Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process through Optimization by Response Surface Methodology

doi:10.4236/fns.2013.412155

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Food and Nutrition Sciences, 2013, 4, 1209-1220

Published Online December 2013 (http://www.scirp.org/journal/fns)

http://dx.doi.org/10.4236/fns.2013.412155

Open Access FNS

Antioxidants from Syrah Grapes (Vitis vinifera L. cv.

Syrah). Extraction Process through Optimization by

Response Surface Methodology

Youssef El Hajj1,2, Espérance Debs3, Catherine Nguyen2, Richard G. Maroun1*, Nicolas Louka1

1Unité Technologies et Valorisation Alimentaire, Centre d’Analyses et de Recherche, Faculté des Sciences, Université Saint-Joseph

de Beyrouth, Beirut, Lebanon; 2INSERM, U928, Technological Advances for Genomics and Clinics Laboratory, Marseille, France;

3Department of Biology, Faculty of Sciences, University of Balamand, Tripoli, Lebanon.

Email: *richard.maroun@usj.edu.lb

Received September 1st, 2013; revised October 1st, 2013; accepted October 8th, 2013

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accor-

ABSTRACT

In this work, optimization of phenolic compounds (PC) and monomeric anthocyanins (MA) extraction from Syrah (Sy)

wine grapes (Vitis vinifera L. cv. Syrah) using response surface methodology was conducted. The comparisons between

two extraction mixtures, Acetone/Water (A/W) as well as Methanol/Water (M/W) and the effects of three critical vari-

ables, Extraction Time (between 8 and 88 h), Extraction Temperature (between 1°C and 35°C) and Solvent Content (be-

tween 63% and 97%), on Phenolic Compounds Yield (PCY), Monomeric Anthocyanins Yield (MAY) and the DPPH

Free Radical Inhibition Potential (DFRIP) were studied. The highest PCY was obtained in 63% A/W solvent content

after 88 h incubation at 35°C. The highest MAY was acquired in 97% M/W solvent content after 8 h incubation at 17°C.

The highest DFRIP of the extract was attained using 97% A/W solvent content after 16 h incubation at 35°C. The low

cost of this process, on economic and environmental levels, could lead to interesting applications on an industrial scale.

It could be used to obtain bioactive phytochemicals from direct material or byproducts for either therapeutic or nutri-

tional purposes.

Keywords: Phenolic Compounds; Monomeric Anthocyanins; Antiradical Scavenging Potential; Extraction

Optimization; Grape; Time; Solvent and Temperature

1. Introduction

Importance of natural antioxidants for medical and food

sectors has been underlined by numerous works [1-15].

Nowadays, many studies report increasing interest in

wine grapes such as Syrah (Vitis vinifera L. cv. Syrah) as

source of powerful antioxidants, mainly phenolic com-

pounds (PC).

The aromatic ring, bound to a hydroxyl group, is the

basal structure common to all phenolic compounds [3].

This configuration allows radical scavenging potential

and gives phenolic compounds a multitude of bioactive

roles [4]. Furthermore, the high industrial value of these

molecules is well proven, especially due to food lipid

antioxidation [5]. Thus PC can be considered as added-

value phytochemicals of plant waste material, justifying

their isolation from the plant matrix by extraction.

Recovery of PC is commonly performed through a sol-

vent-extraction procedure but, currently, only ambiguous

data on the methods and conditions for extraction are

available and sometimes contradictory.

The aim of an extraction process should be to provide

a possible maximum yield of substances of the highest

quality (quantity of target compounds and antioxidant

potential of the extract). Just few works, on antioxidant

recovery from grapes, have targeted the optimization of

some process parameters [6]. The variables mostly stud-

ied have been: the type of extraction solvent or solvent

mixture, extraction time and extraction temperature [6].

Type of solvent has been the most investigated factor.

Acetone and methanol were reported as two of the best

*Corresponding author.

Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology

1210

solvents for extraction of PC and MA from plants [7-10].

Mixtures of solvents and water have revealed to be more

efficient in extracting phenolic constituents than the cor-

responding mono-component solvent system [11,12].

Time and temperature of extraction are important pa-

rameters to be optimized especially in order to minimize

energy cost of the process. Many authors agreed on the

fact that an increase in the working temperature favors

extraction and enhances both the solubility of the solute

and the diffusion coefficient. However, phenolic com-

pounds can be denatured beyond a certain range [2,11,

13]. More contradictories are the data available for incu-

bation time during extraction: some authors chose quite

short extraction times [11,13,14]; other long ones [2,9,

12,15,16].

