- Email: [email protected]
Optimization of extraction process by response surface methodology and preliminary structural analysis of polysaccharides from defatted peanut (Arachis hypogaea) cakes
Carbohydrate Research 346 (2011) 305–310
Contents lists available at ScienceDirect
Carbohydrate Research journal homepage: www.elsevier.com/locate/carres
Optimization of extraction process by response surface methodology and preliminary structural analysis of polysaccharides from defatted peanut (Arachis hypogaea) cakes Yi Song a,b,c, Bingjian Du a,b,c, Ting Zhou a, Bing Han a,b,c, Fei Yu a,b,c, Rui Yang a,b,c, Xiaosong Hu a,b,c, Yuanying Ni a,b,c, Quanhong Li a,b,c,⇑ a b c
College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China Key Laboratory of Fruit and Vegetable Processing, Ministry of Agriculture, China Engineering Research Center for Fruit and Vegetable Processing, Ministry of Education, Beijing 100083, China
a r t i c l e
i n f o
Article history: Received 13 September 2010 Received in revised form 16 November 2010 Accepted 17 November 2010 Available online 21 November 2010 Keywords: Defatted peanut cake Polysaccharide Response surface methodology Preliminary structural analysis
a b s t r a c t In this work, response surface methodology was used to determine optimum conditions for extraction of polysaccharides from defatted peanut cake. A central composite design including independent variables, such as extraction temperature (x1), extraction time (x2), and ethanol concentration (x3) was used. Selected response which evaluates the extraction process was polysaccharide yield, and the second-order model obtained for polysaccharide yield revealed coefficient of determination of 97.81%. The independent variable with the largest effect on response was ethanol concentration (x3). The optimum extraction conditions were found to be extraction temperature 48.7 °C, extraction time 1.52 h, and ethanol concentration of 61.9% (v/v), respectively. Under these conditions, the extraction efficiency of polysaccharide can increase to 25.89%. The results of structural analysis showed that the main composition of defatted peanut cake polysaccharide was a-galactose. Ó 2010 Elsevier Ltd. All rights reserved.
1. Introduction Response surface methodology (RSM) is an alternate strategy involving statistical approach compared to OVAT (one variable at a time), which could represent the effect of interaction between different factors. The main advantages of RSM are the reduced numbers of experimental trials needed to evaluate multiple parameters and their interactions1–3 and it is useful for developing, improving, and optimizing process. RSM has been largely used for optimizing the media for citric acid production4 and extraction of protein from red pepper seed.5 This methodology could be used in developing suitable treatment technology considering the effects of operational conditions on the removal process or to determine a region that satisfies the operating specifications.6,7 The positive health benefits associated with the regular consumption of tree nuts and peanuts are well established.8,9 Peanuts (Arachis hypogaea), in addition to having healthy fatty acid profiles and being good sources of fiber and protein, contain a number of components which are capable of directly scavenging free radicals. Examples include various polyphenols, tocopherols, and flavo⇑ Corresponding author. Address: College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China. Tel.: +86 10 62738831; fax: +86 10 62737761. E-mail address: [email protected] (Q. Li). 0008-6215/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.carres.2010.11.019
noids.8 However, studies focused on the bioactivity of peanut cakes are still limited. Defatted peanut cakes, considered as residual oil contents, are commercially available protein, oligo/polysaccharide, low fat ingredients prepared from peanut seed after squeezing. Recent researches have focused on characterizing the functional ingredients and properties of these residues including rheological properties, hypoglycemic capacity, water holding capacity, etc.10 In the present study, RSM was employed to optimize the polysaccharide extraction process from defatted peanut cakes for maximum yield. The parameters were temperature, extraction time, and ethanol concentration. The preliminary structural information of the polysaccharide was also investigated. 2. Materials and methods 2.1. Materials Defatted peanut cakes (100 g) were pulverized to pass through a 1 mm sieve in an electric mill. The flour was packed in polyethylene bags and stored at room temperature until use. 2.2. Extraction of crude polysaccharides Defatted peanut cake meal was extracted with selected 20 combinations of independent variables, such as temperature
306
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310
(30–70 °C), extraction time (0.5–2.5 h), and ethanol concentration (40–80%). The peanut cakes were crushed using the beater. Then the meal was mixed with distilled water at the rate of 1 g peanut cake meal per 30 mL water and stayed in water bath. The supernatants were mixed, concentrated to a quarter of the original volume by evaporation. After cooling, the proteins in the extract were removed by the Sevag reagent. Then the crude peanut cake polysaccharide mixtures were precipitated by the addition of ethanol and then precipitated at 4 °C for 6 h. After centrifuged at 3000 rpmg for 20 min, the resulting supernatants were collected and lyophilized. Then the crude defatted peanut cake polysaccharide (termed DPCP) was obtained. The content of crude polysaccharide was determined by the phenol–sulfuric acid method,11 and the yield of DPCP was expressed as g DPCP/g peanut meal 100%. All the experiments were carried out in duplicate. 2.3. Experimental design and statistical analysis Response surface methodology was used to determine the influence of three independent variables and the optimum conditions of crude polysaccharide isolation. The process variables and the responses were defined from published data.12,13 The effects of the variables temperature (x1), extraction time (x2), and ethanol concentration (x3) on the crude peanut cake polysaccharide isolation process were investigated. Each variable was coded at five levels: 2, 1, 0, 1, 2 (Table 1). The variables were coded according to the following equation:
