

ORIGINAL ARTICLE 

Year : 2018  Volume
: 14
 Issue : 53  Page : 2226 


Optimization of microwaveassisted extraction of silymarin from Silybum marianum straws by response surface methodology and quantification by highperformance liquid chromatograph method
HongSheng Ruan^{1}, HaiFeng Zhang^{2}, Kun Teng^{2}
^{1} College of China Medicine, Zhejiang Pharmaceutical College, Ningbo, PR China ^{2} College of Pharmacy and Food Science, Tonghua Normal University, Tonghua, PR China
Date of Submission  08Dec2016 
Date of Acceptance  10Jan2017 
Date of Web Publication  20Feb2018 
Correspondence Address: Kun Teng College of Pharmacy and Food Science, Tonghua Normal University 134000, Yucai Road No. 950 Tonghua PR China
Source of Support: None, Conflict of Interest: None  Check 
DOI: 10.4103/pm.pm_556_16
Abstract   
Background: Silybum marianum, a member of the Aster family, is a wellknown Chinese herb and the source of a popular antioxidant that is extensively used in Asia. The abundant S. marianum straws are still underutilized and wastefully discarded to pollute the environment. Objective: To solve the above problem and better utilize S. marianum straws, the objective of this study was to optimize the conditions for extraction of silymarin from S. marianum straws. Materials and Methods: A combination of microwaveassisted extraction and response surface methodology (RSM) was used for silymarin from S. marianum straws and yield assessment by highperformance liquid chromatography method. The RSM was based on a fivelevel, fourvariable central composite design (CCD). Results: The results indicated that the optimal conditions to obtain highest yields of silymarin were microwave power of 146 W, extraction time of 117 s, liquidtosolid ratio of 16:1 mL/g, and ethanol concentration of 43% (v/v). Validation tests indicated that under the optimized conditions, the actual yield of silymarin was 6.83 ± 0.57 mg/g with relative standard deviation of 0.92% (n = 5), which was in good agreement with the predicted yield. Conclusions: The exploitation of the natural plant resources present very important impact for the economic development. The knowledge obtained from this work should be useful to further exploit and apply this material. Abbreviations used: MAE: Microwaveassisted extraction, RSM: Response surface methodology, HPLC: Highperformance liquid chromatography, CCD: Central composite design, ANOVA: Analysis of variance.
Keywords: Microwaveassisted extraction, response surface methodology, Silybum marianum, silymarin
How to cite this article: Ruan HS, Zhang HF, Teng K. Optimization of microwaveassisted extraction of silymarin from Silybum marianum straws by response surface methodology and quantification by highperformance liquid chromatograph method. Phcog Mag 2018;14:226 
How to cite this URL: Ruan HS, Zhang HF, Teng K. Optimization of microwaveassisted extraction of silymarin from Silybum marianum straws by response surface methodology and quantification by highperformance liquid chromatograph method. Phcog Mag [serial online] 2018 [cited 2020 Jul 9];14:226. Available from: http://www.phcog.com/text.asp?2018/14/53/22/225664 
Summary
 Silymarin has been isolated from Silybum marianum straws by microwaveassisted extraction and response surface methodology
 The results obtained are helpful for the full utilization of S. marianum straws
 The microwaveassisted extraction is a very useful method for the extraction of important phytochemicals from plant materials.
Introduction   
Silybum marianum is a member of the S. marianum (L.) Gaerth genus and the Aster family. Seeds of S. marianum (Shui Fei Ji in Chinese) are a famous medical herb. It is used for treating liver and gallbladder diseases.^{[1],[2],[3]} The current research has focused on pharmacological efficacy and on component extraction processing of the seeds of S. marianum extracts.^{[4],[5]} Most of its hepatoprotective properties are attributed to the presence of silybin, which is the main constituent (60%–70%) of silymarin.^{[6],[7]} Silymarin is a complex mixture of polyphenolic molecules, including seven closely related flavonolignans (silybin A, silybin B, isosilybin A, isosilybin B, silychristin, isosilychristin, and silydianin) and one flavonoid (taxifolin).^{[4],[5]} Recently, silymarin has been widely used in food, medicine, and health products.
