHRA A., CHANDRASEKAR V., Dyes Pigm., 111, 2014, p MARAN J. P., SIVAKUMAR V., THIRUGNANASAMBANDHAM K., SRIDHAR R., Carbohydr. Polym., 101, 2014, p SUNA Y.-X., LIUA J.-C., KENNEDY J. F., Carbohydr. Polym., 82, 2010, p.209 Manuscript received: REV. CHIM. (Bucharest) 66 No