Extraction process optimization for bioactive compounds in pomegranate peel

Extraction process optimization for bioactive compounds in pomegranate peel

Food Bioscience 12 (2015) 100–106 Contents lists available at ScienceDirect Food Bioscience journal homepage: www.elsevier.com/locate/fbio Extracti...

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Food Bioscience 12 (2015) 100–106

Contents lists available at ScienceDirect

Food Bioscience journal homepage: www.elsevier.com/locate/fbio

Extraction process optimization for bioactive compounds in pomegranate peel Ankita Sood, Mahesh Gupta n Food, Nutraceutical and Quality Control Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur 176 061, Himachal Pradesh, India

art ic l e i nf o

a b s t r a c t

Article history: Received 8 December 2014 Received in revised form 15 May 2015 Accepted 17 September 2015 Available online 24 September 2015

Pomegranate peel, a waste generated from fruit processing industry, is a potential source of active ingredients such as polyphenols that are known for their antioxidative properties. In this study, optimization of extraction conditions for bioactive compounds from pomegranate (Punica granatum L.) peels was done to investigate the effect of solid/solvent ratio (1:10–1:30), incubation time (15–45 min) and temperature (50– 70 °C) on polyphenol extraction using response surface methodology (RSM). The solvent concentration of 60% ethanol was used to extract the phenolic compounds in each experimental run. The experiment was designed to study the effect of extraction conditions on response variables such as total phenolic content (TPC), total flavonoids content (TFC), color index, percent reducing sugars and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity in each experiment run. The results of RSM revealed that regression model fitted significantly at pr0.01. Using optimization technique, solid to solvent ration of 1:30, temperature of 50 °C and time of extraction of 45 min gives highest yield of 68%, total polyphenolic content of 510 mg gallic acid equivalent/gm, total flavonoids content of 16.40 mg quercetin/gm, color index (ΔE) of 4.07, percent reducing sugars of 0.18 mg of invert sugar and DPPH radical scavenging activity of 24.54%. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Pomegranate peel Extraction Polyphenols Bioactive compounds Response surface methodology

1. Introduction Pomegranate (Punicagranatum L.; Punicaceae) due to its multifunctionality and nutritional benefit in the human diet has gained popularity in recent years. The fruit is rich in tannins and other biochemicals, particularly phenolics, which have been reported to reduce disease risk (Martınez, MelgarejoHernandezSalazar &Martınez, 2006; Jaiswal,Der Marderosian &Porter, 2010).The peel of pomegranate fruit constituting about 50% of the total weight is often discarded as waste (Al-Said, Opara& Al-Yahyai, 2009). However, it has been reported that fruit peel contains maximum amounts of bioactive compounds than the juice that possesses stronger biological activities (Li et al., 2006; Hajimahmoodi et al., 2008; Gözlekçi et al., 2011). Due to an increasing health consciousness among the consumers, there has been a dynamic increase in the demand for natural antioxidants, which has contributed to nutritional quality of products and this demand for antioxidants can be met by the extraction from natural sources. Plant phenolics are aromatic compounds responsible for the protection against various degenerative diseases and play a major antioxidative role in the diet (Rice-Evans et al., 1997). Food and agricultural waste generated during processing has emerged as an n

Corresponding author. Fax: þ91 1894230433. E-mail address: [email protected] (M. Gupta).

http://dx.doi.org/10.1016/j.fbio.2015.09.004 2212-4292/& 2015 Elsevier Ltd. All rights reserved.

ideal substrate for extraction of bioactive compounds. Several food and agro residues such as onion peels, potato, apple and olive tree leaves (Kaur and Kapoor, 2001), raspberry waste (Laroze et al., 2010) and other food processing waste have been assessed for extraction of polyphenolic compounds. Among these food processing residues, pomegranate peels, can be a potential feedstock for efficient recovery of bioactive and phytochemicals. Studies reveal that pomegranate peel extract had markedly higher antioxidant capacity than pomegranate juice against scavenging of hydroxyl radicals, superoxide anion and CuSO4 inhabitation (induced LDL oxidation) assays (Li et al., 2006). It has also been reported that pomegranate peel extracts possess a wide range of biological actions including antimicrobial activity (Mc Carrell et al., 2008; Endo,CortézUeda-NakamuraNakamura &Filho, 2010), anticancer activity (Ackland,Van De Waarsenburg &Jones, 2005; Kowalski, SamojednyPaulPietsz &Wilczok, 2005; Brusselmans,VrolixVerhoeven &Swinnen, 2005), anti diarrheal activity (Olapour, Mousavi,Sheikhzade,Hoseininezhad& Najafzadeh, 2009), anti-inflammatory (Yoshimura, Watanabe,Kasai,Yamakoshi&Koga, 2005) and anti-diabetic activities (Lansky & Newman, 2007; Althunibat et al., 2010), apoptotic and anti-genotoxic properties (Lin et al., 1999; Seeram et al., 2005). However, the bioavailability of antioxidant compounds may vary, depending upon different pomegranate cultivars, region and uses (Holland, Hatib &Bar-Yaakov, 2009). Therefore, the peel extracts have recently generated interest because of their potential use as a nutraceutical and