After having optimized the extraction process of Total

Phenolic Compounds (TPC) and MA from Cabernet

Sauvignon (CS) grapes in a previous study [1], our ob-

jective in this work is to optimize the extraction process

of TPC and MA from Sy grapes in addition to the deter-

mination of FRIP (Free Radical Inhibition Potential) of

the extracts. This will provide us with a better under-

standing of the extraction process parameters impact on

the quality of the extracted PC and MA. In order to

achieve our goal, we used the response surface method-

ology (RSM) with a five-level, and three-variable central

composite design. We have noticed that literature lacks

optimization studies regarding the extraction process of

TPC and MA from grapes as well as FRIP analysis of the

obtained extracts. Therefore we determined the optimal

parameters (solvent type, water concentration in the sol-

vent system, extraction time and extraction temperature)

needed to give the highest TPC, MA yields and FRIP

from Sy grapes extracts. We draw a response surface plot

of the extraction kinetics corresponding to these parame-

ters and aimed to improve the extraction to a low cost

and energy depending procedure. A solvent extraction

method was proposed with simple, no complex machin-

ery and without expensive pre-treatments of the starting

material or excessive heating. We obtained a PC rich

extracts with a high free radical scavenging potential.

These extracts could be used as additives for food pres-

ervation, as well as in pharmaceutical, cosmetics and

nutraceutical industries.

2. Material and Methods

2.1. Reagents

The solvents used for the extraction of the samples were

pure water, acetone and methanol of analytical grade

from Scharlau (Barcelona, Spain) same as Ethanol

(Merck) used for DFRIP (DPPH Free Radical Inhibition

Potential) determination. The Folin reagent (Sigma Che-

mical Co., St. Louis, MO, USA) and sodium carbonate

(Fluka, Buchs, Switzerland) were used for the measure-

ment of the total phenolic compounds concentrations

using the Folin-Ciocalteu method, the calibration curve

was constructed with gallic acid (Sigma Chemical Co., St.

Louis, MO, USA). Potassium chloride (Fluka, Buchs,

Switzerland) and sodium acetate (Scharlau, Barcelona,

Spain) were used for total monomeric anthocyanin de-

termination by the pH-differential method. Resveratrol

(Sigma Chemical Co.) and DPPH (2,2-Diphenyl-picryl-

hydrazyl) reagent (Sigma Chemical Co.) were used for

DFRIP determination.

2.2. Sample Preparation

Grapes (Vitis vinifera L. cv. Syrah) were collected from

different crop areas located at different regions in the

Lebanese Bekaa valley. Harvesting took place during

summer/fall of 2010 (August till October). Grapes from

different regions, at different maturity stages and from

several localization on the vine were placed in a single

container. All batch was crushed to obtain a fine grape

paste (maximum particle size = 1 mm). The paste was

frozen at −80ºC until use. Each tube/experimental point

was subjected to a different parametrical pattern (Table

1). Extracts were then centrifuged (6000 g) and filtered

through RC membranes (0.2 µm). Samples were kept at

−80ºC ready to be analyzed.

2.3. Total Phenolic Compound Determination

Total phenolic compounds were determined according to

the Folin-Ciocalteu reagent with the Micro method pre-

viously described by Andrew Waterhouse (Department

of Viticulture and Enology, University of California,

Davis, USA). The absorbance of each solution was de-

termined at 765 nm against the blank (water). A calibra-

tion curve was created by plotting absorbance vs. con-

centration of the standards (solutions of different Gallic

Acid concentrations) and the total phenols concentrations

were determined in all samples. Phenolic Compound

Yield (PCY) was calculated by transforming milligrams

of Gallic Acid Equivalents (GAE) per liter (mg GAE/L)

into grams of GAE per 100 g of grape paste or fresh

weight (g GAE/100g) which is % GAE.

2.4. Total Monomeric Anthocyanin

Determination

Monomeric anthocyanins were measured by the pH-dif-

ferential method, which relies on the structural transfor-

mation of the anthocyanin chromophore as a function of

pH, and can then be measured using optical spectroscopy

[17]. Two dilutions of each sample were prepared using

he appropriate, previously determined dilution factor: t

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Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology

Open Access FNS

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Table 1. Central composite arrangement for independent variables and their responses for both extraction mixtures.