xi ¼ ðX i X i Þ=DX i
ð1Þ
where xi is the dimensionless value of an independent variable, X i is the real value of an independent variable, X i is the real value of an independent variable at the center point, DX i is the step change. The response function investigated was Y i ¼ g ethanol soluble sugars from extract/2 g defatted peanut flour. A central composite experimental design (CCD) was arranged to allow for fitting of second-order model14 (Table 2). The CCD combined the vertices of hybercube whose coordinates were given by 2n factorial design (runs 1–8) with the star points (runs 9–14). The star points were added to the factorial design to provide for estimation of curvature of the model. Six replicates at the center point of the design (runs 15–20) were used to allow for estimation of the pure error sum of squares. All experiments were carried out in a randomized order to minimize any effect of extraneous factors on the observed responses. The model proposed for response (Yi) was:
The significance of each coefficient was determined using the Ftest and p-value. The corresponding variables would be more significant if the absolute F-value becomes greater and the p-value becomes smaller.15 2.4. Purification of defatted peanut cake polysaccharides Crude polysaccharides extracted from defatted peanut cakes (DPCP) were extracted by the method mentioned above. Then the DPCP were redissolved in distilled water and applied to a DEAE Sepharose Fast Flow gel column (2.6 100 cm). One milliliter of 1 mg/mL crude DPCP was subjected to the gel column and eluted by filtered (0.45 lm membrane) distilled water and then by 0, 0.2, 0.4, 0.6 M NaCl at a flow rate of 4.0 mL/min. Each fraction with 1 mL of eluate was collected and determined by the phenol–sulfuric acid method. Based on the colorimetric total carbohydrate test using the method mentioned above, the water fraction, appearing as a single peak, was further purified by the gel permeation chromatography on a column of Sephacryl S-300 High Resolution (2.6 100 cm). The main fraction was collected, dialyzed, and then lyophilized to get a white purified pumpkin polysaccharide (DPCP1). Protein content was estimated using Folin–Ciocalteu reagent by Agilent 8453 UV–vis spectrophotometer.16 2.5. Analysis of monosaccharide compositions The polysaccharide samples were hydrolyzed with 2 M trifluoroacetic acid (TFA) at 100 °C for 4 h. The acid was removed by evaporations with MeOH. Then the hydrolysates were converted into their respective alditol acetates, followed by GC analysis, which was performed on a Finnigan Trace GC 2000. The detailed experimental conditions were as follows: injection temperature: 220 °C, detector temperature: 220 °C, column temperature programed from 130 to 180 °C at 5 °C/min, holding for 5 min at 180 °C, then increasing to 220 °C at 5 °C/min and finally holding for 3 min at 220 °C. Nitrogen was used as the carrier gas and maintained at 1.0 mL/min. 2.6. FT-IR spectroscopy Fourier-transform infrared spectra of the polysaccharide were recorded with a Nicolet 6700 FT-IR spectrometer (Madison, WI, USA) using the KBr disk method. 3. Results and discussion
Y i ¼ b0 þ b1 x1 þ b2 x2 þ b3 x3 þ b11 x21 þ b22 x22 þ b33 x23 þ b12 x1 x2 þ b13 x1 x3 þ b23 x2 x3
ð2Þ
where Y i is predicted response, b0 is offset term, b1 , b2 and b3 is linear effect terms, b11 , b22 and b33 are squared effects and b12 , b13 and b23 are interaction effects. Surface plots were generated by assigning constant (zero) values to two of the three variables and solving the fitted equations as a quadratic equation in the remaining one variable.
3.1. Fitting the models Defatted peanut cake flour was extracted for its polysaccharide following 20 combinations of three independent variables (temperature, extraction time, ethanol concentration) (Table 1). The application of RSM yields the following regression equation, which is an empirical relationship between polysaccharide yield and the test variable in coded units, as given in the following equation.
Table 1 Independent variable values of the process and their corresponding levels Independent variable
Temperature (°C) Time (h) Ethanol concentration (%) a
Coded variables levelsa
Symbol Uncodified
Codified
2
1
0
1
2
X1 X2 X3
x1 x2 x3
30 0.5 40
40 1.0 50
50 1.5 60
60 2.0 70
70 2.5 80
Passage from coded variables level to natural variable level is given by the following equations: x1 = (X1 50)/10; x2 = (X2 1.5)/0.5; x3 = (X3 60)/10.
307
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310 Table 2 CCD arrangement, responses, and predicted values for polysaccharide yield Coded variablesa
Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a
Uncoded variables
Polysaccharide yield (Y) (%)
X1
X2
X3
x1
x2
x3
Experimental ðY 0 Þ
Predicted ðY i Þ
Y0 Yi
1 1 1 1 1 1 1 1 2 2 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 0 0 -2 2 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 0 0 0 0 -2 2 0 0 0 0 0 0
40 40 40 40 60 60 60 60 30 70 50 50 50 50 50 50 50 50 50 50
1.0 1.0 2.0 2.0 1.0 1.0 2.0 2.0 1.5 1.5 0.5 2.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5
50 70 50 70 50 70 50 70 60 60 60 60 40 80 60 60 60 60 60 60
15.5 13.6 16.5 13.8 17.8 17.2 18.4 17.6 14.0 12.9 22.5 21.6 11.0 11.8 26.0 26.1 25.6 25.4 26.3 25.8
15.6 13.9 16.0 13.8 16.8 16.7 17.1 15.1 15.1 13.2 22.7 22.9 10.5 13.7 25.8 25.8 25.8 25.8 25.8 25.8
0.001 0.003 0.005 0.000 0.010 0.005 0.013 0.025 0.011 0.003 0.002 0.013 0.005 0.019 0.002 0.003 0.002 0.004 0.005 0.000
X1: temperature, X2: extraction time, X3: ethanol concentration.