A. Sood, M. Gupta / Food Bioscience 12 (2015) 100–106

natural food ingredient (Qu,Pan&Ma, 2010). For the utilization of phytochemical in the preparation of dietary supplements, nutraceuticals, food ingredients, pharmaceutical or cosmetic products the important step is the extraction of bioactive compounds from plant materials. Generally, plant samples are treated by milling, grinding and homogenization, followed by air-drying or freeze-drying before carrying out the extraction process (Abascal, Ganora& Yarnell, 2005). Studies found that polyphenols compounds such as gallic acid, flavonols, ellagic tannins, anthocyanin, procyanidins and ellagic acid present in the fruit peel, exhibit various pharmacological activities (Lansky & Newman, 2007; Althunibat et al., 2010; Viuda-Martos,Fernandez-Lopez&Perez-Alvarez, 2010). However, solvent extraction technique due to its efficiency, ease of use and wide applicability is most commonly used procedure for the preparation of extracts from plant materials. However, yield of solvent extraction depends on various factors including the type of solvents with varying polarities, sample-tosolvent ratio, extraction time and temperature, as well as chemical composition and physical characteristics of the pomegranate part (Dai Jin & Mumper Russell, 2010). With this background, the present investigation was undertaken to optimize the extraction of polyphenols from by-products of local pomegranate cultivars.

101

Table 2 Design of experiment with coded and actual values. Run

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Coded values

Actual values

X1

X2

X3

X1

X2

X3

1.00 0.00  1.00  1.00  1.00 0.00 0.00 0.00 0.00 0.00 1.00 1.68 0.00 0.00 0.00  1.00 1.00 1.00  1.68 0.00

 1.00  1.68 1.00  1.00  1.00 0.00 0.00 0.00 0.00 0.00  1.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.00 1.68

1.00 0.00  1.00  1.00 1.00 0.00 0.00  1.68 1.68 0.00  1.00 0.00 0.00 0.00 0.00 1.00  1.00 1.00 0.00 0.00

30 20 10 10 10 20 20 20 20 20 30 36.8 20 20 20 10 30 30 3.18 20

50 43.2 70 50 50 60 60 60 60 60 50 60 60 60 60 70 70 70 60 76.8

45 30 15 15 45 30 30 4.8 55.2 30 15 30 30 30 30 45 15 45 30 30

X1 ¼Solid/solvent ratio, X2 ¼Temperature of extraction, X3 ¼Time of extraction.

2. Material and methods Fresh pomegranate was purchased from local market of Palampur (Himachal Pradesh, India) and processed to separate the peels followed by drying using hot air drier (MAC Instruments, New Delhi) and finally ground to a fine powder and stored in a cool and dry place. The processed pomegranate powder was further used for extraction and optimization in experimental design.

3. Experimental design (central composite rotatable design)

variables) due to transformation of data to standardized scores Z¼ X  X/S where X¼ dependent variable of interest; X¼mean of dependent variable of interest and S ¼standard deviation. For each standardized score, analysis of Variance (ANOVA) was conducted to determine significant differences among the treatment combinations. Also, data were analyzed using multiple regression procedures. This will study the effect of process variables such as solid/solvent ratio, temperature and time of extraction on response viz Total phenolic content (TPC), total flavonoids content (TFC), color index (ΔE), % reducing sugars and DPPH assay for its significant fitness in regression models. The standardized scores were fitted to a quadratic polynomial regression model by employing a least square technique (Gacula & Singh 1984; Wanasaundara & Shahidi, 1996). The model proposed for each response of Y was:

The Response Surface Methodology (RSM) is a widely adopted tool for the quality of optimizations processes (Nazni & Karunathara, 2011). The RSM, originally described by Box and Wilson (Box & Wilson, 1951), is effective for responses that affect many factors and their interactions. The central composite rotatable design (CCRD), was adopted to predict responses based on few sets of experimental data in which all factors were varied within a chosen range (Box & Hunter, 1957). The experiment consisted of 8 factorial runs, 6 axial runs and 6 center runs. The 3 independent variables were solid/solvent ratio (X1), temperature (X2) and time of extraction (X3). Each variable was set at 5 levels and a total of 20 experiments were designed whereby formulation15, namely the center-point formulation, was repeated 6 times. The independent variables and their variation levels are shown in Table 1. The levels of each variable were established according to literature information and preliminary trials. The outline of the experimental layout with the coded and natural values is presented in Table 2. Homogeneous variance is a necessary pre-requisite for (linear) regression models. Therefore, a reduction invariability within the objective response (dependent

where Y is the response, X1 ¼ solid/solvent ratio, X2 ¼temperature, X3 ¼time of extraction, β0 ¼intercepts, β1, β2, β3 are linear, β11, β22, β33 are quadratic and β12, β13 and β23 are interaction regression coefficient terms, respectively. Coefficients of determination (R2) were computed. The adequacy of the model was examined on the basis of three criterion such as F value, Lack of Fit (LoF) and adequate precision value. The optimization was done by numerically. Constraints were set to get the optimized coded value of the variable between the upper and lower limits of the variable. For every response, response surface plots were produced from the equations, by holding the variable with the least effect on the response equal to a constant value, and changing the other two variables.

Table 1 Independent variables and levels used for central composite rotatable design.

4. Proximate analysis

Independent variable

Solid/solvent ratio Temperature Time of extraction

Variables with their coded levels

X1 X2 X3

 1.68

1

0

1

3.18 43.2 4.8

10 50 15

20 60 30

30 70 45

1.68 36.8 76.8 55.2

Y = β0 + β1X1 + β2 X2 + β3 X3 + β11X12 + β22 X22 + β33 X32 + β12 X1X2 + β13 X1X3 + β23 X2 X3

The design of experiment was performed and phytochemical extraction were done using 60% ethanol as solvent with different variables i.e. solid/solvent ratio (1:10–3:10), temperature (50– 70 °C) and time of extraction (15–45 min). Different extracts obtained from each run of experiment were then used for further proximate analysis. TPC was determined according to the modified

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method of McDonald ,PrenzlerAntolovich andRobards (2001). TFC was estimated for each extract by standard method of Chang, YangWen andChern (2002). The hunter color values and color index was obtained using portable color lab (CR400, Konica Minolta). Percent reducing sugars were estimated using a standard method of Ranganna (1986), based on the principle that reducing sugars contain functional aldehyde group which reduces the copper(II) ions (blue color) of Fehling's solution into copper(I) ion (red precipitate). The test was performed with 5 ml of Fehling solution titrated with sample extract till appearance of brick red color. The DPPH assay evaluates the antioxidant potential through free radical scavenging activity of different experimental runs. The change in optical density of DPPH radical in methanolic medium was monitored at 517 nm according to modified method of Manzocco,Anese andNicoli (1998).

Table 3 ANOVA results of process variables against each response. Responses

Regression

Sum of square

F-value

P-value

Yield

Linear Quadratic Cross product Total Model Linear Quadratic Cross product Total Model Linear Quadratic Cross product Total Model Linear Quadratic Cross product Total Model Linear Quadratic Cross product Total Model Linear Quadratic Cross product Total Model

520.91 663.79 141.50 1326.20 15840 7201 2840 25880 29.589 51.579 0.597 81.764 262.678 200.053 24.617 487.348 0.13 0.023 0.019 0.17 26.939 525.26 90.59 642.796

8.03 10.23 2.18 6.81 9.9 4.5 1.77 5.39 3.03 5.28 0.06 2.79 35.68 27.18 3.34 22.07 19.61 3.45 2.81 8.62 0.55 10.76 1.86 4.39

0.005 0.002 0.153 0.003 0.002 0.03 0.215 0.007 0.080 0.019 0.979 0.063 0.00 0.00 0.064 0.00 0.00 0.060 0.094 0.001 0.658 0.002 0.201 0.015

TPC

TFC

ΔE

5. Statistical analysis

%RS

The analytical data obtained for different peel extracts were subjected to analysis of variance (ANOVA) using complete randomized design. The critical difference at p o0.05 was estimated and used to find significant difference if any.

