AGRICULTURAL RESEARCH COMMUNICATION CENTRE

www.arccjournals.comAsian J. Dairy & Food Res.., 33 (4) : 276-284, 2014

doi:10.5958/0976-0563.2014.00617.4

OPTIMIZATION OF VISCOZYME-L ASSISTED EXTRACTION OFCOCONUT MILK AND VIRGIN COCONUT OIL

Ravindra Kumar Agarwal* and S. John Don Bosco

Department of Food Science and Technology,Pondicherry University, Puducherry, 605 014, India

Received: 02-06-2014 Accepted: 10-11-2014

ABSTRACTThe present work aimed to optimize the extraction of milk and oil from coconut by an aqueous

enzymatic extraction process using the enzyme Viscozyme-L. The combine effect of grinding time (2-4min), amount of Viscozyme-L (60-180FBGU) and incubation time (2-7h), were optimized usingResponse Surface Methodology. The selected method provides the best yield of coconut milk(73.88± 0.5%, w/w) and Virgin Coconut Oil (21.57± 0.4%, w/w) with percentage recovery of oil was86.14% of fat present in the fresh coconut kernel at grinding time (3min), the amount of enzyme(120FBGU) and incubation time (4.5h). The experimental results were significantly (P< 0.05)comparable to the predicted yield of coconut milk (73.33%) and oil (21.12%). A validation modelthat performed within the selected range of variation confirmed these results, microscopic image ofcell wall and particle distribution in coconut milk, suggested that the use of the Viscozyme-L treatmentcould enhance the extraction of oil.

Key words: Aqueous enzymatic extraction, Coconut milk, Optimization, Virgin coconut oil, Viscozyme-L

*Corresponding author’s e-mail: agarwalravi.ibt13@gmail.com

AbbreviationsFBGU Fungal -Glucanase Unitsw/w weight(g) /weight (g)AEP Aqueous extraction processAEEP Aqueous enzymatic extraction

processINTRODUCTION

In the present trend of focusing on theenhanced functional properties of foods in foodindustry, commercialization of the extractionmethods that could sustain the nutritional, functionaland sensory characteristics of extracted oils fromtheir sources, gains the importance among the recentresearchers. Industrially, copra oils are extractedfrom dried coconut using mechanical pressingmethods and solvent extraction processes. Thesolvent extraction process recovers the maximumamount of oil from coconut kernel, however, the needof further refining, bleaching and deodorization leadto the depletion of nutrients and environmentalpollution specific to the use of solvents (Mustakas,1980). Virgin Coconut Oil (VCO), the non-copra oil,

is extracted from fresh coconut kernel using physicaland natural processes such as centrifugation,fermentation, and aqueous extraction process (AEP)under ambient temperature (APCC, 2009) withoutfurther chemical treatment. Therefore, VCO retainsthe nutrient components especially Vitamin A, E andphenolic compounds that could enhance theantioxidant activity (Nevin and Rajamohan, 2006;Nevin and Rajamohan, 2009) to withstand theoxidative rancidity. Aqueous extraction process(AEP) to extract oil has been studied over the last50 years. AEP, wherein water is used as anextraction and separation medium, has regainedconsiderable interest during the past decade as anenvironmental friendly approach for extraction ofoil from oil sources. However, the oil recovery inAEP has not still reached the maximal efficiency thatwould be necessary for their economic viabilitybecause oil is localized in lipid bodies, which arebounded by a biological membrane (cell wall andcell membrane) (Agarwal and Bosco, 2013). Theextraction efficiency of AEP could be enhanced with

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the combined enzymatic action in AqueousEnzymatic Extraction Process (AEEP) to rupture thebiological membrane and hydrolyze the protein todestabilize the milk emulsion from vegetative cells ofcoconut kernel (Raghavendra and Raghavarao2010). Aqueous Enzymatic Extraction Processes isa sustainable extraction process involves in mildexperimental conditions to increase the yield of oil(Latif and Anwar 2009), with the sustenance ofnutrients and native flavor of coconut kernelacceptable to the consumers, and thus attracts theattention of many researchers (Sharma et al., 2002).In the past decades, AEEP has been attempted toextract oil from oil bearing materials such as peanut(Jiang et al., 2010), Soybean (Moura et al., 2008),Sesame (Latif and Anwar, 2011), Sunflower (Evonet al., 2009), Corn-gern (Moreau et al., 2004) andRapeseed (Zhang et al., 2007).

