The Extraction Of Phenolic Compounds Biology Essay


Response surface methodology was used to find the optimum ethanol concentration and temperature which maximizes the antioxidant activity (AA) of hydroalcoholic extracts from aerial parts of Bidens pilosa L. A rotatable central composite design was used and the extracts were characterized by the determination of solid concentration (SC), total flavonoid (TFC) and total polyphenol content (TPC). AA was determined through 2,2′-azinobis (3-ethylbenzothiazoline-6-sulphonic acid) diammonium salt (ABTS) and 2,2-diphenyl-1-pycrylhydrazyl (DPPH) radical scavenging activity. Mathematical models showed the significant effects of each variable and allowed to select the optimum conditions of ethanol concentration (62.7%) and extraction temperature (66.2°C). The optimized extract presented an AA of 804.9 ± 12.2 Trolox equivalent antioxidant capacity (TEAC) dry base (d.b.) for DPPH and 515.8 ± 31.8 TEAC d.b for ABTS. It was observed that both TFC and TPC showed a good correlation with AA of the extracts.


Nowdays, there is a growing interest to find natural substances with antioxidant properties which can be used in the replacement of the synthetic antioxidants. The causes of this tendency can be linked to the attributed healthy benefits to human body associated to natural antioxidants and the deleterious secondary effects of artificial antioxidants (Wardhani et al., 2010). Most antioxidants isolated from higher plants are polyphenols, which are the most promising group of molecules (Deba et al., 2008).

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In the human body, the reactions mediated by reactive oxygen species (ROS) protect the cells from oxidative stress and stabilize the redox homeostase. When the balance pro-oxidants/anti-oxidants is broken towards the production of ROS, an oxidative stress is generated which is associated with degenerative diseases (Halliwell & Gutteridge 1999).

Simple experiments could be done in order to test the antioxidant activity (AA) in vitro as a previous step in the study of the AA in vivo. Most of the methods are defined as inhibition methods involving free radicals. Due to the chemical diversity of the molecules present in vegetal samples, it is necessary to use at least two different methods (Choi et al., 2002). Each method has its advantages and disadvantages, but according to Krishnaiah et al. (2010) the more common and relevant are the 2,2′-azinobis (3-ethylbenzothiazoline-6-sulphonic acid) diammonium salt (ABTS) and 2,2-diphenyl-1-pycrylhydrazyl (DPPH) methodologies, which have been improved in the last years.

Bidens pilosa L. (Asteraceae) is a plant native to South America which today is spread all over the world, particularly in tropical and subtropical regions (Brandão et al., 1997) and it was recently reported as a potential source of antioxidants (Krishnaiah et al., 2010). Compounds as the dicaffeoylquinic acids and flavonoids isolated from this plant have been reported as potent antioxidants (Chiang et al., 2004). B. pilosa is also traditionally used as anti-hyperglycemic, anti-hypertensive, antiulcerogenic, hepatoprotective, anti-leukemic, antitumoral (Chiang et al., 2004), anti-inflammatory agent in hepatitis, laryngitis, headache, and digestive disorders (Abajo et al.,2004). In the Amazon region B. pilosa is used to treat malaria (Brandão et al., 1992). The leaves infusion was recently included in the resolution of medicinal plants of the Brazilian Sanitary Surveillance Agency (Brasil, 2010) for the treatment of jaundice. Deba et al. (2008), demonstrated the antioxidant and antimicrobial activity of essential oils from flowers and leaves of B. pilosa, which might be a natural potential source of preservative in food or related industries. Kviecinski et al. (2011) reported the high levels of scavenger activity of the crude extract and the ethyl acetate fraction of B. pilosa which exerted a beneficial action in preventing liver damage.