DPPH

6. Results and discussion

Y1 (%Yield) = 42. 211 + 5. 924X1 − 1. 195X2 − 1. 271X3 + 3.

569X12

+ 5. 160X22 + 3. 922X32 + 2. 250X1X2 − 2. 250X1X3 + 2. 750X2 X3

80

Yield

70 60 50 40 40

Te 50 m pe 60 ra tu re

70 80

60

50

40

30

f eo Tim

20

10

0

n tio ac r t ex

Fig. 1. Effect of temperature and time of extraction on percent yield of pomegranate peel.

80 70

Yield

In the present investigation, the experimental design has been formulated to develop an empirical model thereby examining the interaction of different associated parameters responsible for the extraction of phenolic constituents present in pomegranate peels. This study optimized the extraction conditions in a multivariable system in order to evaluate the fitness of response function in experimental set up. In addition to the linear and quadratic effect of independent variables i.e. X1, X2, X3. Their interactions were also analyzed for regression coefficients in RSM study. However, fitness and adequacy of the model was judged by the coefficient of determination (R2) and lack-of-fit significance in the model. The closer the R2 value to unity, the better the empirical model fits the actual data (Fan,Han,Gu&Chen, 2007; Wang,YangDu&Yi, 2008). The coefficient of determination (R2) for different responses of the experiment was calculated to be 0.86, 0.829, 0.715, 0.952, 0.886 and 0.798 for percent yield (Y1), total phenolic content (Y2), total flavonoid content (Y3), color index (Y4), percent reducing sugars (Y5) and DPPH radical scavenging activity (Y6) respectively. The values of regression coefficients, sum of squares, F values and P values for coded form of process variables are presented in Table 3. Second-order polynomial equations were used to study the relation between the input process variables (X1, X2, X3) and their respective responses (Y1, Y2, Y3, Y4, Y5, Y6). The second-order polynomial coefficient for each term of the equation was determined through multiple regression analysis. The extraction yield of different experimental runs ranged between 40–68%. The F value of the model is 6.81 and lack of fit is significant. The quadratic model of all the independent variables has a positive effect on yield, while interaction model of solid/solvent ratio and time of extraction has a negative effect. Spigno and De Faveri (2007) also studied the influence of extraction conditions on % yield in case of grape stalks and Marc that correlated with our results. Regressions analysis was used in experimental data for obtaining second order polynomial equation as follows:

60 50 40 0

So lid

40

10

50

20

/s ol ve nt

ure rat e mp Te 60

30

70 40

80

Fig. 2. Effect of solid/solvent ratio and temperature on percent yield of pomegranate peel.

A. Sood, M. Gupta / Food Bioscience 12 (2015) 100–106

103

Table 4 Regression coefficient from quadratic model and their significance. % Reducing sugar

DPPH

Constant X1 X2 X3 X1  X1 X2  X2 X3  X3 X1  X2 X1  X3 X2  X3 R2

448.83 32.08  5.4 10.08 6.84  20.38  3.41 5.89 0.61  17.89 82.9%

17.2 1.45 0.17 0.19 1.56  0.55  0.695 0.18 0.115  0.1675 71.5%

13.9  3.2 2.89  0.775  1.288 0.876  3.355 0.305 0.495  1.655 95.2%

0.237  0.097 0.014 0.002  0.03 0.016 0.009  0.039 0.018 0.022 88.6%

22.45 1.26 0.477 0.395 0.513  5.776 0.886  1.065  0.118  3.190 79.8%

42.211 5.924  1.195  1.271 3.569 5.160 3.922 2.250  2.250 2.750 86%

The effect of solid/solvent ratio, temperature and time of extraction on the percent yield of extraction has been shown in Figs. 1 and 2. The TPC of different phytochemical extracts ranged from 310– 510 mg GAE/gm. The P-values were used as a tool for checking the significance of each coefficient, which in turn might indicated the interaction patterns between the variables (Hou & Chen, 2008). Smaller the P-value, more significant was the corresponding coefficient. This degree of significance for different models can be observed from Table 3. The developed model for TPC in the form of uncoded (actual) process variables is as follows (Table 4):

Y2 (TPC ) = 448.83 + 32.08X1 − 5.4X2 + 10.08X3 + −

3.41X32

6.84X12



20.38X22

550

500

TPC

ΔE

450 400 0 10 20 30 60

10

0

n tio rac t x 50 fe eo m i T 40

40

20

30

Fig. 4. Effect of solid/solvent ratio and time of extraction on TPC of pomegranate peel.

