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. 2019 Sep 4;29(3):379–385. doi: 10.1007/s10068-019-00667-9

Optimizing extraction conditions for functional compounds from ginger (Zingiber officinale Roscoe) using response surface methodology

Jaeyoon Cha 1, Chong-Tai Kim 2, Yong-Jin Cho 3,✉
PMCID: PMC7105539  PMID: 32257521

Abstract

Extraction process was optimized for maximizing the contents of functional compounds from ginger using response surface methodology which applied Box–Behnken design. Ginger extracts were obtained at 3 levels of ethanol concentration (0–70%) of solvent, extraction time (30–90 min), and extraction temperature (50–70 °C) as independent variables. The 6-shogaol and 6-gingerol of the extracts were analyzed through HPLC. The significance of each term in polynomial regression equations was evaluated on functional compound contents and extraction yield in extraction process. It was verified that the regression equations were accurate with high determination coefficients over 0.892. The optimum ethanol concentration, extraction time, and extraction temperature for extraction yield were determined as 41.38%, 78.16 min, and 70 °C, respectively. The functional compound contents predicted at optimal conditions were as follows: 39.55 mg/g at 70%, 70 min, and 70 °C for 6-gingerol, 2.44 mg/g at 70%, 51.90 min, and 62.29 °C for 6-shogaol.

Keywords: Extraction, Ginger, Optimization, Response surface methodology, Regression equation

Introduction

With the economic growth and increasing average national income, interest in securing safe food as well as in health and food in general has been growing rapidly. Researchers have focused on the search for active substances derived from natural products which have useful physiological activities without side effects. In particular, the studies on antimicrobial, anti-aging, adult disease prevention, immunity enhancement, and antioxidative effects are actively conducted on natural plant resources (Chaovanalikit and Wrolstad, 2004; Choi et al., 2002).

Ginger, the rhizome of Zingiber officinale Roscoe, has been consumed as not only a spice and dietary supplement but also medicine for asthma, cough, diabetes, stroke, rheumatism, and stroke (Feng et al., 2011). Although ginger has a few insignificant side effects and interacts with some medications, Food and Drug Administration (FDA) recognizes as a safe herbal medicine (Bilehal et al., 2011). In addition, it has been used as a common additive in food and medicine because of pungent components like gingerol-related components (Bartley and Jacobs, 2000; Pawar et al., 2011). The 6-gingerol was the most pungent among the main pungent components such as 6-gingerol, 8-gingerol, and 10-gingerol (Govindarajan, 1982). Lee and Ahn (1985) reported that 6-gingerol exhibited anti-inflammatory, antiseptic, and antioxidant activities. It has been reported that oleoresin, gingerol, and shogaol activated natural killer cells to enhance the effect of immunity in studies related to the immunity effects of ginger (Zakaria-Runkat et al., 2003; McCarthey et al., 1993). The 6-shogaol and 6-gingerol were analyzed as functional compounds from ginger in this study.

Extraction is the decisive process for recovering and purifying functional compounds from medicinal plants (Shouqin et al., 2007). Some extraction methods such as cold extraction, heat reflux extraction, soxhlet extraction, and extractions using ultrasound and microwave have been used. These methods need a suitable agitation, power, and solvent to increase the solubility and mass transfer rate (Prasad et al., 2009). The antioxidant activity and extraction yields of the materials are changed depending on the extraction solvent because of the different antioxidant compounds with various polarities and chemical properties (Peschel et al., 2006). A lot of studies have been carried out to optimize the extraction conditions of functional or bioactive components using response surface methodology (Cha et al., 2019; Chuyen et al., 2017; Kadam et al., 2015; Guglielmetti et al., 2017; Yan et al., 2015). Response surface methodology (RSM) was designed to identify the multiple effects of independent variables and their interactions on dependent variables (Box and Wilson, 1951). Although fewer experimental runs are conducted in RSM than in full factorial design, statistically acceptable results can still be provided. The RSM for optimization design is applied so as to reduce high cost and numerical noise of analysis methods (Tan et al., 2009). Aydar (2018) summarized RSM application used to optimize extraction process of plant materials.

In this study, the ethanol concentration, extraction time, and extraction temperature were optimized for extraction yield and functional compound contents from ginger. The specific objectives were to identify the effects of extraction conditions for 6-gingerol and 6-shogaol contents and extraction yield and to develop the regression equations to predict the functional compound contents and extraction yield using RSM.