Several parameters could influence the extraction efficiency of phenolic compounds from vegetable sources, such as, temperature, pH, time and solvent polarity (Juntachote et al., 2006) and their effects may be either independent or interactive. Traditional optimization method, test one factor at a time in a very time-consuming process and interaction among factors could be ignored (Liyana-pathirana & Shahidi, 2005). (Liyana-Pathirana, C. & Shahidi F. 2005). Response surface methodology (RSM) is a useful experimental design tool based on statistical and mathematical techniques used to study different levels of factors with a minimum of experiments. RSM has been successfully applied for the extraction of bioactive compounds from plants, for example, phenolic compounds from wheat (Liyana-Pathirana & Shahidi, 2005), grape cane (Karacabey & Mazza, 2008), phenolic antioxidants from Euterpe oleracea (Pompeu et al.,, Silva & Rogez , 2009), production of antioxidant compounds from soy beans fermented by Aspergillus orizae (Wardhani , et al.,Vazquez & Pandiella, 2010), extraction of phenolics and flavonoids from a pink guava puree industrial by-product (Kong et al., 2010) and production of phenolic extracts of lemon grass, galangal, holy basil and rosemary (Juntachote et al., 2006) among others works.

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Granato et al. (2011) summarized the statistical procedures used to analyze results from a design of experiments. The first step is to select the relevant factors and their levels which will be employed in the experimental design that could be factorial, fractional factorial, central composite or a mixture design. Experimental data are analyzed and validated to generate a mathematical model, which describes the chemical or biochemical processes and this model is used to optimize the process. The aim of this work was to use RSM to optimize the polyphenol contents and AA of hydroalcoholic extracts from the aerial parts of B. pilosa.


Chemicals: 6-hydroxyl-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox), ABTS, DPPH, gallic acid and dehydrated quercetin were acquired from Sigma-Aldrich Chemical Co. Ferric chloride (FeCl3.6H2O), ethanol and potassium persulfate were acquired from LabSynth.

Plant material: wild plants were collected in rural region of Monte Alegre do Sul, SP, Brazil (S.22°41.57.91'5;W.46°40'32.70.0) during the summer season (March 2010). The plant material was identified and a voucher specimen (collection no. SPFR 12751) was deposited at the herbarium of the University of São Paulo, Ribeirão Preto. The aerial parts of the plant were dried in an air circulation stove at 37 °C and powdered using a knife mill, until a mean diameter of 0.3 mm. Powdered plants were maintained at room temperature in hermetic plastic pots, and protected from light until required for experimental runs.

Extractions: Extractive solutions were prepared using dynamic maceration in a glass extractor coupled to a thermostatic water bath set at the desired temperature according to an experimental design (Table 1). Solvent temperature was verified before each extraction. A plant to solvent ratio of 1/10 (w/v) and an extraction time of 30 min was set for all extraction experiments. The extraction mixture was maintained under agitation during all the extraction time by using stirring bars. In order to finish the extraction, the mixture was filtered through filter paper using a vacuum filtration system (Souza, 2007). The filtered extracts were maintained at 4°C until needed for analysis. The extracts were characterized by determination of the solids concentration (SC), total flavonoid content (TFC), total polyphenol content (TPC) and AA.

Solids concentration: Approximately 2 g of extract were put in a Petri dish and maintained at 105 ± 1°C in an oven until constant weight (oven drying method). SC was calculated based on the difference of the extractive solution and the dried residue weight. Results were expressed as the average of three determinations, in percentage.

Total flavonoid content: The spectrometric method used was described and validate by Souza (2007). It is based on the absorbance displacement measured at 425 nm after the addition of 0.5 % AlCl3 solution (w/v) with a reaction time of 30 min. The absorbance was measured using a spectrophotometer UV-vis HP 8453XXX HP. The TFC is expressed as mg quercetin/g extract. All samples were analyzed in triplicate.

Total polyfenol content: The TPC in the extracts was determined by the Folin-Denis method (Souza, 2007), consisting in the reaction of 2 mL of diluted extract solution and addition of 2 mL of Folin-Denis reagent and 16 mL of a saturated solution of calcium carbonate. Absorbance at 750 nm was measure exactly after 2 min in a HP 8453 spectrophotometer. A calibration curve was constructed and results were expressed as mg of gallic acid equivalents (GAE)/g of extract. Triplicate tests were conducted for each sample.

Antioxidant activity:

The AA of the extractive solutions was determined by two distinct methodologies, the reduction of the radical DPPH, and by the ABTS method.