Table 3 Fit statistics for Y
Y ¼ 0:250886 þ 0:005875x1 þ 0:000250x2 0:015250x3 0:033307x21 0:011807x22 0:025932x23 0:000250x1 x2 þ 0:004000x2 x3 0:001250x1 x3
ð3Þ
The predicted values of polysaccharide yields were calculated using the regression model and compared with experimental values in Figure 1. The total determination coefficient (R2) was 97.81%, indicating a reasonable fit of the model to the experimental data. Earlier studies have reported values for R2 ranging from 58.5% to 99.03% for Lingzhi (Ganoderma lucidum),17 roots of Codonopsis pilosula,18 Phellinus igniarius,19 Pholiota squarrosa.7 It can be seen that ethanol concentration was the most significant factor (p <0.05). Especially, temperature, extraction time, and ethanol concentration showed significance at quadratic terms (p <0.05). Guo et al.19 reported a similar effect; however, Sun
Mean R2 Adjusted R2 RMSE CV (%)
Master model
Predictive model
18.97 0.9781 0.9583 0.054 5.85
18.90 0.8398 0.9583 0.054 5.87
et al.18 reported that temperature and extraction time influenced polysaccharide extraction significantly (p <0.001). Analysis of variance (ANOVA) of independent variables was given in Table 3. There was a non-significant lack of fit that further validates the model (p >0.05). The coefficient of variation (CV) is the ratio of the standard error of estimate to the mean value of observed response expressed as a percentage. It is a measure of
2 7 .0 0
27
23.25
Yield (%)
Predicted values
2 2 .7 5
1 8 .5 0
19.5
15.75
12
1 4 .2 5 2.50
70.00 2.00
1 0 .0 0
60.00 1.50
Extraction time (h)
1 0 .5 3
1 4 .4 7
1 8 .4 2
2 2 .3 6
2 6 .3 0
50.00 1.00
40.00
Temperature (°C)
0.50 30.00
Actual v alues Figure 1. Comparison between predicted and actual polysaccharide yield.
Figure 2a. Response surface plots showing the effect of temperature (x1) and extraction time (x2) on extraction yield of polysaccharide.
308
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310
reproducibility of the models. The CV of the model was calculated as 5.85%. As a general rule, a model can be considered to reasonably reproducible if its CV is not greater than 10%. 3.2. Optimization of the process The three-dimension surface plots were drawn to illustrate the main and interactive effects of the independent variables on the dependent one. These graphs were obtained by fixing two variables at coded zero levels (Table 2) while varying the remaining two variables and predicting the response variables (polysaccharide yield). Figure 2a shows both temperature (x1) and extraction time (x2) exert a quadratic effect on polysaccharide production. Effect of temperature (x1) and ethanol concentration (x3) on polysaccharide yield is presented in Figure 2b. The results revealed that the increase in ethanol concentration and extraction time extracted
27
Yield (%)
23
19
15
11
higher amount of polysaccharide from peanut cakes. Figure 2c depicts the influence of extraction time (x2) and ethanol concentration (x3). It can be seen as a quadratic effect for both ethanol concentration and extraction time. Optimum extraction conditions were estimated by the desirability method using a Minitab Software. An extraction temperature of 48.7 °C, extraction time of 1.52 h, and ethanol concentration of 61.9% (v/v) were found to be optimal for polysaccharide extraction from peanut cakes. Studies of the extraction of peanut cakes could not be traced, but similar studies using other materials have been reported. Chen et al.17 worked on polysaccharide extraction from Lingzhi (G. lucidum) and found significant effects of extraction temperature and concluded that optimum conditions were: extraction temperature of 95 °C, extraction time of 3 h, and solvent/meal ratio of 12:1 (v/w). Sun et al.18 reported that optimum conditions for polysaccharide extraction from roots of C. pilosula were as follows: extraction temperature 94 °C, solvent/meal ratio of 9:1 (v/w), extraction time 2.5 h, and number of extraction 5. Guo et al.19 studied the extraction of polysaccharide from P. igniarius and concluded that maximum polysaccharide yield was obtained by extracting mycelia powder with a temperature of 70 °C, extraction time of 1.5 h and solvent/meal ratio of 6.2:1 (v/ w). Qiu et al.20 stated that significant effects of pH, extraction time, extraction temperature, and salting-out temperature for pectin from banana peels were found and concluded that optimum extraction were: pH of 1.5, temperature of 85.5 °C, extraction time of 2 h, and salting-out temperature of 70 °C. Canettieri et al.21 determined that H2SO4 concentration of 0.65%, temperature of 157 °C, solvent/meal ratio of 8.6:1 (v/w) and reaction time of 20 min were optimum conditions for extracting monomeric sugars from hemicellulose fraction of Eucalyptus grandis residue. 3.3. Confirmative tests
80.00
70.00 70.00
60.00 60.00
Ethanol concentration (%)
50.00 50.00
40.00
Temperature (°C)
40.00 30.00 Figure 2b. Response surface plots showing the effect of temperature (x1) and ethanol concentration (x3) on extraction yield of polysaccharide.
The suitability of the model equation for predicting the optimum response value was tested using the recommended optimum conditions. When optimum values of independent variables (extraction temperature 48.7 °C, extraction time 1.52 h, and ethanol concentration of 61.9% v/v) were incorporated into the regression equation, 25.82% polysaccharide yield was obtained whereas experiments at optimum conditions gave a polysaccharide yield of 25.89%. Thus, predicted values from fitted equations and observed values were in very good agreement. 3.4. Preliminary structural analysis
27
Yield (%)
23
19
15
11
80.00
2.50 70.00
2.00 60.00
Ethanol concentration (%)
1.50 50.00
1.00
Extraction time (h)
40.00 0.50 Figure 2c. Response surface plots showing the effect of extraction time (x2) and ethanol concentration (x3) on extraction yield of polysaccharide.