AEEP requires enzymatic system that canhydrolyze carbohydrates (starch, cellulose,hemicellulose and pectin) linked to the cell wallsupporting the stabilization of milk emulsion insideof vegetative cell. Viscozyme-L is a multi-activecarbohydrase enzyme, which can effectivelyhydrolyze the polysaccharides in plant cells andcleave the linkages within the polysaccharides matrixto liberate more intercellular components, such asfat, protein for the ease of the extraction of lipid bodies.AEEP can thus be carried out for the extraction ofVCO using Viscozyme L, as there are only few studieshas been reported on the extraction of VCO from freshcoconut kernel using Viscozyme L.

Response Surface Methodology (RSM) is aneffective tool for optimizing processes (Rustom etal., 1991) wherein the interaction among factors(independent variables) has to be tailored for desiredresponses (dependent variables). RSM considersinteraction among process parameters and optimizethem to a reasonable range, with the advantage ofthe relevant information in the shortest time withthe least number of experiments (Lee and Yusof,2006). The basic principle behind response surfacemethodology (RSM) analysis is to relate the observedvalue (response) to process parameters (independentvariables) using statistical methods (Myers andMontgomery, 2002). RSM has been widely reportedfor the optimization of extraction of oil usingenzymatic action as in peanut oil (Song et al., 2011),

olive oil (Aliakbarian et al., 2008; Meziane, 2013);virgin olive oil (Servili et al., 2003) soyabean oil(Campbell and Glatz, 2009), coconut oil (Sant’Annaet al., 2003) and rapeseed oil (Zhang et al., 2007;Hellner et al., 2010; Niu et al., 2012).

In the present study, grinding time, amountof Viscozyme-L and incubation time were selectedas independent variables and their interactive effecton the yield of coconut milk and recovery of VCOwas optimized using response surface methodology.The microstructural changes associated withenzymatic action on the cell wall of coconut kerneland the effect of grinding time on reducing the sizeof particles in coconut milk emulsion for the releaseof oil bodies were also examined.

MATERIALS AND METHODSFresh and mature (10-12 months old)

coconuts (Cocos nucifera L.) of East coast tall varietyprocured from a local garden of Pondicherry (India).Coconuts were randomly selected for eachexperiment. Liquid enzyme Viscozyme L (multienzyme complex containing a broad range ofcarbohydrases including cellulase, hemicellulase,arabanase, xylanase, and -glucanase) fromAspergillus sp. The activity of Viscozyme L is 120Fungal -Glucanase Units (FBGU) ml-1 (1 FBGU isthe amount of enzyme required to hydrolyze barley-glucan to reducing carbohydrates, with a reducingpower corresponding to 1µmol glucose/ min underthe standard conditions at 45°C, pH of 5 wasobtained from Sigma- Aldrich. All other reagents wereof analytical grade procured from Merck chemicals,Mumbai, India.