17.5 16.5 15.5

TFC

TFC

nt lve /so

TPC

lid So

Parameters Yield

14.5

+ 5.89X1X2 + 0.61X1X3 − 17.89X2 X3

13.5 12.5 40 50

t era mp Te

60 70

e ur

80

60

50

10

0

n tio ac r t ex of e Tim 40

30

20

Fig. 5. Effect of temperature and time of extraction on TFC of pomegranate peel.

25 24 23 22 21 20 19 18 17 16 15 0

TFC

The interactions of X1 X2 and X1 X3 have positive effect while X2 X3 exhibits a negative effect on TPC. The effect of solid/solvent ratio, temperature and time of extraction on the TPC has been shown in Figs. 3 and 4. It has been found that TPC decreases with increase in temperature and time of extraction. The similar study results also observed the same effect of temperature on TPC in potato peels (Sotillo,Hadley &Holm, 1994). On the other hand, solid/solvent ratio is directly proportional to TPC. According to Mohamed and Chang (2009) same trend may be due to higher amount of solvent that causes more dissolution of bioactive compounds. The total flavonoid content of different phytochemical extracts ranged from 15.8–17.8 mg quercetin/gm of sample. The F value of the model is 2.79 and lack of fit is significant. The quadratic model of solid/solvent ratio has positive effect on the TFC of extracts while interaction model of temperature and time of

470

420

40

10

nt lve /so

TPC

lid So

370

320 40

50

20

60

30

e tu r era p m Te

70 40

80

Fig. 6. Effect of solid/solvent ratio and temperature on TFC of pomegranate peel.

50

tu ra pe m Te

60

re

n tio ac r 40 t ex of e Tim 30

70 80

50 60

10

0

20

Fig. 3. Effect of temperature and time of extraction on TPC of pomegranate peel.

extraction has a negative effect. The generalized second-order polynomial model proposed for TFC is as follows:

Y3 (TFC) = 17.2 + 1.45X1 + 0.17X2 + 0.19X3 + 1.56X12 − 0.55X22 − 0.695X32 + 0.18X1X2 + 0. 12X1X3 − 0. 167X2 X3

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15

0.40

10

0.35

% RS

5

E

0 -5 0

So lid

10 20

/s

ol ve nt

30 40

50 60

40

30

0

0.25 40 0

50

m Te

f eo Tim

10

on cti t ra ex 20

0.30

tu ra pe

Fig. 7. Effect of solid/solvent ratio and time of extraction on ΔE of pomegranate peel.

60 70

re

Y4 (ΔE ) = 13. 9 − 3. 2X1 + 2. 89X2 − 0. 775X3 − 1. 288X12 + 0. 876X22 − 3. 355X32 + 0. 305X1X2

30

on

0.5 0.4 0.3 02 0.2 0.1 0.0

+ 0. 495X1X3 − 1. 655X2 X3

0 40

10

lid So

50

20

nt ve ol /s

The interactions of X1 X2 and X1 X3 have positive effect on ΔE. The effect of solid/solvent ratio, temperature and time of extraction on the ΔE has been shown in Figs. 7 and 8. The temperature has profound effect on color index, higher the temperature of extraction; greater is the value for ΔE. Different phytochemical extracts showed the reducing sugar content ranging between 0.407 and 0.02%. The interactions of solid/solvent ratio and temperature (X1X2) have a negative effect on % reducing sugars where as temperature and time of extraction (X2X3) exhibit a positive effect. The F value of the model is 8.62 and lack of fit is significant. Multiple regressions analysis was used in experimental data for obtaining second order polynomial equation as follows:

60

30

e tu r a r e mp Te

70 40

80

Fig. 10. Effect of solid/solvent ratio and temperature on % reducing sugars of pomegranate peel.