The total sugar content of DPCP-1 was estimated 97.1 ± 1.2% by the phenol-sulfuric method. In contrast, the protein content in the aqueous extract only accounts for 1.0 ± 0.3%, which was due to the removal by the Sevag reagents at the step of purification. Sugar compositional analysis of DPCP-1 determined by GC indicated that its main composition was galactose (Fig. 3). The FT-IR spectrum of DPCP-1 is shown in Figure 4. Three strong absorption bands at 1023.23, 1079.12, 1154.09 cm1 in the range of 1200–1000 cm1 indicated that the monosaccharide in DPCP-1 had a pyranose ring.22,23 The broadly-stretched intense at 3368 cm1 was due to the hydroxyl stretching vibration of the polysaccharide, so is the vibration at 2931.21 cm1 which indicated C–H stretching vibration. The relatively strong absorption peak at 1642 cm1 was due to the associated water.23–25 The absorption peak at 1415 cm1 suggested the C–O stretching vibration, and the peak at 1239 cm1 indicated the existence of O–H flexural vibration. The absorption at ca. 840 cm1 revealed that the polysaccharide had aconfigurations in it.26 A band of absorption at 763 cm1 represented symmetrical ring vibration. No absorption at 1730 cm1 indicated that there were no uronic acids.
309
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310 FID1 A, (HXQ\08071601.D)
pA 140 120 100
Galactose-16.687
80 60 40 20 0 0
5
10
15
20
25
30
min
Figure 3. DPPH scavenging activities of the defatted peanut cakes polysaccharide.
Figure 4. Superoxide anion scavenging activities of the defatted peanut cakes polysaccharide.
4. Conclusions RSM was sufficient to describe and predict the extraction process of bioactive compounds from defatted peanut cakes. Polysaccharide was extracted from defatted peanut cakes with 20 selected combinations of temperature, extraction time, and ethanol concentration. The experimental value of polysaccharide yield varied from 11% to 26.3%. The variable with the largest effect was ethanol concentration. An extraction temperature of 48.7 °C, extraction time of 1.52 h, and ethanol concentration of 61.9% (v/v) were found to be optimal for polysaccharide extraction from defatted peanut cakes which could obtain a yield of 25.89%. The main composition of the polysaccharide was agalactose. Further studies on the precise chemical structures and biological functions of the polysaccharide are needed. References 1. Chen, M. J.; Chen, K. N.; Lin, C. W. J. Food Eng. 2005, 68, 471–480. 2. Gunawan, E. R.; Basri, M.; Rahman, B. A. M.; Salleh, A. B.; Rahman, R. N. Z. A. Enzyme Microb. Technol. 2005, 37, 739–744. 3. Jafari, M.; Nateghi, M.; Rabbani, A. Int. J. Biol. Macromol. 2010, 46, 104–108. 4. Lofty, W. A.; Ghanem, K. M.; El-Helow, E. R. Bioresour. Technol. 2007, 98, 3470– 3477. 5. Ebru, F.; Ozgul, E. LWT-Food Sci. Technol. 2010, 43, 226–231.
6. Ravikumar, K.; Pakshirajan, K.; Swaminathan, T.; Balu, K. Chem. Eng. J. 2005, 105, 131–138. 7. Zhao, H. Z.; Wang, J.; Lu, Z. X. Carbohydr. Polym. 2009, 77, 677–680. 8. Isanga, J.; Zhang, G. N. LWT-Food Sci. Technol. 2009, 42, 1132–1138. 9. Talcott, S. T.; Passeretti, S.; Duncan, C. E.; Gorbet, D. W. Food Chem. 2005, 90, 379–388. 10. Davis, J. P.; Dean, L. L.; Price, K. M.; Sanders, T. H. Food Chem. 2010, 119, 539– 547. 11. Dubois, M.; Gilles, K. A.; Hamilton, J. K.; Rebers, P. A.; Smith, F. Anal. Chem. 1956, 28, 350–356. 12. Fu, C. L.; Tian, H. J.; Li, Q. H.; Cai, T. Y.; Du, W. J. Ultrason. Sonochem. 2006, 15, 511–516. 13. Li, Q. H.; Fu, C. L. Food Chem. 2006, 92, 701–706. 14. Nakai, S.; Li-Chen, E. C. Y.; Dou, J. In Handbook of Food and Bioprocess Modeling Techniques; Sablani, S., Datta, A., Rahman, M. S., Mujumdar, A., Eds.; CRC Press: Boca Raton, 2006; Vol. 1, pp 293–323. 15. Atkinson, A. C.; Donev, A. N. Optimum Experimental Designs; Oxford University Press, 1992. pp. 132–189. 16. Lowry, O. H.; Rosebrough, N. J.; Farr, A. L.; Randall, R. J. J. Biol. Chem. 1951, 193, 265–275. 17. Chen, X. P.; Wang, W. X.; Li, S. B.; Xue, J. L.; Fan, L. J.; Sheng, Z. J.; Chen, G. Y. Carbohydr. Polym. 2010, 80, 944–948. 18. Sun, Y. X.; Liu, J. C.; Kennedy, J. F. Carbohydr. Polym. 2010, 80, 949–953. 19. Guo, X.; Zou, X.; Sun, M. Carbohydr. Polym. 2010, 80, 344–349. 20. Qiu, L. P.; Zhao, G. L.; Wu, H.; Jiang, L.; Li, X. F.; Liu, J. J. Carbohydr. Polym. 2010, 80, 326–331. 21. Canettieri, E. V.; Rocha, G. J.; Carvalho, J. A., Jr.; Silva, J. B. Bioresour. Technol. 2007, 98, 422–428. 22. Kacˇuráková, M.; Capek, P.; Sasinková, V.; Wellner, N.; Ebringerová, A. Carbohydr. Polym. 2000, 43, 195–203.
310
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310
23. Ye, L. B.; Zhang, J. S.; Yang, Y.; Zhou, S.; Liu, F. Y.; Tang, Q. J., et al Food Chem. 2009, 112, 962–966. 24. Park, F. S. Application of I.R. Spectroscopy in Biochemistry, Biology and Medicine; Plenum: New York, 1971. pp. 100–140.
25. Cao, W.; Li, X. Q.; Liu, L.; Wang, M. C.; Fan, H. T.; Li, C., et al Carbohydr. Res. 2006, 341, 1870–1877. 26. Barker, S. A.; Bourne, E. J.; Stacey, M.; Whiffen, D. H. J. Chem. Soc. 1954, 171– 176.