The DPPH methodology was performed according Georgetti et al. (2006). Briefly aliquots of 30 µL of an appropriated plant extract dilution were added to a mixture of 1 mL of acetate buffer pH 5.5 and 1 mL of absolute ethanol. Finally 0.5 mL of a 0.250 mM radical solution of DPPH in absolute ethanol was added and its absorbance was measured at 517 nm after 20 min. A solvent blank solution of a mixture of 1 mL ethanol and 0,5 mL of buffer was employed. The DPPH radical solution in the reaction medium without the extract was considered the positive control. The antioxidant capacity based on the DPPH free radical scavenging ability of the extract was expressed as µmol Trolox equivalents/g of plant extract (TEAC) using a standard analytic curve of Trolox.

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The ABTS methodology carried out as described by Re et al. (1999). ABTS+ radical cation was generated by reacting 7 mM ABTS and 2.45 mM potassium persulfate with incubation for 16 h at room temperature in the dark. The ABTS solution was diluted with ethanol to reach an absorbance of 0.700 ± 0.020 at 734 nm. Plant extracts were appropriately diluted with absolute ethanol and mixed with 3 mL of diluted ABTS free radical cation solution. Absorbance was recorded at 734 nm after 6 min using a UV-VIS HP 8453 spectrophotometer. A calibration curve of Trolox was constructed with standard solutions in concentrations from 0 to 19.8 µM. Absolute ethanol was used as blank. The percent of inhibition of absorbance at 734 nm was calculated and plotted as a function of concentration of Trolox for the standard reference data. The absorbance of the resulting oxidized solution was compared to that of the calibrated Trolox standard. Results were expressed in terms of TEAC (Re et al., 1999).

Experimental design and statistical analysis

An rotatable central composite design of two factor/five level was used to study the extraction process. It consisted of 11 experimental runs, including three replicates at the center point. The independent variables were ethanol proportion (%, v/v ethanol/water) and extraction temperature (°C). The range and levels of these variables are presented in Table 1, being the coded values shown in brackets. Preliminary experiments were the first step in the generation of the experimental design model, evaluating the main factors that control the process and the lower and upper levels that would be employed in the design.Table 1. Coded and uncoded variables used in the experimental design.

Experimental data were analyzed with the statistical software Statistica 9.1 (StatSoft, Inc. 2010) and results were fitted to and appropriate mathematical model in order to obtain empirical equations that describe the significant parameters as a function of ethanol concentration and temperature. A confidence level higher than 95 % (p < 0.05) was considered significant.

Model validation: Equations for each parameter were employed to obtain optimum conditions of ethanol concentration and temperature wichwhich maximizes the TFC, TPC and the AA of the extractive soluctions. An extract was prepared in the selected conditions and analyzed in order to verify the accuracy and prediction capacity of the statistical modeling.


Solvent polarity is as a critical factor in the extraction of flavonoids and polyphenols (Cacace & Mazza 2003) and it is known that those compounds present good correlation with AA (Thaipong et al., 2006, Tawaha et al., 2007). Different solvents could be employed, but in order to reduce toxicity of the extracts for human use the solvent polarity was limited to ethanol-water mixtures. Changes in ethanol concentration modify the physical properties of the solvent such as density, dynamic viscosity and dielectric constant (Cacace & Mazza, 2003). Extraction time was fixed in 30 min since preliminaries experiments did not show significant influence of this factor in the extraction process of antioxidant compounds from B. pilosa. Regarding to temperature, previous works (Pompeu et al., Silva & Rogez , 2, 2009; Ghafoor, et al., Choi, Leon & Jo, 2009) showed that increasing temperature would favor extraction by enhancing solubility of antioxidant compounds, although, some phenolic compounds are thermolabile. Thus, it is important to select a temperature that increases the antioxidants extraction and avoid from thermodegradation.