As a newtype extraction technique, microwaveassisted extraction (MAE) has attracted interest as an alternative approach to the conventional extraction methods due to its unique heating mechanism, moderate cost, and good performance.^{[8]} Later, MAE has been widely used in food, natural products, and traditional Chinese medicine extraction process.^{[8],[9],[10],[11]}
Response surface methodology (RSM) is an effective tool for optimizing the process.^{[12]} With RSM, the number of experiments can be effectively reduced by a reasonable experimental design and multivariate quadratic regression equation to fit the function between factors and response. To date, RSM has been successfully applied to optimize complex processes used to extract compounds from plants.^{[13],[14],[15]}
As an important traditional medicinal plant, S. marianum grows wild and is also being cultivated on large areas in some parts of the world for commercial production of silymarin complex.^{[16]} Although there are bioactive and medicinal potentials in S. marianum, much attention had been paid to the silymarin extraction from S. marianum seeds. However, because of the lack of research on high valueadded utilization of S. marianum straws, this abundant resource is discarded as useless residue after harvesting. Although some portion of these straws is consumed as animal feed, the majority of the processing wastes are thrown out. That is not only an environmental pollution but also a waste of bioresource. Therefore, the development of integrative utilization and high addedvalue products from S. marianum straws could benefit the rapid and sustainable development of S. marianum industry and present an additional source of income for farmers in the Chinese countryside.^{[17]} To our knowledge, the extraction of silymarin from S. marianum straws with MAE method has not yet been reported. To solve above problem and better utilize S. marianum straws, MAE technology was used to extract silymarin from S. marianum straws and to optimize the extraction process. Central composite design (CCD) combined with RSM was applied to fit and exploit a mathematical model representing the relationship between the response (microwave power, extraction time, liquidtosolid ratio, and ethanol concentration) and variables (silymarin yield). The results should be helpful in the further utilization of silymarin from S. marianum straws.
Materials and Methods   
Plant material
The samples of S. marianum straws were collected in Sunwu, Heihe, China. The plants were identified by Zhang Haifeng, and a voucher #151125 of the specimen was deposited at Tonghua Normal College. The content of silymarin from S. marianum straws was not <3.50 mg/g by highperformance liquid chromatography (HPLC) method. The obtained S. marianum straws were dried, ground, and then passed through the sieve screen. The powder obtained from the 20 and 40 mesh sieve screens was subjected to MAE extraction.
Chemicals
Silybin used as reference standard was purchased from the National Institute for the Control of Pharmaceutical and Biological Products (Beijing, China). HPLCgrade methanol was purchased from Tedia Company Incorporated (Ohio, USA). Ultrapure water was purified by a MilliQ water purification system (Bedford, MA, USA). All reagents used in the study were of analytical grade.
Extraction procedure
MAE was carried out in a CW2000 microwave preparation system (Xintuo Microwave Decomposition and Testing Technology Co. Ltd., Shanghai, China). S. marianum straw powder (10 g) was accurately weighted and placed into the extraction vessel in addition to a suitable amount of extraction solvent and subjected to set microwave power and extraction times for predefined irradiation time for two cycles. At the end of extraction, the extracts were allowed to cool to room temperature. Subsequently, the extract was filtered and the filtrate was collected for HPLC analysis.
Experimental design and statistical analysis
Specifically, data from the CCD were utilized to determine the optimum combination of variables. A fractional 5level, 4factor experimental design with three replicates at the center point was used to find effects of independent variables on the dependent variables. In the study, independent variables include microwave power (x_{1}), extraction time (x_{2}), liquidtosolid ratio (x_{3}), and ethanol concentration (x_{4}) for S. marianum straws. Each factor was coded at five levels (–1.682, –1, 0, 1, and 1.682). The RSM experimental design is summarized in [Table 1]. The complete experimental design consisted of 30 points, including six replicates of the center point, were randomized to satisfy the statistical requirement of independence of observations, as shown in [Table 2]. A secondorder polynomial regression model was used to express the yield as a function of the independent variables as follows:  Table 2: Central composite design matrix four variables with experimental values of silymarin yield
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Where y represents the response variables, β_{0} is a constant, β_{i}, β_{ii}, and β_{ij} are the linear, quadratic, and interactive coefficients, respectively, and x_{i} and x_{j} represent the coded independent variables. The adequacy of the model was determined by evaluating the lack of fit, coefficient of determination (R^{2}), and the Fisher test value (Fvalue) obtained from the analysis of variance (ANOVA) generated by the software DesignExpert version 7.0.(StatEase Inc., Minneapolis, MN, USA). Threedimensional (3D) response surface plots were generated by keeping two responses variable at its optimal level and plotting that against two factors (independent variables). Statistical significance was considered at P < 0.05.
[Table 1] shows the code and levels of factors chosen for the experiments.
Highperformance liquid chromatography analysis of extracts
Silybin was analyzed by a Shimadzu LC2010 HT HPLC system (Shimadzu Corp., Kyoto, Japan) coupled with a UV detector. A Kromasil C_{18} column (150 mm × 4.6 mm, 5 μm) was used. The mobile phase consisted of methanol and 1% acetic acid in water (48:52, v/v) at a flow rate of 1.0 mL/min.^{[18]} The wavelength of detection was 287 nm, column temperature was 25°C, and injection volume was 10 μL.