Run Variables levels (coded/uncoded) A/W M/W

1a X

2b X

3c PCY (%GAE)MAY (mg/100g)DFRIP (%)PCY (% GAE) MAY (mg/100g) DFRIP (%)

1 −1 (24) −1 (8) −1 (70) 0.73 99.36 63.35 0.54 104.87 54.61

2 1 (72) −1 (8) −1 (70) 0.85 82.72 45.91 0.58 94.48 45.68

3 −1 (24) 1 (28) −1 (70) 0.67 77.39 60.92 0.52 96.41 46.84

4 1 (72) 1 (28) −1 (70) 0.88 54.85 49.55 0.67 93.45 46.36

5 −1 (24) −1 (8) 1 (90) 0.72 91.52 57.28 0.56 115.71 56.8

6 1 (72) −1 (8) 1 (90) 0.89 82.78 40 0.61 105.43 42.95

7 −1 (24) 1 (28) 1 (90) 0.59 65.35 67.48 0.51 102.82 55.58

8 1 (72) 1 (28) 1 (90) 0.81 50.42 54.77 0.75 104.47 42.73

9 −α (7.63) 0 (18) 0 (80) 0.83 93.91 54.57 0.62 99.81 48.95

10 α (88.36) 0 (18) 0 (80) 0.83 56.78 65.81 0.66 92.15 44.96

11 0 (48) −α (1.18) 0 (80) 0.78 90.84 67.59 0.59 50.36 50.69

12 0 (48) α (34.81) 0 (80) 0.87 33.5 48.48 0.68 79.49 47.07

13 0 (48) 0 (18) −α (63.18) 0.84 81.02 56.08 0.56 90.44 51.34

14 0 (48) 0 (18) α (96.81) 0.84 80.22 76.7 0.64 111.39 47.42

15 0 (48) 0 (18) 0 (80) 0.8 82.78 54.02 0.64 102.88 49.07

16 0 (48) 0 (18) 0 (80) 0.78 80.85 56.49 0.64 103.22 49.48

17 0 (48) 0 (18) 0 (80) 0.85 79.03 54.64 0.65 102.76 46.8

18 0 (48) 0 (18) 0 (80) 0.82 81.93 50.93 0.65 104.24 48.45

PCY, Phenolic compounds Yields; MAY, Monomeric Anthocyanins Yields; DFRIP, DPPH Free Radical Inhibition Percentage; % GAE, Percentage Gallic Acid

Equivalent; A/W, Acetone/Water; M/W, Methanol/Water. aTime (h); bTemperature (˚C); cSolvent Content (%).

once with potassium chloride buffer at 0.025 M and pH

1.0 and the other with sodium acetate buffer at 0.4 M and

pH 4.5. The dilutions were equilibrated for 15 min. The

absorbance of each dilution was measured at the



vis-max

vis-max and at 700 nm against blank cell filled with dis-

tilled water. The absorbance (A) of the diluted sample

was calculated as follows:



700-max 700



H1 pH4.5

vis vis

AA AAA



  (1)

The monomeric anthocyanin pigment (MAP) concen-

tration in the original sample was calculated using the

following formula:





mg L

MAPMWDF 1000molALA  (2)

where MW and molA are the molecular weight and the

molar absorptivity, respectively of the pigment cyanid-

ing-3-glucoside used as reference; MW = 449.2 g/mole

and molA = 26900 mg−1·l−1·cm−1. DF is the dilution fac-

tor. Milligrams of MA (Monomeric Anthocyanin) per

liter of extract (mg/L) were then transformed into Mono-

meric Anthocyanin Yield (MAY) which is milligrams

per 100 grams of grape paste or fresh weight (mg/100g).

2.5. DPPH Free Radical Inhibition

Potential Determination

Antiradical potential of the extracts was assessed ac-

cording to the DPPH assay, which is based on the ability

of antioxidants to interact with the radical DPPH de-

creasing its absorbance at 517 nm. 1 mg of Resveratrol

was dissolved in 1 ml of Ethanol (Merck) to form the 1

mg/ml positive control stock solutions. The grape sample

extracts and the positive control solutions were diluted

with Ethanol (Merck) to obtain a concentration for each

sample and for the positive control at 100 µg/l. 3.9 mg of

DPPH powder (Sigma Chemical Co.) were dissolved in

200 ml methanol to form a 0.1 mM DPPH solution wich

can be stored at 4ºC. 315.2 mg of Tris-HCl were dis-

solved in 40 ml of water and the pH was elevated to 7.4

Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology

1212

with NaOH solution (10 mM) to obtain a Tris-HCl (50

mM, pH 7.4) buffer.

A mix of 50 µl of the different sample and positive

control dilutions, 450 µl of the Tris-HCl buffer and 1.5

ml of the DPPH solution were incubated for 30 minutes

at room temperature then the absorbance was read at 517

nm.

DFRIP of the original sample was calculated using the

following formula:







DFRIP 100

res sres

AAA  (3)

where Ares is the absorbance of the solution containing

DPPH after inhibition of its free radicals by resveratrol,

and As is the absorbance of the solution containing DPPH

after inhibition of its free radicals by the grape extract

sample.