Y5 (%RS) = 0.24 − 0.097X1 + 0.014X2 + 0.002 X3 − 0.03X12 + 0.016X22 + 0.009X32 − 0.039X1X2 + 0.018X1X3 + 0.02X2 X3 The effect of solid/solvent ratio, temperature and time of extraction on the % reducing sugars has been shown in Figs. 9 and 10. The DPPH radical scavenging activity of different extracts ranged from 24.54–5.66. The coefficient of determination R2 was 79.8% of the regression model. The quadratic model X22 has a negative effect on the DPPH radical scavenging activity of experiment runs. On the other hand, the interaction model between all the three variables i.e. X1 X2, X2 X3 and X3 X1 has a negative effect on DPPH radical scavenging activity. Second-order polynomial equations for phytochemical extracts in the form of coded form for DPPH are as follows:

20

E

cti tra x 50 fe eo 60 m i T 40

80

10

Fig. 9. Effect of temperature and time of extraction on % reducing sugars of pomegranate peel.

% RS

Figs. 5 and 6 shows the effect of different variables (X1, X2, X3) on the TFC. The results indicate that extraction process is sensitive to the extraction time and temperature in the early stage. A similar trend has been observed by Pekic, KovacAlonsoandRevilla (1998) using different materials in kinetics study of extraction of proanthocyanidins from dry grape seeds. The ΔE of different phytochemical extracts ranged from 3.81 to 22.54. The F value of the model is 22.07 and lack of fit is significant. Results showed that both the linear as well as quadratic model of all parameters had significant effect on ΔE. The regression equation showing the mathematical relationship of process variables for ΔE is as follows:

20

10

Y6 (DPPH) = 22.452 + 1.26X1 + 0.477X2 + 0.395X3 + 0.513X12

0 0 40

lid So

10

50

20

nt lve /so

60

30

70 40

80

mp Te

e

tu r era

Fig. 8. Effect of solid/solvent ratio and temperature on ΔE of pomegranate peel.

− 5.776X22 + 0.886X32 − 1.065X1 × X2 − 0.118X1X3 − 3.19X2 X3 The effect of solid/solvent ratio, temperature and time of extraction on free radical scavenging capacity (DPPH) has been shown in Figs. 11 and 12. It has been observed that radical scavenging ability increased with the increase in temperature up

A. Sood, M. Gupta / Food Bioscience 12 (2015) 100–106

particular antioxidant properties present in pomegranate peels, which can be further explored for their potential application in food and pharmaceutical industry.

30

Conflict of interest

20

DPPH

105

Authors has no any conflict of interest. 10

Acknowledgment

0 40

e tu r era mp Te

50

60

20

0

on cti tra x 50 fe eo m i T 30

70

10

40

80

60

Authors are thankful to the Council of Scientific and Industrial Research and Director, CSIR-IHBT for providing the necessary facilities and continuous support to carry out research work. This manuscript bears the CSIR-IHBT publication no 3617.

References

Fig. 11. Effect of temperature and time of extraction on DPPH of pomegranate peel.

29 28

DPPH D

27 26 25 24 23 22 21 0 10

lid So

20

nt ve ol

/s

30 60

10

0

on cti a r t ex 50 of e Tim 40

40

20

30

Fig. 12. Effect of solid/solvent ratio and time of extraction on DPPH of pomegranate peel.

to 60 °C followed by a sharp decrease beyond 60 °C. Similarly, Liu, YangZhang andMajetich (2010) also observed the inhibition of DPPH radical scavenging activity at higher temperature in Folium eucommiae.

7. Conclusion The present study confirmed the advantages of RSM in optimizing the extraction conditions for highest yield and its functionality from pomegranate peels through novel and eco-friendly approach. The optimized extract of pomegranate peel gives maximum retention of bioactivity after extraction process of their biomolecule. Ethanol concentration of 60% was used as extraction solvent in each experimental run. Using the numerical optimization method, the process variables at solid to solvent ration of 1:30, temperature of 50 °C and time of extraction of 45 min gives maximum yield of 68%, TPC of 510 mg GAE/gm, TFC of 16.4 mg quercetin/gm, ΔE of 4.07, reducing sugar of 0.18% and highest free radical scavenging activity (DPPH) of 24.54% was achieved as optimum. Further works may be carried out under the optimum conditions to identify the phenolic compounds responsible for

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