Results and Discussion   
Extraction model and statistical analysis
The design matrix of the variables in coded units is given in [Table 2] along with the predicted and experimental values of response. The silymarin yield ranged from 3.98 mg/g to 7.02 mg/g. By applying multiple regression analysis on the experimental data, the response variable and the test variables were related by the following secondorder polynomial equation:
[Table 2] shows the CCD matrix four variables with experimental values of silymarin yield.
The significance of each coefficient was determined using the Ftest and P values [Table 3]. It can be seen that the variables with the largest effect were the linear terms of microwave power (x_{1}), extraction time (x_{2}), and the quadratic term of microwave power (x_{1}^{2}), extraction time (x_{2}^{2}), liquidtosolid ratio (x_{3}^{2}), and ethanol concentration (x_{4}^{2}), followed by the interaction effects of microwave power and extraction time (x_{1}x_{2}), microwave power and ethanol concentration (x_{1}x_{4}), and extraction time and liquidtosolid ratio (x_{2}x_{3}). The results suggest that the change of microwave power and extraction time had highly significant effects on the yield of silymarin (P < 0.0001) from S. marianum straws.  Table 3: Estimated regression model of relationship between response variables (silymarin yield) and independent variables (x_{1}, x_{2}, x_{3}, x_{4})
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ANOVA procedure was used to analyze the model for significance and suitability, and a statistical summary is given in [Table 4]. Values of probability (P) >F < 0.05 indicate model terms are significant. Values >0.10 indicate the model terms are not significant. The ANOVA showed that the model was highly significant (P < 0.0001) with F of 24.42. The value of 1.26 for lack of fit implied that it was not significant relative to the pure error. Nonsignificant lack of fit is good and indicates that the model equation was adequate for predicting the silymarin yield under any combination of values of the variables. The determination of coefficient (R^{2}) of the model was 0.958, which indicated a relatively high degree of correlation between the observed and predicted values. The predicted R^{2} of 0.8094 pointed to a good agreement between the experimental and predicted values for silymarin. The predicted R^{2} of 0.8094 is also in reasonable agreement with the adjusted R^{2} of 0.9187. An adequate precision of 17.949 for silymarin indicated an adequate signal. This model can be used to navigate the design space.  Table 4: Variance analysis of the secondorder regression model on silymarin yield
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Optimization of the procedure by response surface methodology
Equation 1 allowed the prediction of the effects of the four factors on the silymarin yield. Four independent response surface plots are shown in [Figure 1]a,[Figure 1]b,[Figure 1]c,[Figure 1]d,[Figure 1]e,[Figure 1]f. Two variables within the experimental rang were depicted in 3D surface plots while the other variable was kept constant at zero level. As shown in [Figure 1], the increased microwave power (x_{1}), extraction time (x_{2}), liquidtosolid ratio (x_{3}), and ethanol concentration (x_{4}) up to a threshold level led to increased silymarin yield. Beyond this level, the silymarin yield slightly decreased, which indicated that a greater yield could be achieved if the moderate microwave power (x_{1}), extraction time (x_{2}), liquidtosolid ratio (x_{3}), and ethanol concentration (x_{4}) were selected. Therefore, it could be concluded that the optimal conditions for MAE of silymarin yield from S. marianum straws were a microwave power of 146 W, extraction time of 117 s, liquidtosolid ratio of 16:1 mL/g, and ethanol concentration of 43% (v/v).  Figure 1: Response surface plots for the effects of (a) microwave power and extraction time; (b) microwave power and liquidtosolid ratio; (c) microwave power and ethanol concentration; (d) extraction time and liquidtosolid ratio; (e) extraction time and ethanol concentration; (f) liquidtosolid ratio and ethanol concentration on the silymarin yield
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Validation of the model
Triplicates verification experiment was carried out under these conditions to validate the adequacy of the model. Under the optimal conditions, the maximum yield of predicted value was 6.97 mg/g. A mean value of 6.83 ± 0.57 mg/g with relative standard deviation of 0.92% (n = 5), obtained from actual experiments. The good agreement between the predicted and experimental results verified the validity of the model and also indirected that RSM was a powerful tool for searching the optimal values of the individual variables and the maximum response value.