2.6. Experimental Design

In this response surface methodology study, a rotatable

central composite design was used to evaluate the main

effects of the factors: extraction time (X1), extraction

temperature (X2), and solvent content (degree or per-

centage) (X3) and their interaction on total phenolic

compounds, monomeric anthocyannins yields and DPPH

Free Radical Inhibition Potential obtained from grapes

(Vitis vinifera L. cv. Syrah) using Acetone or Methanol

separately as extraction solvents. Eighteen experiments

(Table 1) were performed per extraction solvent mixture

including four experiments as the repeatability of the

measurements at the center of the experimental domain.

All the factors levels are reported in Table 2. Data

pertaining to three independent, and two response, vari-

able were analyzed to get a multiple regression equation:

33 23

11 11

nn nnnnmnm

nn nmn

Yb bXbXbXX

 

 

  (4)

where Y is the predicted response, Xn and Xm are the

coded values of the factors, b0 is the mean value of re-

sponses at the central point of the experiment; and bn, bnn

and bnm are the linear, quadratic and interaction coeffi-

Table 2. Independent variables and their levels used for

central composite rotatable design.

Independent variables SymbolCoded variable levels

−α −1 0 +1+α

Extraction time (h) X1 7.64 24 48 7288.36

Extraction temperature (˚C) X2 1.18 8 18 2834.82

Solvent degree (%) X3 63.18 70 80 9096.82

cients, respectively. Analysis of the coefficients of re-

gression models was carried out using an ANOVA table

to find the significance of each coefficient (Table 3).

This significance was illustrated using Pareto charts (Fig-

ure 1). The significance of Lack of fit for each extraction

model is shown in Table 4. The process was optimized

using response surface methodology for two independent

variables at a time. The third parameter was fixed at zero

level, the response surface graphs gave values of inde-

pendent variables allowing the optimization of the proc-

ess, considering that all the independent variable condi-

tions can be identified for maximum PCY, MAY yields

and DFRIP (Figures 2 and 3). The optimum experimen-

tal conditions were deduced from this study. Table 5

shows the best time, temperature and solvent degree

where the highest PCY, MAY and DFRIP are obtained

using A/W or M/W.

Table 3. Test of significance effect for each independent

variable, quadratic and interaction effect between variables.

(A parameter is significant if Pi < 0.05).

A/W M/W

(PCY)

(MAY)

(DFRIP)

(PCY)

(MAY)

(DFRIP)

X1a 0.04630.00020.0185 0.0001 0.00080.0022

X2b 0.77920.00010.5357 0.0007 0.00190.0439

X3c 0.70490.02340.0274 0.0013 0.00010.674

X12d0.74110.06170.3929 0.0134 0.01960.3028

X1X2e0.56620.07750.2022 0.0004 0.002 0.0659

X1X30.80410.04280.8683 0.0088 0.08910.0139

X22 0.68690.00090.8709 0.0079 0.00000.476

X2X30.46390.15370.0359 0.3081 0.10560.1887

X32 0.85390.32160.0222 0.0008 0.00080.271

aTime, bTemperature, cSolvent Content, dQuadratic effect of time, eInterac-

tion effect between Time and Temperature.

Table 4. Validation of the model showed by the responses

lack of fit values.

Lack of fit

Sum of squares Df f ratio P value

PCY 0.052 5 11.68 0.0351

MAY 135.83 5 10.38 0.0412 A/W

DFRIP930.545 5 34.82 0.0074

PCY 0.0119 5 72 0.0025

MAY 1260.14 5 557.79 0.0001 M/W

DFRIP54.558 5 7.85 0.0601

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Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology

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1213

Figure 1. Standardized Pareto charts. Analysis shown for PCY (a); MAY (b) and DFRIP (c) using A/W and for PCY (d);

MAY (e) and DFRIP (f) using M/W. The variables are: X1, time; X2, temperature; X3, solvent content; X1X1, X2X2 and X3X3,

quadratic effect of time, temperature and solvent content, respectively; X1X2, X1X3 and X2X3, interaction effect between time

and temperature, time and solvent content and temperature and solvent content, respectively. The columns/parameters ex-

ceeding the vertical bar are statistically significant with more than 95% of confidence.

Figure 2. PCY response surface plots. Three-dimensional expressions by response surface plots of PCY, using A/W ((a), (b),

and (c)) or M/W ((d), (e), and (f)) as extraction mixtures are shown. The three-dimensional graphs were plotted between two

independent variables (temperature and Solvent Content; (a), and (d), time and temperature; (b), and (e), and Time and Sol-

vent Content; (c), and (f)) while the remaining independent variable (time; (a), and (d), Solvent Content; (b), and (e), and

Temperature; (c) and (f)) was kept at its zero level. The colored areas at the bottom of each graph indicate the iso-responses

zones.