Aqueous Enzymatic Extraction processes(AEEP): For each experiment, the fresh grated whitecoconut kernel was ground with distilled water byfixed ratio of coconut kernel to water (1:1,w/w) in amixer grinder for different grinding time. Theresulting slurry was subsequently adjusted to theoptimum pH (5± 0.5) using 0.1N HCl andtemperature (45± 2°C) for maximum activity ofViscozyme L enzyme for 1h then Viscozyme L wasadded in different amount and incubated for differenttime in a shaking water bath. Thus, the obtainedslurry was filtered through double layer of cheeseclothto obtain milk emulsion, which was then centrifugedat 5000 rpm for 10 min to obtain coconut creamand discard the aqueous phase. For the extraction

278 ASIAN JOURNAL OF DAIRY & FOOD RESEARCH

of oil, the obtained cream was kept in freezer at 0oCfor 30 min, and after thawing at room temperature,it was centrifuged at 5000 rpm for 20min and thefloating oil layer was removed immediately aftercentrifugation. Hence, Viscozyme-L assistedextraction process was optimized using responsesurface methodology with a selected ratio of grindingtime, amount of enzyme and incubation time byscreening experiment for the maximum recovery ofmilk which in turn could result in maximum yield ofoil.

Extraction Yield: The percentage yield of coconutmilk (Y1), VCO (Y2) and percentage recovery ofextracted oil (R) were calculated using Eq.1, 2 and3 respectively.

Y1 (%) = (Weight of coconut milk / Weightof grated coconut kernel plus water added) × 100Eq. 1

Y2 (%) = (Weight of extracted oil by AEEP /Weight of fresh grated coconut kernel) × 100 Eq. 2R (%) = (A/ B) × 100 Eq.3

Where, A = Weight of oil extracted from freshcoconut kernel by AEEP B = Weight of oil extracted from fresh coconutkernel › Weight of oil extracted from wet residue bySoxhlet method (AOAC, 1997).

Selection of suitable extraction conditions: Thepreliminary phase of the study was conducted forthe selection of range of each factor based on yieldof milk and oil. The factors including grinding time(1-4 min), amount of Viscozyme L enzyme (20-200FBGU) and incubation time (1-10h) forsequential optimization at the constant ratio ofcoconut kernel to distilled water (1:1), pH (5) andtemperature (45°C) for the maximum yield of coconutmilk and VCO. Grinding time was first optimizedfollowing the optimization of the amount of enzymeat the optimized grinding time and then incubationtime at the optimized grinding time and amount ofenzyme. From the results of preliminary study, therange of grinding time (2-4min), amount ofViscozyme L enzyme (60-180FBGU) and incubationtime (2-7h) were found to significant on the yield ofVCO (data not shown). The interaction of theseindependent factors on the yield of coconut milk andVCO was determined through central compositerotatable design (CCRD) using response surfacemethodology.

Experimental design for AEEP: The centralcomposite rotatable design (CCRD) (Cochran andCox, 1992) was designed to study the interactiveeffect of three independent factors (grinding time,amount of Viscozyme L enzyme and incubation timefor Viscozyme L) at five different level (, 1, 0,+ 1, + ) on the responses (yield of coconut milkand VCO). The actual and coded value of the threeindependent factors and test designed aresummarized in Table 1. According to the design, thetotal number of experiment combinations were 20with eight (23) factorial points, six axial points (starpoints) and six repetition of experiments at the centralpoint. The experiments run in random order tominimize the effect of unexpected inconsistency inthe observed responses due to extraneous factors.The yield of coconut milk and oil was measured intriplicates in 20 different experimental runs and theirobservations were fitted to the following second orderpolynomial equation using multiple regressionprocedure (Liu et al., 2009).Y = o + 1 A + 2 B+ 3 C+ 11 A

2 + 22 B2+ 33C

2+12 AB + 13 AC+ 23 BC Eq.4

Where Y is the predicted response; o is theregression coefficient at center point, 1, 2 and 3

are the linear coefficients, 11, 22 and 33 are thequadratic coefficients, 12, 13 and 23 are the secondorder interaction coefficient, and A-grinding time,B-amount of enzyme, C-incubation time are theindependent variables. All experiments were carriedout in triplicates and randomized order to minimizethe effect of unexplained variable on the observedresponses due to extraneous factors.