Conclusions   
In this work, an efficient MAE process has been developed for the extraction of silymarin from S. marianum straws. CCD was successfully employed to optimize the extraction parameters. The best conditions were shown to be microwave power of 146 W, extraction time of 117 s, liquidtosolid ratio of 16:1 mL/g, and ethanol concentration of 43% (v/v). The maximum silymarin yield was 6.83 ± 0.57 mg/g (n = 5) under these optimal conditions. This study can be useful for the development of industrial extraction of silymarin from S. marianum straws, including further studies concerning the optimal number of sequential steps to enhance the efficacy of a potential largescale extraction system. With all these merits, MAE should be considered for wider application in the extraction and purification of phytochemicals from plants. It was found that RMS could be used to optimize MAE process.
Financial support and sponsorship
This research was financially supported by the Hei long jiang Administration of Land Reclamation (HNK125B1304A).
Conflicts of interest
There are no conflicts of interest.
References   
1.  Zheng XZ, Wang X, Lan YB, Shi J, Xue SJ, Liu C. Application of response surface methodology to optimize microwaveassisted extraction of silymarin from milk thistle seeds. Sep Purif Technol 2009;70:3440. 
2.  Greenlee H, Abascal K, Yarnell E, Ladas E. Clinical applications of Silybum marianum in oncology. Integr Cancer Ther 2007;6:15865. 
3.  Kren V, Walterová D. Silybin and silymarin – New effects and applications. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 2005;149:2941. 
4.  Kim NC, Graf TN, Sparacino CM, Wani MC, Wall ME. Complete isolation and characterization of silybins and isosilybins from milk thistle ( Silybum marianum). Org Biomol Chem 2003;1:16849. 
5.  Kroll DJ, Shaw HS, Oberlies NH. Milk thistle nomenclature: Why it matters in cancer research and pharmacokinetic studies. Integr Cancer Ther 2007;6:1109. 
6.  Salehi M, Hasanloo T, Mehrabian S, Farahmand S. Effects of Silybum marianum (L.) Gaertn seeds extract on dermatophytes and saprophytes fungi in vitro compare to clotrimazol. Pharm Sci 2011;16:20310. 
7.  Hassan R, Tahereh H, Mohammad RS, Roshanak S. Silymarin production by hairy root culture of Silybum marianum (L.) Gaertn. Iran J Biotechnol 2008;6:1138. 
8.  Ma FY, Gu CB, Li CY, Luo M, Wang W, Zu YG, et al. Microwaveassisted aqueous twophase extraction of isoflavonoids from Dalbergia odorifera T. Chen leaves. Sep Purif Technol 2013;115:13644. 
9.  Wu ZJ, Ruan HS, Wang YH, Chen ZB, Cui YD. Optimization of microwaveassisted extraction of puerarin from radix puerariae using response surface methodology. Sep Sci Technol 2013;48:165764. 
10.  Fliniaux O, Corbin C, Ramsay A, Renouard S, Beejmohun V, Doussot J, et al. Microwaveassisted extraction of herbacetin diglucoside from flax ( Linum usitatissimum L.) seed cakes and its quantification using an RPHPLCUV system. Molecules 2014;19:302537. 
11.  Suhara P, Mohini S. Optimization of microwave assisted alkaline extraction of xylan from birch wood using response surface methodology. J Mater Sci Chem Eng 2013;1:3850. 
12.  Box G, Wilson K. On the experimental attainment of optimum conditions. J Roy Statist Soc Ser B Metho 1951;13:145. 
13.  de Morais Rodrigues MC, Borges LL, Martins FS, Mourão RH, da Conceição EC. Optimization of ultrasoundassisted extraction of phenolic compounds from Myrcia amazonica DC. (Myrtaceae) leaves. Pharmacogn Mag 2016;12:912. 
14.  Peng LX, Zou L, Zhao JL, Xiang DB, Zhu P, Zhao G, et al. Response surface modeling and optimization of ultrasoundassisted extraction of three flavonoids from tartary buckwheat ( Fagopyrum tataricum). Pharmacogn Mag 2013;9:2105. 
15.  Zou TB, Xia EQ, He TP, Huang MY, Jia Q, Li HW, et al. Ultrasoundassisted extraction of mangiferin from mango ( Mangifera indica L.) leaves using response surface methodology. Molecules 2014;19:141121. 
16.  Zahir A, Abbasi BH, Adil M, Anjum S, Zia M, IhsanUIHaq, et al. Synergistic effects of drought stress and photoperiods on phenology and secondary metabolism of Silybum marianum. Appl Biochem Biotechnol 2014;174:693707. 
17.  Lee CP, Yen GC. Antioxidant activity and bioactive compounds of tea seed ( Camellia oleifera abel.) oil. J Agric Food Chem 2006;54:77984. 
18.  Pharmacopoeia of the People's Republic of China. Beijing, China: Chinese Medicine Science Press; 2015. p. 108. 
[Figure 1]
[Table 1], [Table 2], [Table 3], [Table 4]