3. Results and Discussion

3.1. Optimal Yields and Antioxidant Activity

Response surface methodology was used to determine

the parameters for optimal levels of PC and MA yields

(PCY and MAY) and those for optimal antioxidant po-

tential of the extracts (DFRIP) (Equations (1), (2) and (3),

respectively). The corresponding independent variables

and their levels are shown in (Table 2, Equation (4)).

Using RSM, Table 1 gives the value of the three re-

Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology

1214

Figure 3. MAY response surface plots Three-dimensional expressions by response surface plots of MAY, using A/W ((a), (b),

and (c)) or M/W ((d), (e), and (f)) as extraction mixtures are shown. The three-dimensional graphs were plotted between two

independent variables (Temperature and Solvent Content; a, and d, Time and Temperature; (b), and (e), and Time and Sol-

vent Content; (c), and (f)) while the remaining independent variable (Time; (a), and (d), Solvent Content; (b), and (e), and

Temperature; (c) and (f)) was kept at its zero level. The colored areas at the bottom of each graph indicate the iso-responses

zones.

Table 5. Optimum experimental conditions for maximal extraction yields and values of the corresponding responses.

Optimum condition Extraction yield

A/W as extraction mixture M/W as extraction mixture

Time (h) Temperature (˚C) Solvent content (%) Time (h)Temperature (˚C)Solvent content (%)A/W M/W

PCY 88.36 34.8 63.18 88.36 34.81 94.88 0.94% GAE 0.82% GAE

MAY 7.69 9.13 63.18 7.64 16.51 96.5 107.53 mg/100g 123.94 mg/100g

DFRIP 16.06 34.82 96.82 7.64 5.72 96.82 76.37% 62.36%

sponses: PCY, MAY and DFRIP in A/W and M/W mix-

tures. The optimized levels of the parameters were as

follows: for PCY, 63.18% acetone in water, 88.36h of

extraction incubation and at 34ºC; for MAY, 96.5%

methanol in water, 7.64 h of extraction incubation and at

16.51ºC; for DFRIP, 96.82% acetone in water, 16.06 h of

extraction length and at 34.82ºC (Table 5).

In many works similar to this one, optimizations of the

PC extraction parameters (extraction time [12,15-18],

extraction temperature [2,19] and extraction solvent [20])

were done using different plant matrices. We looked to

compare response optimums as an attempt to relate our

study to previous ones, even though a complete correla-

tion will not be possible due to differences in the starting

material, the diversity of the PC in each plant as well as

the antioxidant profile of the extract and the change-

ability of the extraction process. Our work showed rela-

tively high PCY of 0.94% GAE of fresh weight (grape

paste), fair yields of MA: 123.94 mg/100g and our ex-

tract showed high antioxidant potential translated in a

higher optimum level of DFRIP: 76.37% (Table 5). In

literature, total PC yields were of lower levels compared

to our study, as Spigno and De Faveri, (2007) [2] ob-

tained a PCY of 0.27% GAE from powdered red grape

pomace and of 0.33% GAE from red grape stems, Re-

villa et al. (1998) [8] obtained 0.51% GAE of PCY from

fresh grapes and 0.25% GAE from fresh red grape skins,

Cruz et al. (2004) [19] got 0.22% GAE of PCY from

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Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology 1215

distilled grape pomace and Benvenuti et al., (2004) [21]

yielded 0.88% GAE from black berries. MAY in litera-

ture were very close to ours; Revilla et al. (1998) [8]

obtained 111 mg/100g from entire fresh grapes, and Fan

et al. (2008) [22] had 152 mg/100g from dried sweet

potato. In a previous work, antioxidant potential of ex-

tracts obtained (by classic or carbon maceration) did not

exceed 50% [16].

3.2. Response Surface Model Design

The experimental values of PCY, MAY and DFRIP ob-

tained in A/W or M/W are shown in Table 1.

The values for the coefficient of determination (R2)

were 46.83%, 97.1%, 29.71%, 81.51%, 64.06% and

78.11% for the experimental design of PCY, MAY and

DFRIP in A/W mixture and of the same constituents in

M/W mixtures, respectively. The value of R2 for MAY

(0.971) extracted by A/W mixture, is very close to 1, and

indicates a high degree of correlation between the ob-

served and predicted values. Whereas the values of R2 for

PCY and DFRIP in M/W mixture are reasonably close to

1, indicating reasonable agreement of the corresponding

models with the experimental results.