Contents lists available at ScienceDirect
Carbohydrate Research journal homepage: www.elsevier.com/locate/carres
Optimization of extraction process by response surface methodology and preliminary structural analysis of polysaccharides from defatted peanut (Arachis hypogaea) cakes Yi Song a,b,c, Bingjian Du a,b,c, Ting Zhou a, Bing Han a,b,c, Fei Yu a,b,c, Rui Yang a,b,c, Xiaosong Hu a,b,c, Yuanying Ni a,b,c, Quanhong Li a,b,c,⇑ a b c
College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China Key Laboratory of Fruit and Vegetable Processing, Ministry of Agriculture, China Engineering Research Center for Fruit and Vegetable Processing, Ministry of Education, Beijing 100083, China
a r t i c l e
i n f o
Article history: Received 13 September 2010 Received in revised form 16 November 2010 Accepted 17 November 2010 Available online 21 November 2010 Keywords: Defatted peanut cake Polysaccharide Response surface methodology Preliminary structural analysis
a b s t r a c t In this work, response surface methodology was used to determine optimum conditions for extraction of polysaccharides from defatted peanut cake. A central composite design including independent variables, such as extraction temperature (x1), extraction time (x2), and ethanol concentration (x3) was used. Selected response which evaluates the extraction process was polysaccharide yield, and the second-order model obtained for polysaccharide yield revealed coefficient of determination of 97.81%. The independent variable with the largest effect on response was ethanol concentration (x3). The optimum extraction conditions were found to be extraction temperature 48.7 °C, extraction time 1.52 h, and ethanol concentration of 61.9% (v/v), respectively. Under these conditions, the extraction efficiency of polysaccharide can increase to 25.89%. The results of structural analysis showed that the main composition of defatted peanut cake polysaccharide was a-galactose. Ó 2010 Elsevier Ltd. All rights reserved.
1. Introduction Response surface methodology (RSM) is an alternate strategy involving statistical approach compared to OVAT (one variable at a time), which could represent the effect of interaction between different factors. The main advantages of RSM are the reduced numbers of experimental trials needed to evaluate multiple parameters and their interactions1–3 and it is useful for developing, improving, and optimizing process. RSM has been largely used for optimizing the media for citric acid production4 and extraction of protein from red pepper seed.5 This methodology could be used in developing suitable treatment technology considering the effects of operational conditions on the removal process or to determine a region that satisfies the operating specifications.6,7 The positive health benefits associated with the regular consumption of tree nuts and peanuts are well established.8,9 Peanuts (Arachis hypogaea), in addition to having healthy fatty acid profiles and being good sources of fiber and protein, contain a number of components which are capable of directly scavenging free radicals. Examples include various polyphenols, tocopherols, and flavo⇑ Corresponding author. Address: College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China. Tel.: +86 10 62738831; fax: +86 10 62737761. E-mail address: [email protected] (Q. Li). 0008-6215/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.carres.2010.11.019
noids.8 However, studies focused on the bioactivity of peanut cakes are still limited. Defatted peanut cakes, considered as residual oil contents, are commercially available protein, oligo/polysaccharide, low fat ingredients prepared from peanut seed after squeezing. Recent researches have focused on characterizing the functional ingredients and properties of these residues including rheological properties, hypoglycemic capacity, water holding capacity, etc.10 In the present study, RSM was employed to optimize the polysaccharide extraction process from defatted peanut cakes for maximum yield. The parameters were temperature, extraction time, and ethanol concentration. The preliminary structural information of the polysaccharide was also investigated. 2. Materials and methods 2.1. Materials Defatted peanut cakes (100 g) were pulverized to pass through a 1 mm sieve in an electric mill. The flour was packed in polyethylene bags and stored at room temperature until use. 2.2. Extraction of crude polysaccharides Defatted peanut cake meal was extracted with selected 20 combinations of independent variables, such as temperature
306
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310
(30–70 °C), extraction time (0.5–2.5 h), and ethanol concentration (40–80%). The peanut cakes were crushed using the beater. Then the meal was mixed with distilled water at the rate of 1 g peanut cake meal per 30 mL water and stayed in water bath. The supernatants were mixed, concentrated to a quarter of the original volume by evaporation. After cooling, the proteins in the extract were removed by the Sevag reagent. Then the crude peanut cake polysaccharide mixtures were precipitated by the addition of ethanol and then precipitated at 4 °C for 6 h. After centrifuged at 3000 rpmg for 20 min, the resulting supernatants were collected and lyophilized. Then the crude defatted peanut cake polysaccharide (termed DPCP) was obtained. The content of crude polysaccharide was determined by the phenol–sulfuric acid method,11 and the yield of DPCP was expressed as g DPCP/g peanut meal 100%. All the experiments were carried out in duplicate. 2.3. Experimental design and statistical analysis Response surface methodology was used to determine the influence of three independent variables and the optimum conditions of crude polysaccharide isolation. The process variables and the responses were defined from published data.12,13 The effects of the variables temperature (x1), extraction time (x2), and ethanol concentration (x3) on the crude peanut cake polysaccharide isolation process were investigated. Each variable was coded at five levels: 2, 1, 0, 1, 2 (Table 1). The variables were coded according to the following equation:
xi ¼ ðX i X i Þ=DX i
ð1Þ
where xi is the dimensionless value of an independent variable, X i is the real value of an independent variable, X i is the real value of an independent variable at the center point, DX i is the step change. The response function investigated was Y i ¼ g ethanol soluble sugars from extract/2 g defatted peanut flour. A central composite experimental design (CCD) was arranged to allow for fitting of second-order model14 (Table 2). The CCD combined the vertices of hybercube whose coordinates were given by 2n factorial design (runs 1–8) with the star points (runs 9–14). The star points were added to the factorial design to provide for estimation of curvature of the model. Six replicates at the center point of the design (runs 15–20) were used to allow for estimation of the pure error sum of squares. All experiments were carried out in a randomized order to minimize any effect of extraneous factors on the observed responses. The model proposed for response (Yi) was:
The significance of each coefficient was determined using the Ftest and p-value. The corresponding variables would be more significant if the absolute F-value becomes greater and the p-value becomes smaller.15 2.4. Purification of defatted peanut cake polysaccharides Crude polysaccharides extracted from defatted peanut cakes (DPCP) were extracted by the method mentioned above. Then the DPCP were redissolved in distilled water and applied to a DEAE Sepharose Fast Flow gel column (2.6 100 cm). One milliliter of 1 mg/mL crude DPCP was subjected to the gel column and eluted by filtered (0.45 lm membrane) distilled water and then by 0, 0.2, 0.4, 0.6 M NaCl at a flow rate of 4.0 mL/min. Each fraction with 1 mL of eluate was collected and determined by the phenol–sulfuric acid method. Based on the colorimetric total carbohydrate test using the method mentioned above, the water fraction, appearing as a single peak, was further purified by the gel permeation chromatography on a column of Sephacryl S-300 High Resolution (2.6 100 cm). The main fraction was collected, dialyzed, and then lyophilized to get a white purified pumpkin polysaccharide (DPCP1). Protein content was estimated using Folin–Ciocalteu reagent by Agilent 8453 UV–vis spectrophotometer.16 2.5. Analysis of monosaccharide compositions The polysaccharide samples were hydrolyzed with 2 M trifluoroacetic acid (TFA) at 100 °C for 4 h. The acid was removed by evaporations with MeOH. Then the hydrolysates were converted into their respective alditol acetates, followed by GC analysis, which was performed on a Finnigan Trace GC 2000. The detailed experimental conditions were as follows: injection temperature: 220 °C, detector temperature: 220 °C, column temperature programed from 130 to 180 °C at 5 °C/min, holding for 5 min at 180 °C, then increasing to 220 °C at 5 °C/min and finally holding for 3 min at 220 °C. Nitrogen was used as the carrier gas and maintained at 1.0 mL/min. 2.6. FT-IR spectroscopy Fourier-transform infrared spectra of the polysaccharide were recorded with a Nicolet 6700 FT-IR spectrometer (Madison, WI, USA) using the KBr disk method. 3. Results and discussion
Y i ¼ b0 þ b1 x1 þ b2 x2 þ b3 x3 þ b11 x21 þ b22 x22 þ b33 x23 þ b12 x1 x2 þ b13 x1 x3 þ b23 x2 x3
ð2Þ
where Y i is predicted response, b0 is offset term, b1 , b2 and b3 is linear effect terms, b11 , b22 and b33 are squared effects and b12 , b13 and b23 are interaction effects. Surface plots were generated by assigning constant (zero) values to two of the three variables and solving the fitted equations as a quadratic equation in the remaining one variable.
3.1. Fitting the models Defatted peanut cake flour was extracted for its polysaccharide following 20 combinations of three independent variables (temperature, extraction time, ethanol concentration) (Table 1). The application of RSM yields the following regression equation, which is an empirical relationship between polysaccharide yield and the test variable in coded units, as given in the following equation.
Table 1 Independent variable values of the process and their corresponding levels Independent variable
Temperature (°C) Time (h) Ethanol concentration (%) a
Coded variables levelsa
Symbol Uncodified
Codified
2
1
0
1
2
X1 X2 X3
x1 x2 x3
30 0.5 40
40 1.0 50
50 1.5 60
60 2.0 70
70 2.5 80
Passage from coded variables level to natural variable level is given by the following equations: x1 = (X1 50)/10; x2 = (X2 1.5)/0.5; x3 = (X3 60)/10.
307
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310 Table 2 CCD arrangement, responses, and predicted values for polysaccharide yield Coded variablesa
Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a
Uncoded variables
Polysaccharide yield (Y) (%)
X1
X2
X3
x1
x2
x3
Experimental ðY 0 Þ
Predicted ðY i Þ
Y0 Yi
1 1 1 1 1 1 1 1 2 2 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 0 0 -2 2 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 0 0 0 0 -2 2 0 0 0 0 0 0
40 40 40 40 60 60 60 60 30 70 50 50 50 50 50 50 50 50 50 50
1.0 1.0 2.0 2.0 1.0 1.0 2.0 2.0 1.5 1.5 0.5 2.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5
50 70 50 70 50 70 50 70 60 60 60 60 40 80 60 60 60 60 60 60
15.5 13.6 16.5 13.8 17.8 17.2 18.4 17.6 14.0 12.9 22.5 21.6 11.0 11.8 26.0 26.1 25.6 25.4 26.3 25.8
15.6 13.9 16.0 13.8 16.8 16.7 17.1 15.1 15.1 13.2 22.7 22.9 10.5 13.7 25.8 25.8 25.8 25.8 25.8 25.8
0.001 0.003 0.005 0.000 0.010 0.005 0.013 0.025 0.011 0.003 0.002 0.013 0.005 0.019 0.002 0.003 0.002 0.004 0.005 0.000
X1: temperature, X2: extraction time, X3: ethanol concentration.