Materials and methods

Materials

The dried ginger (Zingiber officinale Roscoe) was cultivated in Korea and provided from Cheonho Bio Co. (Seoul, Korea). The reagents were purchased from Sigma (Sigma Aldrich Co., St. Louis, Mo., USA) as standard products of 6-gingerol and 6-shogaol, which were used for functional compound analysis.

Proximate composition

According to AOAC (1995), moisture content was analyzed by drying method at 105 °C, crude fat by Soxhlet method, and ash by ash incineration at 550 °C. The crude protein content of the sample was then measured using a Tecator digestion system (2006 digestor, Foss, Denmark) and Kjeltec auto sampler system (1035 analyzer, Foss, Denmark). The amount of carbohydrate was calculated by deduction of the amounts of ash, crude fat, crude protein, and moisture from 100.

Extraction process

The dried ginger was extracted to determine the optimal extraction conditions by using a reflux cooling extraction system (HMO-F300, Hana Instrument, Seoul, Korea) shown in Fig. 1. After the addition of 4 L of distilled water (w/v) to the 150 g of dried ginger flake, the extracts were obtained in 13 different combinations with 3 different levels of ethanol concentration (%) of solvent, extraction time, and extraction temperature (°C) according to experiment design. After the extracts were centrifuged at 4 °C and 11,000×g for 5 min, they were filtered through a filter paper (Watman No. 4, Maidstone, England). The filtrate was vaporized in a rotary vacuum evaporator at 40 °C. The residue was lyophilized and used as the analysis sample.

Fig. 1.

Fig. 1

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The schematic diagram of the reflux cooling extraction system

Determination of functional compound contents and extraction yield by HPLC

The extraction yield was determined by dividing the weight of lyophilized extract by that of dried sample. Lyophilized ginger extract was dissolved in methanol to a concentration of 500 mg/mL, then sonicated for 30 min for complete mixing and liberation of phenolic compounds with some modification by Zhan et al. (2011) and Pawar et al. (2011). The extract was used for functional compound analysis after filtering through a 0.45 µm PVDF syringe filter. The standard product of 6-gingerol was dissolved in methanol to a concentration of 1 mg/mL and diluted to 200, 400, 600, and 800 µg/mL. The diluted solution was filtered through a 0.45 µm PVDF syringe filter, and then used for analysis. In the case of 6-shogaol, the methanol solution of 1 mg/mL concentration was diluted to 20, 40, 60, 80, and 100 µg/mL. Prior to being used for the analysis, the diluted solution of 6-shogaol was filtered using the same method as that of 6-gingerol. (Baranowski 1985) reported that the best method for the direct analysis of gingerols and shogaols was HPLC analysis equipped with a reversed-phase column. As functional compounds for ginger, 6-gingerol and 6-shogaol were analyzed using HPLC (Agilent Technologies 1260 infinity, USA). The used column was ZORBAX Eclipse XDB-C18 (250 mm × 4 mm, 5 µm, Agilent Technologies, USA), while water (A) and acetonitrile (B) were used as mobile phases. The gradient program for the HPLC was as follows: 65% B for 0–12 min, 60–80% B for 12–18 min, 80% B for 18–25 min, 45% B for 25–30 min, and 65% B for 30–40 min, with a flow rate of 1 mL/min. The injection volume was 20 µL at the column temperature of 25 °C. They were detected at 225 nm.

Statistical analysis

The experimental results in Table 1 were analyzed using SPSS program (IBM SPSS 22 for windows, SPSS INC., Chicago, IL, USA). Data was analyzed by ANOVA and Duncan’s multiple range test, which was used to resolve the difference among treatment means. A value of p < 0.05 was used to indicate significant difference.

Table 1.