A significant lack of fit (P < 0.05) was found in all

models corresponding to PCY and MAY by A/W and

M/W extractions and to DFRIP in A/W extraction condi-

tion. This shows no fit of all five models to real condi-

tions, which means that the manipulator errors are negli-

gible compared to the errors induced by the model (cal-

culated from the repetitions at the field center), in con-

trast no significant lack of fit (P > 0.05) was in the model

corresponding to DFRIP in M/W extraction condition.

From all the above we can assume that the used model is

considered as valid (Table 4).

3.3. Yields and Antioxidant Activity Are

Affected by Parametrical Variation

Table 3 shows the significance of each parameter when

using the ANOVA test for the analysis of the regression

models coefficients. The effect of a parameter is consid-

ered as statistically significant when histograms cross the

vertical line, translating the threshold of significance of

95%. According to Figure 1 and Table 3, and in the field

of variation of the process parameters, the results showed

that Time had a significant linear (X1) effect (P < 0.05)

on PCY, MAY and DFRIP after extraction by both A/W

and M/W mixtures. On another side, Temperature had a

significant linear (X2) effect on PCY, MAY and DFRIP

in the presence of Acetone in the extraction mixture and

on MAY in presence of A/W. Solvent content (X3) linear

effect (P < 0.05) was significant on MAY extracted by

both A/W and M/W mixtures, on PCY extracted by M/W

and on DFRIP extracted by A/W.

The levels of independent variables for optimal extrac-

tion conditions of PC, MA and for DFRIP in A/W or

M/W extraction mixtures were expressed in three dimen-

sions using response surface graphs plotted between two

independent variables while the remaining third inde-

pendent variable was kept at zero level (Figures 2-4).

3.3.1. Total Phenolic Compounds

Response surface plots show the effect of each parameter

on the responses (Figures 2-4). From the shape of the

surface plot it can be noticed that Time affected signifi-

cantly PCY, in both Acetone (A/W) (Figures 2(b) and

(c)) and methanol (M/W) (Figures 2(d), (e), and (f)) ex-

traction systems. A significant increase of PCY with the

extraction length is translated into a clear steepness in the

inclination of the plot ascent in Figures 2(b), (c) and (f).

Thus, the extraction time parameter has a positive and

significant effect on PCY. Some studies in literature were

in accordance with what we found. Pekic et al. (1998)

[15] noticed an increase in the yield of a group of the PC,

the proanthocyanidins with the increase of extraction

time to 24 h after undergoing an extraction from dried

seeds of grape pomace, the same increasing effect in

Spigno et al. (2007) [6] was also observed on powdered

grape pomace total phenolics after 24 h of extraction

process. Lapornik et al. (2005) [16] observed an increase

in total phenolics with the extraction time from grape

pomace obtained after classic maceration using just water

or 70% ethanol as extractants, but also (and in disagree-

ment with what we found) a decrease in total phenolics

from this same grape material using 70% methanol as

extractant was noticed.

Throughout literature, temperature is shown to be one

of the most critical variables to be affecting the release of

phenolic compounds from grape matrix [2,6,9,19], due to

an increase in the coefficient of diffusion and solubility.

In accordance most authors found an increase in the

amount of total extracted phenols [2,13] while heating. In

contrast, in the range of our study measurements a sig-

nificant effect (P < 0.05) of temperature variation on

PCY was shown in M/W extraction mixtures (Figures

2(d) and (e)), but not in A/W (Figures 2(a) and (b)). The

corresponding plots (Figures 2(a) and (d)) are dome

shaped, showing that at the fixed time level (48 h) a

maximal value of PCY has been reached in the range of

our measurements, and that an increase in the extraction

temperature will increase PCY until the value of 0.85%

GAE and 0.65% GAE, in acetonic (Figure 2(a)) and

methanolic extracts (Figure 2(d)).

The effect of solvent content in water on PCY showed

to be statistically significant (P < 0.05) in A/W (Figures

(a) and 2(b)) and M/W (Figures 1(d) and 2(e)). In ac- 1

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Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology

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1216

Figure 4. DFRIP response surface plots. Three-dimensional expressions by response surface plots of DFRIP, using A/W ((a),

(b), and (c)) or M/W ((d), (e), and (f)) as extraction mixtures are shown. The three-dimensional graphs were plotted between

two independent variables (Temperature and Solvent Content; (a), and (d), Time and Temperature; (b), and (e), and Time

and Solvent Content; (c), and (f)) while the remaining independent variable (Time; a, and d, Solvent Content; (b), and (e),

and Temperature; (c) and (f) was kept at its zero level. The colored areas at the bottom of each graph indicate the iso-re-

sponses zones.

cordance with literature, our results showed that the op-

timal PCY were obtained using A/W and not M/W as the

extraction mixture.