Table 3 Fit statistics for Y
Y ¼ 0:250886 þ 0:005875x1 þ 0:000250x2 0:015250x3 0:033307x21 0:011807x22 0:025932x23 0:000250x1 x2 þ 0:004000x2 x3 0:001250x1 x3
ð3Þ
The predicted values of polysaccharide yields were calculated using the regression model and compared with experimental values in Figure 1. The total determination coefficient (R2) was 97.81%, indicating a reasonable fit of the model to the experimental data. Earlier studies have reported values for R2 ranging from 58.5% to 99.03% for Lingzhi (Ganoderma lucidum),17 roots of Codonopsis pilosula,18 Phellinus igniarius,19 Pholiota squarrosa.7 It can be seen that ethanol concentration was the most significant factor (p <0.05). Especially, temperature, extraction time, and ethanol concentration showed significance at quadratic terms (p <0.05). Guo et al.19 reported a similar effect; however, Sun
Mean R2 Adjusted R2 RMSE CV (%)
Master model
Predictive model
18.97 0.9781 0.9583 0.054 5.85
18.90 0.8398 0.9583 0.054 5.87
et al.18 reported that temperature and extraction time influenced polysaccharide extraction significantly (p <0.001). Analysis of variance (ANOVA) of independent variables was given in Table 3. There was a non-significant lack of fit that further validates the model (p >0.05). The coefficient of variation (CV) is the ratio of the standard error of estimate to the mean value of observed response expressed as a percentage. It is a measure of
2 7 .0 0
27
23.25
Yield (%)
Predicted values
2 2 .7 5
1 8 .5 0
19.5
15.75
12
1 4 .2 5 2.50
70.00 2.00
1 0 .0 0
60.00 1.50
Extraction time (h)
1 0 .5 3
1 4 .4 7
1 8 .4 2
2 2 .3 6
2 6 .3 0
50.00 1.00
40.00
Temperature (°C)
0.50 30.00
Actual v alues Figure 1. Comparison between predicted and actual polysaccharide yield.
Figure 2a. Response surface plots showing the effect of temperature (x1) and extraction time (x2) on extraction yield of polysaccharide.
308
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310
reproducibility of the models. The CV of the model was calculated as 5.85%. As a general rule, a model can be considered to reasonably reproducible if its CV is not greater than 10%. 3.2. Optimization of the process The three-dimension surface plots were drawn to illustrate the main and interactive effects of the independent variables on the dependent one. These graphs were obtained by fixing two variables at coded zero levels (Table 2) while varying the remaining two variables and predicting the response variables (polysaccharide yield). Figure 2a shows both temperature (x1) and extraction time (x2) exert a quadratic effect on polysaccharide production. Effect of temperature (x1) and ethanol concentration (x3) on polysaccharide yield is presented in Figure 2b. The results revealed that the increase in ethanol concentration and extraction time extracted
27
Yield (%)
23
19
15
11
higher amount of polysaccharide from peanut cakes. Figure 2c depicts the influence of extraction time (x2) and ethanol concentration (x3). It can be seen as a quadratic effect for both ethanol concentration and extraction time. Optimum extraction conditions were estimated by the desirability method using a Minitab Software. An extraction temperature of 48.7 °C, extraction time of 1.52 h, and ethanol concentration of 61.9% (v/v) were found to be optimal for polysaccharide extraction from peanut cakes. Studies of the extraction of peanut cakes could not be traced, but similar studies using other materials have been reported. Chen et al.17 worked on polysaccharide extraction from Lingzhi (G. lucidum) and found significant effects of extraction temperature and concluded that optimum conditions were: extraction temperature of 95 °C, extraction time of 3 h, and solvent/meal ratio of 12:1 (v/w). Sun et al.18 reported that optimum conditions for polysaccharide extraction from roots of C. pilosula were as follows: extraction temperature 94 °C, solvent/meal ratio of 9:1 (v/w), extraction time 2.5 h, and number of extraction 5. Guo et al.19 studied the extraction of polysaccharide from P. igniarius and concluded that maximum polysaccharide yield was obtained by extracting mycelia powder with a temperature of 70 °C, extraction time of 1.5 h and solvent/meal ratio of 6.2:1 (v/ w). Qiu et al.20 stated that significant effects of pH, extraction time, extraction temperature, and salting-out temperature for pectin from banana peels were found and concluded that optimum extraction were: pH of 1.5, temperature of 85.5 °C, extraction time of 2 h, and salting-out temperature of 70 °C. Canettieri et al.21 determined that H2SO4 concentration of 0.65%, temperature of 157 °C, solvent/meal ratio of 8.6:1 (v/w) and reaction time of 20 min were optimum conditions for extracting monomeric sugars from hemicellulose fraction of Eucalyptus grandis residue. 3.3. Confirmative tests
80.00
70.00 70.00
60.00 60.00
Ethanol concentration (%)
50.00 50.00
40.00
Temperature (°C)
40.00 30.00 Figure 2b. Response surface plots showing the effect of temperature (x1) and ethanol concentration (x3) on extraction yield of polysaccharide.
The suitability of the model equation for predicting the optimum response value was tested using the recommended optimum conditions. When optimum values of independent variables (extraction temperature 48.7 °C, extraction time 1.52 h, and ethanol concentration of 61.9% v/v) were incorporated into the regression equation, 25.82% polysaccharide yield was obtained whereas experiments at optimum conditions gave a polysaccharide yield of 25.89%. Thus, predicted values from fitted equations and observed values were in very good agreement. 3.4. Preliminary structural analysis
27
Yield (%)
23
19
15
11
80.00
2.50 70.00
2.00 60.00
Ethanol concentration (%)
1.50 50.00
1.00
Extraction time (h)
40.00 0.50 Figure 2c. Response surface plots showing the effect of extraction time (x2) and ethanol concentration (x3) on extraction yield of polysaccharide.
The total sugar content of DPCP-1 was estimated 97.1 ± 1.2% by the phenol-sulfuric method. In contrast, the protein content in the aqueous extract only accounts for 1.0 ± 0.3%, which was due to the removal by the Sevag reagents at the step of purification. Sugar compositional analysis of DPCP-1 determined by GC indicated that its main composition was galactose (Fig. 3). The FT-IR spectrum of DPCP-1 is shown in Figure 4. Three strong absorption bands at 1023.23, 1079.12, 1154.09 cm1 in the range of 1200–1000 cm1 indicated that the monosaccharide in DPCP-1 had a pyranose ring.22,23 The broadly-stretched intense at 3368 cm1 was due to the hydroxyl stretching vibration of the polysaccharide, so is the vibration at 2931.21 cm1 which indicated C–H stretching vibration. The relatively strong absorption peak at 1642 cm1 was due to the associated water.23–25 The absorption peak at 1415 cm1 suggested the C–O stretching vibration, and the peak at 1239 cm1 indicated the existence of O–H flexural vibration. The absorption at ca. 840 cm1 revealed that the polysaccharide had aconfigurations in it.26 A band of absorption at 763 cm1 represented symmetrical ring vibration. No absorption at 1730 cm1 indicated that there were no uronic acids.