Table 2 shows the responses of the dependent variables as a function of the extraction conditions. Data from Table 2 show that the highest and lowest SC have direct relationship with the extraction conditions. High temperatures would favor extraction process by increasing solubility and the diffusion coefficient. Responses were fitted to a second-order model equation and examined in terms of the goodness of fit. Effects varied depending on which response variable was analyzed. Regression coefficients of the adjusted quadratic model as a function of the studied factors are shown in Table 3. Data with p < 0.05 were considered significant. It can be seen from Table 3 that almost all variables were statistically significant on the SC of the extractive solutions at the range studied except the quadratic component of the temperature. Linear and quadratic effects of ethanol concentration show negative effects since increases in this variable will reduce the SC. The interaction between the linear components of temperature and ethanol concentration produces the highest significant effect, which is reflected on results from Table 2. The extract obtained with an ethanol concentration of 70% and temperature of 30 °C presents a SC of 1.4 %, while for the extract with an ethanol concentration of 80.6% and 45 °C the result was 1.5 %.

TFC increases as temperature and ethanol concentration increase as shown in the three dimension graph presented in Figure 1, reflecting the positive effects of the linear components of the regression model fitted to ethanol concentration. TPC shows a different response since the quadratic effect of ethanol concentration was negative. Figure 1 shows that the TPC increases significantly (???? - EU VEJO UM CRESCIMENTO SIGNIFICATIVO - CORRIGIR TEXTO), with the increase of ethanol concentration reaching a maximum close to the higher levels of ethanol concentration tested. This response is affected mainly by the linear and quadratic effects of the ethanol concentration and by linear component of the temperature. The response surface obtained for TPC was comparable to the results presented by Ghafoor et al. (2009) during the optimization of ultrasound-assisted extraction of phenolic compounds, antioxidants and anthocyanins from grape (Vitis vinifera) seeds, where the factors investigated were the extraction time, temperature and ethanol concentration.

The AA of the extractive hydroalcoholic solutions showed an interesting behavior. The three dimensional graph of the DPPH method is similar to the TPC graph. In the same way, the graph of the ABTS is similar to the graph obtained for TFC. Regression coefficients also showed the same behavior. Negative effect for the quadratic component of ethanol concentration was observed in the regression analysis of TFC and AA obtained by ABTS method. In the case of polyphenols and DPPH negative effects were observed for the quadratic component of ethanol concentration and for the interaction between ethanol concentration and temperature. The high determination coefficients (R2) of the plot of AA obtained by the two methods against the TFC and TPC, presented in Figure 2 confirm the trends previously described since higher values are found in the graphic of DPPH versus polyphenols and ABTS versus flavonoids. This behavior could be explained by the fact that polyphenols are hydrophilic substances and, therefore, would react easily with the DPPH radical. Since flavonoids are less water soluble, they would react more easily with the ABTS radical, which could be employed in determination of AA in both lipophilic and hydrophilic medium. The DPPH radical does not have a high enough redox potential to oxidize simple sugars as glucose, and most of the reported flavonoids of B. pilosa are glycoside (Wang et al., 1997; Wang et al.,. Wu. Shi. 202010). So the DPPH radical in the extract will react more easily with aglycone compounds than with glycosides ones, since glycoside molecules are less reactive towards free radicals and more water-soluble (Rice, - Evans. 1997). However, further studies are needed in order elucidate these trends.

Lizcano et al. (2010) reported a higher correlation between pholyphenols rather than flavonoids and AA of aqueous extracts of Colombian medicinal plants. In that work TPC showed a R2 of 0.824 for the ABTS method and R2 of 0.915 for DPPH. Regarding to TFC an R2 of 0.845 for ABTS and R2 of 0.865 for DPPH was observed.

Since the two radicals molecules employed to test the AA are different the TEAC value will not be the same. However the trend observed for the two methods was similar, showing the same behavior regarding to ethanol concentration and temperature.

Even though correlations between AA, TPC and TFC were found, other compounds present in the extracts should contribute to the overall AA. Chiang et al. (2004) reported significant AA of the 3,4-di-O-caffeoylquinic acid (IC50 3.29 mg/mL) and 4,5-di-O-caffeoylquinic acid isolated from the buthanolic fraction of B. pilosa. Compounds as monoterpenes have been identified as the bioactive components of this plant and are thought to be also involved in its AA (Deba et al., 2008).