Validation of the model: Optimal conditionsincluding grinding time, amount of enzyme andincubation time for the extraction of coconut milkand VCO were obtained using the predictiveequations of RSM. The yield of coconut milk andVCO were determined under optimal conditions. Theexperimental and predicted values were comparedin order to determine the validity of the model.

Particle size analysis: Particle size distribution ofcoconut milk emulsions with the effect of differentgrinding time (1-4 min) was determined using a laserlight scattering instrument (Malvern Zetasizer NanoS, Malvern Instruments Ltd, UK). The fixedrefractive index ratio (1.33) and viscosity (0.887cP)

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TABLE 1: Central Composite Rotatable Design (CCRD) matrix in actual value (coded value) for yield of coconut milk andVCO by Viscozyme-L assisted AEEP

Run A Grinding BEnzyme CIncubation Yield of Milk (%,w/w) Yield of VCO (%,w/w)

time (min) concentration(FBG) time(h) Observed Predicted Observed Predicted

1. 2 (-1) 60 (-1) 2 (-1) 67.26 67.20 15.92 15.692. 4 (+ 1) 60 (-1) 2 (-1) 68.82 68.31 16.51 16.253. 2 (-1) 180 (+ 1) 2 (-1) 67.84 67.89 17.12 17.384. 4 (+ 1) 180 (+ 1) 2 (-1) 70.04 70.18 18.05 17.555. 2 (-1) 60 (-1) 7 (+ 1) 68.43 68.20 17.48 17.876. 4 (+ 1) 60 (-1) 7 (+ 1) 69.23 69.09 18.24 17.867. 2 (-1) 180 (+ 1) 7 (+ 1) 68.07 68.49 17.18 17.328. 4 (+ 1) 180 (+ 1) 7 (+ 1) 70.59 70.56 16.81 16.929. 1.30 (-) 120 (0) 4.5 (0) 65.72 65.57 17.47 17.0810. 4.70 (+ ) 120 (0) 4.5 (0) 67.96 68.24 16.66 17.2211. 3 (0) 19. 1(-) 4.5 (0) 66.88 67.39 16.28 16.5112. 3 (0) 221.0(+ ) 4.5 (0) 69.59 69.21 17.19 17.1313. 3 (0) 120 (0) 0.30 (-) 71.03 71.22 17.01 17.3814. 3 (0) 120 (0) 8.7 (+ ) 72.44 72.38 18.89 18.6815. 3 (0) 120 (0) 4.5 (0) 72.38 73.33 20.84 21.1216. 3 (0) 120 (0) 4.5 (0) 73.1 73.33 21.08 21.1217. 3 (0) 120 (0) 4.5 (0) 73.49 73.33 21.10 21.1218. 3 (0) 120 (0) 4.5 (0) 73.6 73.33 21.12 21.1219. 3 (0) 120 (0) 4.5 (0) 73.87 73.33 21.02 21.1220. 3 (0) 120 (0) 4.5 (0) 73.56 73.33 21.57 21.12

(-1): indicates the lowest coded value; (0): indicates the mean level; (+ 1): indicates the highest coded value. á values round oftheir nearest integer.

were used to calculate the oil body size distributionin coconut milk at 25°C.

Scanning Electron Microscopy (SEM): Control(grated coconut chip) and Viscozyme L treatedcoconut chips were freeze-dried (-40°C) andmounted on an aluminum stubs using double sidesticky tape followed by coating employing a sputtercoater. SEM images illustrating the effect ofViscozyme L on rupturing the cell wall to release theoil bodies were captured employing a field emissionscanning microscope (Hitachi model S-3400N). Theimages were studied using secondary electrondetectors at an operating voltage of 5kV.

Statistical analysis: The Statistical software“Design- Expert” trial version 8.0.7.1 (State-EaseInc., Minneapolis, MN, USA) was employed forregression analysis and graphical visualizationrespectively. The quality of the fitted model wasdetermining by its F-value and determinationcoefficient of (R2). Statistical analysis was performedby Analysis of variance (ANOVA) for multiplecomparisons and to evaluate the adequacy of thegenerated mathematical models.