309
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310 FID1 A, (HXQ\08071601.D)
pA 140 120 100
Galactose-16.687
80 60 40 20 0 0
5
10
15
20
25
30
min
Figure 3. DPPH scavenging activities of the defatted peanut cakes polysaccharide.
Figure 4. Superoxide anion scavenging activities of the defatted peanut cakes polysaccharide.
4. Conclusions RSM was sufficient to describe and predict the extraction process of bioactive compounds from defatted peanut cakes. Polysaccharide was extracted from defatted peanut cakes with 20 selected combinations of temperature, extraction time, and ethanol concentration. The experimental value of polysaccharide yield varied from 11% to 26.3%. The variable with the largest effect was ethanol concentration. An extraction temperature of 48.7 °C, extraction time of 1.52 h, and ethanol concentration of 61.9% (v/v) were found to be optimal for polysaccharide extraction from defatted peanut cakes which could obtain a yield of 25.89%. The main composition of the polysaccharide was agalactose. Further studies on the precise chemical structures and biological functions of the polysaccharide are needed. References 1. Chen, M. J.; Chen, K. N.; Lin, C. W. J. Food Eng. 2005, 68, 471–480. 2. Gunawan, E. R.; Basri, M.; Rahman, B. A. M.; Salleh, A. B.; Rahman, R. N. Z. A. Enzyme Microb. Technol. 2005, 37, 739–744. 3. Jafari, M.; Nateghi, M.; Rabbani, A. Int. J. Biol. Macromol. 2010, 46, 104–108. 4. Lofty, W. A.; Ghanem, K. M.; El-Helow, E. R. Bioresour. Technol. 2007, 98, 3470– 3477. 5. Ebru, F.; Ozgul, E. LWT-Food Sci. Technol. 2010, 43, 226–231.
6. Ravikumar, K.; Pakshirajan, K.; Swaminathan, T.; Balu, K. Chem. Eng. J. 2005, 105, 131–138. 7. Zhao, H. Z.; Wang, J.; Lu, Z. X. Carbohydr. Polym. 2009, 77, 677–680. 8. Isanga, J.; Zhang, G. N. LWT-Food Sci. Technol. 2009, 42, 1132–1138. 9. Talcott, S. T.; Passeretti, S.; Duncan, C. E.; Gorbet, D. W. Food Chem. 2005, 90, 379–388. 10. Davis, J. P.; Dean, L. L.; Price, K. M.; Sanders, T. H. Food Chem. 2010, 119, 539– 547. 11. Dubois, M.; Gilles, K. A.; Hamilton, J. K.; Rebers, P. A.; Smith, F. Anal. Chem. 1956, 28, 350–356. 12. Fu, C. L.; Tian, H. J.; Li, Q. H.; Cai, T. Y.; Du, W. J. Ultrason. Sonochem. 2006, 15, 511–516. 13. Li, Q. H.; Fu, C. L. Food Chem. 2006, 92, 701–706. 14. Nakai, S.; Li-Chen, E. C. Y.; Dou, J. In Handbook of Food and Bioprocess Modeling Techniques; Sablani, S., Datta, A., Rahman, M. S., Mujumdar, A., Eds.; CRC Press: Boca Raton, 2006; Vol. 1, pp 293–323. 15. Atkinson, A. C.; Donev, A. N. Optimum Experimental Designs; Oxford University Press, 1992. pp. 132–189. 16. Lowry, O. H.; Rosebrough, N. J.; Farr, A. L.; Randall, R. J. J. Biol. Chem. 1951, 193, 265–275. 17. Chen, X. P.; Wang, W. X.; Li, S. B.; Xue, J. L.; Fan, L. J.; Sheng, Z. J.; Chen, G. Y. Carbohydr. Polym. 2010, 80, 944–948. 18. Sun, Y. X.; Liu, J. C.; Kennedy, J. F. Carbohydr. Polym. 2010, 80, 949–953. 19. Guo, X.; Zou, X.; Sun, M. Carbohydr. Polym. 2010, 80, 344–349. 20. Qiu, L. P.; Zhao, G. L.; Wu, H.; Jiang, L.; Li, X. F.; Liu, J. J. Carbohydr. Polym. 2010, 80, 326–331. 21. Canettieri, E. V.; Rocha, G. J.; Carvalho, J. A., Jr.; Silva, J. B. Bioresour. Technol. 2007, 98, 422–428. 22. Kacˇuráková, M.; Capek, P.; Sasinková, V.; Wellner, N.; Ebringerová, A. Carbohydr. Polym. 2000, 43, 195–203.
310
Y. Song et al. / Carbohydrate Research 346 (2011) 305–310
23. Ye, L. B.; Zhang, J. S.; Yang, Y.; Zhou, S.; Liu, F. Y.; Tang, Q. J., et al Food Chem. 2009, 112, 962–966. 24. Park, F. S. Application of I.R. Spectroscopy in Biochemistry, Biology and Medicine; Plenum: New York, 1971. pp. 100–140.
25. Cao, W.; Li, X. Q.; Liu, L.; Wang, M. C.; Fan, H. T.; Li, C., et al Carbohydr. Res. 2006, 341, 1870–1877. 26. Barker, S. A.; Bourne, E. J.; Stacey, M.; Whiffen, D. H. J. Chem. Soc. 1954, 171– 176.