Optimization of Supercritical Carbon Dioxide Extraction of Phenolic Compounds from Mango Ginger Rhizome (<i>Curcuma Amada</i> Roxb.) Using Response Surface Methodology

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2.4. Phenolic acid analysis
2.4.1. Determination of Total Phenolic Content (TPC)

Total phenolic content of SCF-MG extracts were measured according to Folin-Dennis method ^[16]. 200 µg of SCF-MG extract was dissolved in 500 µl of methanol and the sample was incubated with 2.5 ml of 10% Folin and Ciocalteu’s (FC) phenol reagent for 2 min at room temperature. To this 2 ml of 7.5% Na₂CO₃ was added and incubated for 1 hr at ambient temperature. The absorbance was measured at 765 nm against a blank developed with 0.5 ml solvent using a Shimadzu UV-Visible spectrophotometer and gallic acid was used as standard. Total phenolic content in the extract was expressed as gallic acid equivalents (GAE).

2.4.2. High Performance Liquid Chromatography for Phenolic Acids

The bioactive phenolic acids of Mango ginger SCF extracts were analyzed by HPLC (model LC-10A, Shimadzu Corp.) on a reversed phase Shimpak C₁₈ column (4.6 x 250 mm, Shimadzu Corp.) using a diode array UV detector (operating at λ_max ) 280 nm). The mobile phase was composed of water/acetic acid/methanol (80: 5: 15 v/v/v). The isocratic chromatography was run at flow rate of 1 mL/min. Phenolic acid standards such as caffeic, coumaric, cinnamic, ferulic, gallic, gentisic, protocatechuic, syringic, and vanillic acids were employed for the identification of phenolic acids present in SCF-Mango ginger by comparing the retention time under similar experimental conditions ^[17].

2.5. Design of Experiments

The effect of the operating variables on the extraction yield and total phenolic content was studied using Box–Behnken design of response surface methodology. The experimental design used to investigate the effect of the factors were pressure (X1), temperature (X2) and time (X3) with three levels for each variable, while the dependent variable was the extract yield (Y) or Total Phenolic Content (TPC). Codes and levels of independent variables of Pressure, temperature and time in RSM design were given in Table 1.The predicted values of total extract yield were calculated during regression model and compared with the experimental values. A second order quadratic polynomial equation was used as the regression model for each response (Eq. 1)

(1)

Where Y is the predicted extract yield or TPC, A₀ is the intercept, X represents the independent variable (pressure, temperature and time) and A₁-A₃ are linear coefficients, A₄-A₆ are quadratic coefficients, A₇-A₉ are interaction coefficients and ε random error respectively. Coefficients for the above equation and Analysis of variance (ANOVA) were determined by employing Microsoft Excel data analysis tool. Three-dimensional response contour plots were obtained using the Kyplot software version 2.0 beta by varying any two of the variables and maintaining the other variable at + 1 coded value. Search for optimum yield within the range of variables was carried using SOLVER function of the MS-Excel-2010®software ^{[7, 18]}.

Table 1. Codes and levels of independent variables of pressure, temperature and time in RSM design

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3. Result and Discussion

3.1. Effect of Pressure, Temperature and Time on the Extraction Yield and Total Phenolic Content

The solvating power of the supercritical fluid varies significantly as the variation in the applied temperature and pressure. Because density is the function of pressure and temperature, as the density increases the fluid behaves like a liquid and solubility will enhance. Depending upon the pressure and temperature, the yield of extract increased with increasing in CO2 mass and time. At constant temperature, the yield of extract increased with the increase in pressure. This happens due to increase in density of CO2 and intermolecular physical interactions with increasing pressure at constant temperature. At constant pressure, the yield decreases with increase in temperature because of decrease in the solvent density. This trend was followed at tower pressures. However, despite of the increase in temperature the yield of the extract increased at higher pressure (350 bar) due to increase in the vapor pressure of the active components in the extract. An increase in temperature could accelerate the mass transfer of solute in the matrix and/or from the matrix to the solvent thus increasing the extraction yield ^[19].

Phenolic content was calculated from Spectrometric method (FC method) and expressed in Gallic acid equivalents per total extract obtained at the specific extraction condition. Amount of phenolic content in the extract also follow the same pattern of the extraction yield with changing in the process parameters. In the present investigation the solute vapor pressure dominates solvent density. Similar results were noticed when extraction time was kept constant. As temperature increased, TPC decreased at pressure less than 250 bar and above 250 bar the trend reverses.

3.2. Statistical Analysis

Table 2. Regression Statistics of the response surface model

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All 15 of the designed experiments were conducted according to the Box-Bhenken design and the results were analyzed by multiple regression analysis using Microsoft office excel 2010 data analysis tool pack. Two responses were considered i.e yield and total phenolic content. The regression equation includes liear, quadratic and polynomial terms. The Box-Behnken design showed that polynomial regression models were in good agreement with the experimental results. The model was built based on the variables with confidence levels of 95%. The regression statistics and analysis of variance (ANOVA) for yield and total phenolic content reported in Table 2-Table 4. Indicates that the model is highly significant, which is evident from the high Fisher (F) ratio value. The coefficients of correlation (R) 0.927 and 0.93 for TPC and yield respectively indicates a high degree of correlation between observed and predicted values (Figure 2) thus indicating adequacy of the fitted models. Figure 3a-b show the effect of P, T and time on the total phenolic content, at constant temperature and as the pressure increases there is increase in the TPC (Table 5).

Table 3. Analysis of variance for yield and TPC

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Table 4. Regression coefficient of polynomial functions of response surface of total extract yield and total phenolic content

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Table 5. Experimental and predicted data for the yields and TPC obtained from Box–Behnken design

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Figure 2. Plot of experimental values vs model predicted values (a) TPC, (b) Yield %

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Figure 3. (a) Effect of temperature and pressure on TPC, (b) Effect of pressure and time on TPC, (c) Effect of temperature and time on TPC

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The coefficients of the response surface model as provided by Eq. 1 were evaluated. The final predictive equation obtained was as given in Eq. 2 and Eq. 3

(2)

(3)

The effect of pressure, temperature and extraction time on yield are also shown in response plots (Figure 4a-b). In the present study the effect of linear terms is not significant as p > 0.05, but there is significant effect of interaction between pressure and temperature which increases the yield and total phenolic content (p < 0.05). The highest extraction yield of extract and total phenolic content obtained at 350 bar, 60°C and 15 hr was 2.83% and 154 mg GAE/tot extract which was well matched with the predicted yield. At lower pressure the yield of phenolic content is less due to the solubility of phenolic acid are less at the less density of CO2. At higher pressure yield increases significantly.

Figure 4. (a) Effect of pressure and time on yield of extract, (b) Effect of temperature and time on yield of extract, (c) Effect of temperature and pressure on yield of extract

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Figure 5. HPLC chromatogram of SC-CO₂ extract of Mango ginger at optimum conditions

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