RESULTS AND DISCUSSIONFitting the model: The central composite designemployed for 20 experiments planned at different

combinations o f the signi f icant factors inquadratic model for aqueous enzymatic extractionprocess demonstrates in Table 1. It shows thepredicted and observed yield of coconut milk andVCO corresponding to the combined effect of allthe three significant variables in the specifiedranges. From the results of CCRD and regressionanalysis of experimental results, a second orderpolynomial equation was tested to estimate therelationship of variables on the yield of coconutmilk or VCO.

The following regression equation obtainedfor the yield of milk:Milk Yield (%) = (73.33) + (0.79 A) + (0.54B) +

(0.35C) + (0.30 AB) – (0.055AC) – (0.100BC) – (2.27A2) – (1.78B2) – (0.54C2) Eq.5

Where, A, B and C are the coded value ofindependent factors.

The following regression equation obtainedfor the yield of VCO:Oil Yield (%) = (21.12) + (0.040A) + (0.19B) +

(0.39C) –(0.099AB) – (0.14AC) – (0.56BC) – (1.40A2) –(1.52B2) – (1.09C2) Eq.6

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TABLE 2: Regression analysis (ANOVA) of CCRD for yield of coconut milk by Viscozyme-L assisted AEEP

Source SS1) DF MS F-Value p-value*

Model 124.91 9 13.88 55.86 0.0001A-Grinding time 8.62 1 8.62 34.68 0.0002B-Amount of enzyme 3.96 1 3.96 15.95 0.0025C-Incubation time 1.64 1 1.64 6.60 0.0280AB 0.70 1 0.70 2.80 0.1251AC 0.024 1 0.024 0.097 0.7614BC 0.080 1 0.080 0.32 0.5829A2 74.36 1 74.36 299.27 0.0001B2 45.57 1 45.57 183.42 0.0001C2 4.22 1 4.22 16.96 0.0021Residual 2.48 10 0.25Lack of Fit 1.09 5 0.22 0.78 0.6058Pure Error 1.40 5 0.28Correlation Total 127.40 19R2 0.98C.V. 0.71%Adequate precision 22.0181) SS: sum of squares; DF: degrees of freedom; MS: mean square; *p< 0.05 indicates significance

TABLE 3: Regression analysis (ANOVA) of CCRD for yield of VCO by Viscozyme-L assisted AEEP

Source SS1) DF MS F-Value p-value*

Model 71.37 9 7.93 45.23 0.0001A-Grinding time 0.022 1 0.022 0.13 0.7307B-Amount of enzyme 0.47 1 0.47 2.70 0.1317C-Incubation time 2.03 1 2.03 11.61 0.0067AB 0.078 1 0.078 0.44 0.5198AC 0.16 1 0.16 0.91 0.3625BC 2.50 1 2.50 14.24 0.0036A2 28.36 1 28.36 161.76 0.0001B2 33.28 1 33.28 189.79 0.0001C2 17.12 1 17.12 97.65 0.0001Residual 1.75 10 0.18Lack of Fit 1.46 5 0.29 4.99 0.0512Pure Error 0.29 5 0.059Correlation Total 73.12 19R2 0.976C.V. 2.28%Adequate precision 18.3171) SS: sum of squares; DF: degrees of freedom; MS: mean square; *p< 0.05 indicates significance

Where, A, B and C are the coded value ofindependent factors

The statistical signicance of the models wereevaluated by ANOVA as shown in Table 2 and 3.The model F-value of 55.86 for the yield of coconutmilk and 45.23 for the yield of VCO indicates boththe models were significant (P< 0.05) with a 0.01%chance for a large “Model F-Value” to occur due tonoise. In the case of coconut milk yield (Eq.5), thecoded value of the linear term of grinding time (A),amount of enzyme (B), and Incubation time (C) as

well as the quadratic term ( A2, B

2 and C

2) were

shown to be the significant (< 0.05) model terms,whereas in the case the yield of VCO (Eq.6), onlylinear term of incubation time (C), interactive termof amount of enzyme and Incubation time (BC) andquadratic term of all factors ( A