Literature studies on extractions from grape materials

showed that aqueous acetone was a better mixture for

extracting PC (which had an overall unpolar character)

than aqueous methanol [23].

3.3.2. Monomeric Anthocyanins

Figures 3(b), (c), (e) and (f) show plots with a clear

steepness in the inclination of their profile, which can be

translated into a significant decrease of MAY with the

extraction time. Thus this parameter had a negative sig-

nificant effect on MAY.

Lapornik et al. (2005) [16] showed a decrease in total

anthocyanins with water extractions after a long extrac-

tion time similarly to what appeared in our study, but an

increase in anthocyanins was noted using 70% ethanol

and methanol as extractants.

In accordance to what was said previously, we noticed

a statistical (P < 0.05) and negative influence of tem-

perature on MA yields in both A/W (Figures 3(a) and

(b)) and M/W (Figures 3(d) and (e)) mixtures; in fact,

the corresponding plots showed a significant tendency in

MAY towards higher temperatures (35ºC - 37ºC). Our

samples subjected to extraction temperature between 1ºC

and 17ºC showed higher MAY than samples extracted at

temperatures around 35ºC. This could be explained by

conformational changes or degradation of monomeric

anthocyanins at higher temperatures or by color change

and co-pigmentation, which is an interaction and cou-

pling of the anthocyanins with other components making

them trapped and undetectable by usual tests.

We chose in our study to consider the temperature

margins in which were extracted, at the same time, both

grape compound groups (PC and MA) without subjecting

them to degradation. In the same context, literature

showed temperature to be one of the major degradation

factors of the anthocyanins along with oxygen and photo

degradation [24]. In addition to this and according to

Vatai and Skerget, (2009) [25] a relatively low extraction

temperatures (20ºC) were more suitable than high tem-

perature (60ºC) for extracting higher MA yields from

Cabernet and Merlot grapes.

Zhou and Yu [23], showed that methanol was better

than acetone or water for MAY extraction [8,16]. In ac-

cordance with this observation, our results showed that

the optimal MAY was obtained using M/W and not A/W.

MAY was affected significantly (P < 0.05) by both the

acetone and methanol contents in water (Figures 1(b)

and (e), Figures 3(a) and (d)). According to literature,

MA are better extracted using more polar solvents like

Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology 1217

methanol than by other organic solvents. It is also well

described that methanol and alcoholic solvents are better

extractants than water for anthocyanins. Our study

showed a negative effect of acetone content in the A/W

mixture on the MA yields (Figures 3(a), and (c)), mean-

ing that MA are more affine to the water part of the mix-

ture, in accordance to the previous assumptions. The

same comment could be given for the positive effect of

methanol content on MAY, in the M/W mixture (Figures

3(d) and (f)). We can conclude that the affinity of sol-

vents to MAY is as follows: methanol is the best, fol-

lowed by water then acetone.

3.3.3. Antioxidant Activity

Figures 4(b), (c), (e) and (f) show plots with a clear

steepness in the inclination of their profile, which can be

translated into a significant decrease of DFRIP with the

extraction time. Thus this parameter had a negative sig-

nificant effect on the antioxidant activity.

In addition to that and in contrast to our study other

authors described an increase in the antioxidant potential

of PC extracts [16]. In those works these increases were

described after undergoing extraction not longer than 2 to

3 h. The short times of extraction might explain this be-

havior. The very long extraction time (up to 88 h) used in

our study, might be responsible for the loss in the anti-

oxidant potential translated by the decrease in DFRIP. It

is well known that at this level we can observe, in func-

tion of time, a competition between two phenomena;

extraction v/s oxidation.

Additionally, temperature showed a significant and

negative effect on the antioxidant potential (DFRIP) of

the extract in the presence of methanol as extraction

mixture (M/W) (Figures 4(d) and (e)). This loss of anti-

oxidant potential could be explained by a degradation

process of the phenolics taking place in the presence of

methanol at higher extraction temperatures. In literature

and in disagreement with what we found, some studies

showed an increase in the antioxidant potential of the

extract with higher extraction temperatures [13], while

others showed the exact decreasing effect [16]. This di-

chotomy in the results could be explained by a double

effect that temperature could produce on PC; first it

could promote a better extraction of antioxidants from

the matrix, and second could cause degradation of those

antioxidants, decreasing by this the overall antiradical

potential.

Some authors show that antioxidant potential of the

extract was better preserved in the presence of unpolar

solvents like acetone [26,27]. Higher values were noticed

as compared to those obtained by Rajha et al. (2013) [28]

for phenolic compounds water extracts. In accordance

with this, our results showed that DFRIP optimal level

was obtained with Acetone (Table 5).