Optimization of the extractive process

The optimization of the extraction conditions was carried out through the use of the desirability approach, using the software Statistica 9.1 (StatSoft. Inc. 2010), and the models obtained by regression analysis. The following extraction conditions were obtained: ethanol concentration (62.7%) and extraction temperature (66.2°C) being the others conditions maintained constant, plant/solvent ratio and time.

A new extraction experiment was carried out at the selected conditions, in order to evaluate the validity of the optimization procedure. Table 4 shows results for predicted conditions and obtained results for each experimental response. Results show a good agreement between the experimental and predicted values, although the SC was slightly lower than expected. However, the differences observed are not statistically relevant, and the procedure and conditions selected could be considerate adequate.

Table 4. Validation of the optimized model.







Predicted result






Observed result




14.1±0.2 w.b*804.9±12.2 d.b**

9.0±0.6 w.b*515.8±31.8 d.b**

Table 2. Experimental results for Total flavonoid content (TFC), Total polyphenols content (TPC), antioxidant activity by DPPH and ABTS.

Extract code

Total flavonoids(mg/gbu)

Total Polyphenols (mg/gbu)

Solids concentration(%)




0.06 ± 0.00

0.40 ± 0.01

1.7 ± 0.1

2.20 ± 0.10

1.24 ± 0.05


0.26 ± 0.00

1.07 ± 0.06

1.4 ± 0.1

10.11 ± 0.36

4.47 ± 0.22


0.09 ± 0.00

0.63 ± 0.01

1.7 ± 0.1

4.39 ± 0.06

2.72 ± 0.14


0.39 ± 0.00

1.13 ± 0.00

1.9 ± 0.1

11.80 ± 0.58

8.71 ± 0.19


0.17 ± 0.00

0.79 ± 0.00

1.7 ± 0.1

7.86 ± 0.06

4.80 ± 0.33


0.30 ± 0.09

1.24 ± 0.02

2.1 ± 0.0

12.55 ± 0.01

8.05 ± 0.21


0.10 ± 0.00

0.42 ± 0.00

1.9 ± 0.0

1.19 ± 0.13

1.21 ± 0.01


0.34 ± 0.01

0.86 ± 0.00

1.5 ± 0.1

10.88 ± 0.07

6.70 ± 0.22


0.21 ± 0.00

0.89 ± 0.00

1.9 ± 0.1

8.73 ± 0.24

5.10 ± 0.18

EPA 10

0.21 ± 0.00

0.93 ± 0.02

1.9 ± 0.1

8.01 ± 0.04

5.30 ± 0.04

EPA 11

0.21 ± 0.00

0.95 ± 0.00

1.8 ± 0.0

8.54 ± 0.09

5.46 ± 0.07

Table 3. Regression coefficients of the predicted quadratic model of the intercept, linear, quadratic and cross-product terms for Total Flavonoid Content (TFC), Total Polyphenol content (TPC), Solids content (SC), DPPH and ABTS.

Model parameter












(1)% Etanol(L)






% Etanol(Q)






(2)Temp C(L)






Temp C(Q)






1L by 2L






*Significant at P < 0.05 (significant for a 95 % confidence level)Figure 2. Correlation between a) total flavonoids and antioxidant activity for ABTS, b) total flavonoids and DPPH, c) polyphenols and ABTS and d) polyphenols and DPPHCONCLUSIONS

RSM was successfully applied to optimize the AA of the extractive hydroalcoholic solutions from aerial parts of B. pilosa. The maximum predicted AA of 14.1 ± 0.2 and 9.0 ± 0.6 (TEAC/gwb), respectively by the DPPH and ABTS methodologies were obtained with an ethanol concentration of 62.7 % and 66.2 °C. In those conditions the extract presented a SC of 1.8 ± 0.7 %; TFC 0.385 ± 0.002 mg/gwb; TPC 1.219 ± 0.004 mg/gwb. Based on statistical analysis it is possible to say that the influence of ethanol concentration was higher than temperature, in the experimental range studied. It was observed a positive correlation between the TPC and TFC with the AA, and direct relationship between the DPPH method with polyphenols and ABTS with flavonoids.