2, B

2 and C

2)

were

significant model terms (P< 0.05). Further the modelswere statistically analysed for being appropriate topredict their respective responses. The error analysisrevealed the non-significant lack of fit for both themodels to be good to fit. The values of determination

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ba

c d

e f

FIG 1: Response surfaces for percentage yield of Coconutmilk as a function of (a) grinding time and amount of enzyme,(b) grinding time and incubation time (c) amount of enzyme

and incubation time; for percentage yield of VCO as function of(d) grinding time and amount of enzyme, (e) grinding time and

incubation time, (f) amount of enzyme and incubation time.

coefficient (R2) of 0.980 for the yield of coconut milkand 0.976 for the yield of VCO were satisfactory tovalidate the models and point out that the model doesnot explain only 2% and 3% of the total variations inthe responses. Moreover, the lowest coefficient ofvariance (C.V.) for both the yield of coconut milk0.71% and VCO (2.28%) evinced the better precisionand reliability of the model (Firatligil-Durmus andEvranuz, 2010). Adequate precision measures thesignal to noise ratio. In the present study, adequatoprecision for the yield of coconut milk (22.02) andVCO (18.32) were greater than 4 indicating theadequacy of the models to navigate the design space.

The maximum yield of coconut milk andVCO predicted by regression quadric equation were73.33% (w/w) and 21.12% (w/w) respectively, underthe extraction conditions including grinding time of3min, amount of enzyme 120 FBGU and 4.5h ofincubation time. The percentage recovery of VCOwas found to be 86.14% of total fat content in freshcoconut kernel. The increase in the recovery of oilin the present study could be credited to theenzymatic action of Viscozyme-L as compared tothe recovery of oil (83.12%) observed in aqueousextraction process. This was higher than the oil yield(18.11%) obtained by (Krasaechol et al., 2011) usingViscozyme L treatment and did not found any changein quality. In earlier study, (Tano-debrah and Ohta,1997) recovered 65.5% of the oil from copra usingmixture of protease, cellulase and hemicellulose and(Che Man et al., 1996) recovered 73% oil from gratedcoconut kernel using mixture of protease, cellulase,-amylase and polygalactouranase. (Danso-Baoteng, 2011) investigate the effect of Viscozyme-L action on sunflower oil extraction using aqueousextraction process and reveals that Viscozyme-Ltreatment alone found to be the most efficient,producing oil yield of 34.05%, which represented61.46% of the total extractable oil. The effect ofinteraction between the independent variables onthe yield of coconut milk and oil was demonstratedby the three-dimensional response plot shown inFigure 1(a, b, c) and (d, e, f) respectively. In Figure1a and 1d, illustrated to be increasing up to moderatelevel of both the grinding time and amount of enzymefor the yield of coconut milk and oil were respectively.However, the higher level of enzyme amount wasinsignificant to increase the yield of both the coconutmilk and VCO whereas the higher level of grinding

time decreased the yield of coconut milk and VCO.A similar result between grinding time and incubationtime on the yield of coconut milk and VCO wasencountered as shown in Figure 1b and 1erespectively.

There was also a moderate interactive effectof amount of enzyme and incubation time onincreasing the yield of coconut milk and VCO asshown in Figure 1c and Figure 1f respectively.However, the slight increase in the yield of coconutmilk and rapid increase in the yield of oil due to themoderate interaction between incubation time andamount of enzyme could be observed from thevariation in the shape of the curve in Figure 1c and1f respectively.