The response of extraction yield and 6-shogaol and 6-gingerol contents from ginger by extraction process applied Box-Behnken design

Run no. Independent variables Dependent variables
Coded values Uncoded values
X1 X2 X3 X1 X2 X3 Y1 Y2 Y3
1 − 1 − 1 0 50 30 35 12.41d 11.20d 0.97b
2 1 − 1 0 70 30 35 11.54cd 27.60h 1.39c
3 − 1 1 0 50 90 35 11.42c 16.42f 1.05b
4 1 − 1 0 70 90 35 14.94h 30.68i 1.47c
5 − 1 1 − 1 50 60 0 13.06ef 4.12a 0.31a
6 1 1 − 1 70 60 0 13.75f 14.09e 0.53ab
7 − 1 0 1 50 60 70 10.12a 22.22g 1.58c
8 1 0 1 70 60 70 12.98e 35.17j 2.06d
9 0 − 1 − 1 60 30 0 12.49d 5.17b 0.35a
10 0 1 − 1 60 90 0 10.54ab 6.95c 0.35a
11 0 − 1 1 60 30 70 10.76b 27.78h 2.57e
12 0 1 1 60 90 70 11.79c 33.15ih 2.43e
13 0 0 0 60 60 35 14.04f 21.15g 1.67c
14 0 0 0 60 60 35 13.41f 20.88g 1.75c
15 0 0 0 60 60 35 13.69f 21.00g 1.68c
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X1 extraction temperature (°C), X2 extraction time (min), X3 ethanol concentration of solvent (%), Y1 extraction yield (%), Y2 content of 6-gingerol (mg/g), Y3 content of 6-shogaol (mg/g), Means with different character superscripts in each column are significantly different (p < 0.05)

Results and discussion

The contents of carbohydrate, crude ash, crude fat, crude protein, and moisture of ginger used in this study were 72.74%, 6.81%, 3.46%, 10.52%, and 6.73%, respectively. The general components of the ginger used in this study were mostly composed of carbohydrates in a similar composition to common ginger.

Effect of extraction conditions on extraction yield

As shown in Table 1, the extraction yield (Y1) of the ginger extract ranged from 10.12 to 14.94%. The highest extraction yield was obtained at 70 °C for 90 min using the solvent with 35% ethanol concentration, and the lowest one was obtained at 50 °C for 60 min using the solvent with 70% ethanol concentration. The extraction yield decreased at 50 and 70 °C for 60 min as ethanol concentration of solvent increased from 0 to 70%, whereas it increased at 60 °C for 90 min (Table 1). Kim et al. (1993) reported that the extraction yield of cinnamon extract increased up to 70% of ethanol concentration, then decreased as with ethanol concentration increased. Although it was not significantly different at the extraction conditions of 30 min and 35% (run 1 and 2) and 60 min and 0% (run 5 and 6) with the increase of extraction temperature from 50 to 70 °C (p > 0.05), it significantly increased at the condition of 90 min and 35% (run 3 and 4) and 60 min and 70% (run 7 and 8) (p < 0.05). The change of extraction yield was not constant with increasing extraction time at the same extraction condition of ethanol concentration and extraction temperature. Among the first-order terms in the regression equation for extraction yield, the p value of extraction time was the highest at 0.526 (Table 3). As a result, it was considered that extraction time did not affect the extraction yield.

Table 3.

Polynomial regression equations of extraction yield and 6-gingerol and 6-shogaol contents from ginger

Response Polynomial regression equation R2 p value
Extraction yield (%) Y1 = 13.7133 + 0.7750X1 − 1.1092X22 − 1.2092X23 + 1.0975X1X2 0.862 0.034
Content of 6-gingerol (mg/g) Y2 = 21.010 + 6.6975X1 + 1.9312X2 + 10.9987X3 − 2.6613X23 0.982 0.000
Content of 6-shogaol (mg/g) Y3 = 1.7000 + 0.8875X3 − 0.3925X21 0.955 0.005
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X1 extraction temperature (°C), X2 extraction time (min), X3 ethanol concentration of solvent (%), Y1 extraction yield (%), Y2 content of 6-gingerol (mg/g), Y3 content of 6-shogaol (mg/g)

