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Renewable Energy 141 (2019) 847e857

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Renewable Energy

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Co-immobilization of Rhizomucor miehei lipase and Candida antarcticalipase B and optimization of biocatalytic biodiesel production frompalm oil using response surface methodology

Mansour Shahedi a, Maryam Yousefi b, *, 1, Zohreh Habibi a, **, Mehdi Mohammadi c,Mohammad Ali As'habi d

a Department of Pure Chemistry, Faculty of Chemistry, Shahid Beheshti University, G.C., Tehran, Iranb Nanobiotechnology Research Center, Avicenna Research Institute, ACECR, Tehran, Iranc Bioprocess Engineering Department, Institute of Industrial and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology(NIGEB), Tehran, Irand Department of Phytochemistry, Medicinal Plants and Drugs Research Institute, Shahid Beheshti University, G. C., Evin, Tehran, Iran

a r t i c l e i n f o

Article history:Received 7 July 2018Received in revised form24 February 2019Accepted 9 April 2019Available online 12 April 2019

Keywords:BiodieselCo-immobilizationLipaseResponse surface methodology

* Corresponding author.** Corresponding author.

E-mail addresses: M.yousefi@ari.ir (M. Yousefi), Z_1 These authors contributed equally to this work.

https://doi.org/10.1016/j.renene.2019.04.0420960-1481/© 2019 Elsevier Ltd. All rights reserved.

a b s t r a c t

Lipases from Candida antarctica B (nonspecific lipase) and Rhizomucor miehei (1,3-specific lipase) weresimultaneously immobilized on epoxy functionalized silica gel under mild conditions. The resultsshowed rapid and simple immobilization of 4e15mg of CALB:RML (different ratios 4:1, 2:1, 1.5:1, 1:1) on1 g of support after 6 h. The thermal stability of derivatives and also their stability in methanol weregreatly improved compared to the single immobilized enzyme. All the derivatives were also used tocatalyze the transesterification of palm oil with methanol to produce fatty acid methyl esters (FAMEs).Response surface methodology (RSM) and a central composite rotatable design (CCRD) was used to studythe effects of five factors, reaction temperature, methanol/oil ratio, reaction time, t-butanol concentra-tion and CALB:RML ratio on the fatty acid methyl esters (FAME) yield. A quadratic polynomial equationwas obtained for methanolysis reaction by multiple regression analysis. The optimum combinations forthe reaction were CALB:RML ratio (2.5:1), t-butanol to oil (39.9 wt%), temperature (35.6 �C), methanol:oilratio (5.9), reaction time 33.5 h. FAME yield of 78.3.5%, which was very close to the predicted value of75.2%, was obtained. Verification experiment confirmed the validity of the predicted model.

© 2019 Elsevier Ltd. All rights reserved.

1. Introduction

Fossil fuels have been used for many years as themost dominantfuel for motor engines. However the serious crisis of declining fossilfuel resources and environmental pollution have led to a search fornew renewable biofuels and finding novel alternative fuel sources.Biodiesel (monoalkyl esters of long-chain fatty acids) has a greatpotential as an alternative diesel fuel [1].

Biodiesel is produced by alcoholysis of renewable lipid sources,such as vegetable oil or animal fat. From an environmental point ofview it shows several advantages over conventional fuel: biode-gradability, renewability, reduction of greenhouse gas emissions,

habibi@sbu.ac.ir (Z. Habibi).

reduced CO, hydrocarbons, NOx and particles in exhaust emissionand therefore, significantly reduces pollution, also biodiesel can bepumped, stored and handled using the same infrastructureemployed for compression ignition engines with little or nomodifications.

Conventionally the synthesis of alkyl esters is accomplished bychemical transesterification from which, short reaction times andhigh yields are obtained. Though the yield is high, the process hasmany disadvantages such as high energy requirements, difficulty inthe transesterification of triglycerides with high free fatty acidcontent, pretreatment of the substrate when water is present anddifficulties in the recovery of catalyst and glycerol [2].

Enzymatic approaches serve as a promising technology forbiodiesel production due to the mild reaction conditions, easy re-covery of product, being environmentally friendly and lowdemanding on raw materials compared with chemical methods. Incontrast, biocatalysts allow the synthesis of specific alkyl esters,

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857848

easy recovery of the glycerol, and the transesterification of tri-glycerides with high free fatty acid content.

The most important features of the biocatalyst is efficiency andcompatibility with the environment. Enzyme as a catalyst becomesmore important every day due to the mentioned features. The mostcommonly used enzymes for biodiesel production are lipases. Li-pases (triacylglycerol acylhydrolase, EC 3.1.1.3) are part of the familyof hydrolases that catalyze hydrolysis of a triglyceride into di-glycerides, monoglycerides, fatty acids, and glycerol.