Validation of the model: In order to maximizethe response and to validate the adequacy of thequadratic model, optimum extraction conditionswere estimated by the desirability method (Bezerra

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FIG 2: Particle size distribution of Viscozyme-L treated coconut milk emulsion for different grinding time; (a) 1 min (b) 2 min(c) 3 min (d) 4 min.

a b

FIG 3: Scanning electron micrographs of grated coconutkernel

(a) Untreated and (b) Viscozyme-L treated

et al., 2008).The prediction of the models wasvalidated through addi tional independentexperiments in triplicates under the optimumconditions. The experimental value of 73.88% (w/w) for the yield of coconut milk and 21.57% (w/w)for VCO were found in agreement to their respectivepredicted values. Therefore, the extraction conditionsfor coconut milk and VCO determined by RSM werepractical.

Particle size: The effect of grinding time (1-4 min)on particle size distribution in coconut milk emulsionfavorable to the cell rupture and increase in theefficiency of release of oil bodies from vegetative cellsis depicted in Figure 2. The average particle sizedistribution of milk emulsion was 1521nm, 929.2nm,667.7nm, and 567.5nm for 1, 2, 3, 4min of grindingtime respectively. From the results, the particle sizefrom 1521 to 667.7nm corresponding to the grindingtime for 1 to 3min was shown to increase the releaseof oil as depicted in response surface plot (Fig 1).The increase in oil recovery for smaller size particlescould be attributed to the diffusion of water-solublecomponents as well as enhanced the enzymediffusion rate to act more easily on substrates.However, excessive grinding (4min) favored theformation of stable emulsion of coconut milk andreduced the yield of oil.

Scanning Electron Microscopy (SEM): The effectof enzymatic action on the degradation of cell wallfor enhancing the release of oil bodies from vegetativecells could be observed from the changes inmicrostructure of Viscozyme L treated coconutkernel as compared to that of control (untreatedgrated coconut kernel) (Figure 3). Figure (3a) showedthe regular arrangement of cells enclosed with cellwall for control whereas the microstructure ofViscozyme L (complex of multi enzyme) treatedcoconut kernel was observed with the collapse ofcell wall structure due to the breakdown of complexarrangement of polysaccharides in cell wall as shownin Figure 3b. Similarly, (Womeni et al., 2008), studyaqueous enzymatic oil extraction from Irvingia

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gabonensis seed kernels and Scanning electronmicroscopy analysis revealed the partial action ofAlcalase and Pectinex, while Viscozyme was shownto completely disorganize the morphological structureof the cell.

CONCLUSIONThe present study concludes that the

maximum yield of coconut milk was dependent onthe linear and quadratic term of grinding time,amount of Viscozyme L enzyme and incubation time.However, the yield of VCO was dependent on linearterm of incubation time and quadratic terms of allthree independent factors as well as interactionbetween amount of enzyme and incubation time inaqueous enzymatic extraction process optimizedusing response surface methodology. The proposedquadratic regression model showed the optimumlevel of independent factors such as grinding time (3min), amount of Viscozyme L (120FBGU) and ofincubation time (4.5 h) for the maximum yield ofcoconut milk (73.33% w/w) and VCO (21.12% w/w). This was in agreement to the verified

experimental yield of coconut milk (73.88% w/w)and VCO (21.57% w/w). The maximum recoveryof VCO was about 86.14% of total fat content infresh coconut kernel. The extracted oil wastransparent like water and had the characteristicspleasant coconut aroma. Moreover, the SEM imageshowed the act ion of Viscozyme-L on thedegradation of cell wall of coconut kernel tomaximize the yield of milk as well as particle sizeanalysis also revealed that 3min of grinding washelpful for reducing the size of particles (667.7nm)in coconut milk emulsion. Therefore, in the presentstudy the addition of Viscozyme L can facilitate thepenetration of the cell wall to release the oil bodies,which results in the maximum yield of VCO.

ACKNOWLEDGEMENTThe authors are thankful to the Department

of Food Science and Technology, for generousfinancial support and Central InstrumentationFacility of Pondicherry University, India for theassistance in instrumental analysis in the support ofthe study.

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