Effect of extraction conditions on the functional compounds content

The contents of 6-shogaol and 6-gingerol at different extraction conditions are shown in Table 1. The highest content of 6-gingerol was 35.17 mg/g extracted at 70 °C for 60 min using the solvent with 70% ethanol concentration, and the lowest content was 4.12 mg/g at 50 °C for 60 min using water. The content of 6-gingerol significantly increased at the same ethanol concentration and extraction time (run 1 and 2, 3 and 4, 5 and 6) with increasing extraction temperature from 50 to 70 °C (p < 0.05). It also significantly increased at the same ethanol content and extraction temperature (run 1 and 3, 2 and 4) with the increase of extraction time from 30 to 90 min (p < 0.05). Dent et al. (2013) reported that the phenolic content increased with increasing extraction time using a 70% solution of acetone, ethanol, and water with maximum values at 90 min. The content of 6-gingerol significantly increased at the same extraction time and temperature (run 5–12) with the increase of ethanol concentration of solvent from 0 to 70% (p < 0.05). From these results, it can be conjectured that each parameter independently affected the content of 6-gingerol. The highest content of 6-shogaol was 2.57 mg/g extracted at 60 °C for 30 min using the solvent with 70% ethanol concentration, and the lowest content was 0.31 mg/g at 50 °C for 60 min using water (Table 1). The content of 6-shogaol significantly increased in the same ethanol concentration and extraction time (run 1 and 2, 3 and 4, 5 and 6) with increasing extraction temperature from 50 to 70 °C (p < 0.05). The content of 6-shogaol significantly increased at the same extraction time and extraction temperature (run 5–12) with increasing ethanol concentration of solvent from 0 to 70% (p < 0.05). From these results, it can be guessed that ethanol concentration and extraction temperature independently affected the content of 6-shogaol.

Regression modeling of extraction condition

The Box–Behnken design (BBD) was applied as an experimental design used to fit the second-order response surface based on the structure of balanced incomplete block designs. For this experimental design, the ethanol content (X3), extraction time (X2), and extraction temperature (X1), which affected the extraction process, were encoded as the independent variables. The extraction conditions were determined by considering the results from preliminary experiments with each independent variable, extraction temperature (40–100 °C), extraction time (30–120 min), and ethanol concentration (0–90%), respectively. The extraction yield of ginger was a little increased and then, decreased from 60 °C as with extraction temperature increased. The response variables were the contents of 6-gingerol and 6-shogaol and extraction yield. The BBD applied in this study was composed of 12 different combinations of the independent variables (1 to 12) and 3 central points (13 to 15). All experiments were conducted with three replications. For regression analysis, mean values were used to identify mathematical relationship between independent variables and response variables. MiniTab (MiniTab 16, Minitab Inc., State College, PA) was used to perform RSM. The significance of each term in polynomial regression equations was statistically evaluated at the significant level, α = 0.05. The dependent (Yn) and independent variables (Yn) are shown in polynomial regression equation below, and bn are the fixed constant and regression coefficients of the equation.

Y=b0+b1X1+b2X2+b3X3+b11X12+b22X22+b33X32+b12X1X2+b13X1X3+b23X2X3

Table 2 shows the p-value of each term in the regression equations, which indicates the significance of each term to the model.

Table 2.

p value of each parameter in the polynomial regression equations of extraction yield and 6-gingerol and 6-shogaol contents from ginger

Parameter p value of each parameter in polynomial regression equations
Y1 Y2 Y3
Constant 0.000 0.000 0.000
X1 0.036 0.000 0.076
X2 0.526 0.039 0.978
X3 0.114 0.000 0.000
X21 0.950 0.613 0.027
X22 0.040 0.936 0.522
X23 0.030 0.048 0.200
X1X2 0.036 0.609 1.000
X1X3 0.220 0.482 0.618
X2X3 0.112 0.403 0.786
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X1 extraction temperature (°C), X2 extraction time (min), X3 ethanol concentration of solvent (%), Y1 extraction yield (%), Y2 content of 6-gingerol (mg/g), Y3 content of 6-shogaol (mg/g)

For extraction yield, the first-order term of extraction temperature was significant at p value 0.036, whereas those of ethanol concentration and extraction time were not significant at p values 0.114 and 0.525, respectively (p > 0.05). However, the significance of quadratic terms was in opposition to the first-order terms (p < 0.05). The first-order terms of ethanol concentration and extraction time and their reciprocal terms were not significant (p > 0.05) (Table 2). The coefficient of determination (R2), which indicates the general validity and accuracy of the polynomial regression equation, was 0.862 (Table 3). The p value was 0.034 in the result of the error analysis, which indicated a significant regression relationship (p < 0.05).