3.4. Simultaneous Response Optimization

In the previous section of this work we designated the

parameters in order to extract optimum yields of PC, MA

and the best DFRIP of the extract. In this part we show

simultaneously, by the desirability function, how the

three responses could be affected by the parameters

(Figure 5). It can be seen that PCY, MAY and DFRIP

concentric circles, converge mostly towards different

regions in the superposition plots. Opposite localization

of the optimum PCY, MAY and DFRIP are observed on

most of the plots of Figure 5. This emphasizes that PC

need long extraction time to reach a maximum yield

while on the contrary, MA are extracted in an optimal

way in the first hours of the extraction process. Plots (a),

(d), (c), and (f) also show how PCY are maximized at a

high range extraction temperature, while MAY and

DFRIP showed best values at low extraction tempera-

tures. High methanol content in the solvent mixture (near

100%) gave the best values for all three responses (Fig-

ures 5(d)-(f)). This was the case as well for DFRIP in

A/W but low Acetone percentages in water (near 63%)

were better for PCY and MAY (Figures 5(a)-(c)). This

divergence in optimal parameters for each response

shows that PCY, MAY and DFRIP cannot be maximized

in the same extract. Nevertheless, we can guide the ex-

traction process to obtain the best yield or the best anti-

oxidant potential as the plots show (Figure 5, green

marks). Thus, the parameters will be compromised be-

tween PCY, MAY and DFRIP. In some specific cases,

these parameters could be favored towards PCY, MAY

or even DFRIP depending on the final application of the

extracted compounds.

4. Conclusions

Hereby, we attempted to explore the field of antioxidants

and their extraction from grapes. Keeping in mind the

variability of the techniques and the grape matrices due

to soil and season climate, we proposed here a model that

could be applied for industrial purposes. Our major find-

ings lead us to suggest that extracting or optimizing the

extraction of phenolic compounds and antioxidants like

anthocyanins from Sy grapes can be done easily, without

heavy or expensive machinery and could be environ-

mentally friendly. We propose as well that multiple re-

sponse optimizations could be used to define the opti-

mum area which can lead to choose the convenient ratio

between PCY and MAY in addition to favoring between

yields of antioxidants and the antiradical potential of the

extract. We showed that aqueous Acetone is better than

Methanol and/or water in extracting total PC and in pre-

serving the antioxidant potential of the extract, but

Methanol seemed to be more suitable in the extraction of

MA followed by water than Acetone. In parallel, the ex-

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Antioxidants from Syrah Grapes (Vitis vinifera L. cv. Syrah). Extraction Process

through Optimization by Response Surface Methodology

Open Access FNS

1218

Figure 5. Desirability analysis. Superposition plots, showing the best experimental parameters (Time, Temperature, and Sol-

vent Content) that maximizes PCY, MAY and DFRIP at the same time are shown. In A/W ((a), (b), and (c)) and M/W ((d), (e),

and (f)) extraction mixtures, the contours graphs were plotted between two independent variables (Temperature and time;

(a), and (d), Solvent Content and Time; (b), and (e), and Solvent Content and Temperature; (c), and (f)) while the remaining

independent variable (Solvent Content; (a), and (d), Temperature; (b), and (e), and Time; (c), and (f)) was at its zero level.

The green mark shows the “middle way” parameters that compromise between PCY and MAY.

traction time effect showed to be significant on the grape

phenolic yields; MA were fast to extract from Sy grapes,

and 8 h as extraction time gave higher yields than longer

time, while extraction yielded the maximum of PC after

88 h. Longer extraction times contributed in decreasing

the antioxidant properties of the extract. We demon-

strated as well that the extraction temperature had a sig-

nificantly negative effect on the MA extraction and on

the antioxidant potential of the extract and low extraction

temperature (10ºC) yielded more MA and gave more an-

tioxidant potential to the extract than high extraction

temperature (35ºC).

Finally, complementary studies are needed in order to

solve the problem concerning preservation of the anti-

oxidant capacity of a grape extracts, and to be able to

fully understand the effect of parameters such as extrac-

tion time, temperature and solvent content on the extrac-

tion process. Future work should take into consideration

larger intervals of the extraction parameters, in order to

be able to enhance the quantity and the quality of the

extracted compounds. All the combined data obtained

through an optimal extraction strategy could lead to the

production of pure natural antioxidant molecules. These

could be used for the quality improvement of several

industrial products such as cosmetics, pharmaceutics and

agrofood.

5. Acknowledgements

This project was funded by the Research Council of

Saint-Joseph University-Lebanon (Project FS20). The

authors are grateful to Joseph Yaghi and Nada El Darra

for technical assistance.

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