For 6-gingerol content, the first-order terms and the quadratic term of ethanol concentration in the regression equation were significantly affected to the content of 6-gingerol, whereas the other quadratic terms and reciprocal terms were not (p < 0.05). The p values of ethanol concentration and extraction temperature were 0.000 (Table 2), which indicate a great importance for 6-gingerol content. The regression equation to predict 6-gingerol content is shown in Table 3. It is considered that this equation fit well due to high determination coefficient of 0.982 (Table 3). The p value was 0.000 in the result of error analysis, which indicated a significant relationship.

For 6-shogaol content, the significance in the first-order term of ethanol concentration and the quadratic term of extraction temperature was indicated for this equation, whereas that in the other terms was not statistically indicated (p < 0.05). The p value of ethanol concentration was 0.000 (Table 2), which explains that this term was the most important in the regression equation for 6-shogaol content. The regression equation for 6-shogaol content in the sample extracted at different conditions is shown in Table 3. The determination coefficient of 0.955 indicated that this equation fit well. The p value of 0.005 was in the result of error analysis, which indicated a significant relationship.

Therefore, these responses are thoroughly explained by these regression equations. It is also reasonable to predict the effects of extraction conditions on extraction yield and 6-gingerol and 6-shogaol contents and extraction yield from ginger.

Optimal extraction condition using RSM

The optimal ethanol concentration of solvent, extraction time, and extraction temperature were determined by polynomial regression equations using MiniTab. Figure 2 shows optimum values and interaction between the variables which were analyzed and expressed as a three-dimensional surface response graph. Extraction yield (Y1) increased as extraction temperature increased in the range of this study, while it increased up to 78.16 min of extraction time and 41.38% of ethanol concentration and thereafter decreased with the increase of ethanol concentration and extraction time. Kim et al. (2014) reported that the extraction yield of kirenol stayed constant below 60% of ethanol concentration, while it decreased 13.5 times with an increase in ethanol concentration from 60 to 100%. Durling et al. (2007) reported that a high extraction yield of phenolics extracted from Salvia officinal was obtained using 55-75% ethanol concentration of solvent. In high hydrostatic pressure extraction for propolis, a high extraction yield was obtained at 75% ethanol concentration (Zhang et al., 2005). For the highest extraction yield using RSM, the optimal ethanol concentration, extraction time, and extraction temperature were determined as 41.38%, 78.16 min, and 70 °C, respectively. For 6-gingerol (Y2), its content increased with increasing ethanol concentration, extraction time, and extraction temperature in the range of this study. The optimum conditions using the regression equation were 70 °C, 90 min, and 70%. Dvorackova et al. (2015) reported that the most efficient ethanol concentration of solvent was 60% for phenolic compounds in the classic extraction of cinnamon. The content of 6-shogaol (Y3) increased with increasing ethanol concentration in the range of this study. As extraction temperature and time increase up to 62.29 °C and 51.90 min, the content of 6-shogaol tended to increase and then decreased after that. The optimum ethanol concentration, extraction time, and extraction temperature using the regression equations were determined as 62.29 °C, 51.90 min, and 70%, respectively.

Fig. 2.

Fig. 2

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Response surface plots for the effects of the extraction temperature (°C, X1), extraction time (min, X2), and ethanol concentration of solvent (%, X3) on the extraction yield (%, Y1) and the contents of 6-gingerol (mg/g, Y2) and 6-shogaol (mg/g, Y3) from ginger by extraction process

The experiment at the optimal conditions was conducted to validate the regression model for predicting the response value. The experimental and predicted values for extraction yield were 16.10 ± 1.2 and 14.88%, respectively. The experimental and predicted values for 6-gingerol content were 41.58 ± 2.7 and 39.55 mg/g, respectively. Those values for 6-shogaol content were 2.63 ± 0.5 and 2.44 mg/g in this optimal extraction condition. The experimental values were good agreed with the predicted values using regression models obtained by RSM. Therefore, it is considered that the model could accurately predict the response.

Acknowledgements

This research was supported by the research grant of the Ministry for Agriculture, Food and Rural Affairs for the 2016 joint research and development of industry-academy-research cooperation technology. This support is appreciated.

Footnotes

Publisher's Note

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Contributor Information

Jaeyoon Cha, Email: chajaeyoon@dau.ac.kr.

Chong-Tai Kim, Email: ctkim@ieasthill.com.

Yong-Jin Cho, Email: yjcho@kfri.re.kr.

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