However, the high cost of commercially available enzymeslimits the enzymatic production of biodiesel on an industrial scale.On the other hand, poor solubility of methanol in oil and adsorptionof glycerol onto the lipase lead to the accumulation of methanolaround the enzyme, resulting in the inactivation of the enzyme [3].To lower the cost of the enzymatic process, immobilized enzymesare promising. Enzyme immobilization increase stability, recoveryand reusability of the enzymes.

Development co-immobilized enzyme complex, is very usefulfrom the viewpoint of the environment and the economy [4e6].Co-immobilization of enzymes has many benefits such as: allowthat product of an enzyme directly transferred to the co-immobilized following enzyme, This means that the first enzymeproducts is reactant second enzyme and those short diffusionaldistances accelerate the speed of the reaction.

To date several reports have been published on co-immobilization of enzymes, Lee and coworkers immobilizedCandida rugosa lipase and Ryzopus oryzae lipase simultaneously onsilica gel for biodiesel production [7]. In an another work Yan andcoworkers co-displayed two synergistic lipases, Candida antarcticalipase B and Thermomyces lanuginosus lipase, on the surface ofPhichia pastoris cell [8].

In our previous work, a new process for biodiesel productionusing amixture of Rhizomucor miehei and Candida antarctica lipaseswas successfully developed and optimal conditions were investi-gated [9]. sn-1,3-specific lipases enhance acyl migration and soincrease the conversion of triacylglycerols [10e13] but mixing 1,3-specific lipase and a non-specific lipase remove the acyl-migrationstep which is rate determining step of biodiesel productionmechanism, and enzyme activity will be notably enhanced.

The aim of this work is co-immobilization a sn-1,3-specificlipase (RML) and nonspecific lipase (CALB) on epoxy-functionalized silica. First CALB immobilizied on epoxy function-alized silica and then RML co-immobilizied. The immobiliziedenzyme stability in methanol and its thermal stability were eval-uated. Response surface methodology was used to evaluate severalreaction parameters that influence FAME yield.

A 5-level-5-factor central composite design (CCD) was used todesign the experiments and response surface methodology (RSM)was carried out for process optimization. Several reaction param-eters that influence FAME yield reaction temperature, methanol/oilratio, reaction time, t-butanol concentration and CALB:RML ratiowere optimized. The relationships between the parameters and theresponses (FAME yield) were further analyzed systematically.

2. Materials and methods

2.1. Materials

Lipases from Candida antarctica B and Rhizomucor miehei andmethyl ester standards (methyl laurate, methyl stearate, methyllinoleate, methyl oleate, methyl palmitate) were purchased fromSigma-Aldrich. Palm oil (with an initial saponification number of201.8mg KOH/g and free fattyacid (FFA) level of 0.11%) was pur-chased from Jahan company. Molar amount of the triacyl glycerol(TAG) was calculated from its saponification value. The water

content was determined to be 0.02% (w/w) and measured by theKarl Fischer titration method [14]. Methanol, t-butanol, triethyl-amine (Et3N), n-hexane, toluene and chloroform purchased fromMerck. 3-Glycidyloxypropyl trimethoxysilane (3-GPTMS) was pur-chased from Acros. All other chemicals were obtained commer-cially and were of analytical reagent grade.

2.2. Functionalization of silica particles

One gram of dry silica gel was mixed in a dry toluene solution(30ml) containing 3-GPTMS (1ml) and Et3N (0.15ml). The result-ing mixture was refluxed under argon atmosphere and constantstirring for 4 h. The silica gel was then washed thoroughly withCHCl3 and dried at 60 �C for 2 h.

2.3. Immobilization of lipases

The activated silics gel (1 g) was mixed with 5,10,15,20mg ofCALB in 10ml phosphate buffer 25mM (pH 7) followed by incu-bation at 25 �C for 24 h. Immobilized lipase was recovered byfiltration, washed thoroughly with distilled water, and then dried atroom temperature. Then CALB immobilized support were mixedwith 5,10,15,20mg of RML same as CALB immobilization.

2.4. Determination of the amount of enzyme bound to the silicaparticles

For the quantification of dissolved lipase, Bradford method wasused [15]. The amount of lipase bound to the carrier was deter-mined as the difference between the initial and residual proteinconcentration. The yield of bound enzyme was calculated as theratio of the amount bound on silica gels to the initial amount.

2.5. Enzyme activity assay

The activity of enzyme derivatives was quantified by the releaseof p-nitrophenol during the hydrolysis of p-nitrophenyl butyrate(dissolved in acetonitrile) in 25mM potassium phosphatebuffer(pH 7.0) at room temperature. To start the reaction, 20e80 mL of thelipase suspension (50mg immobilized enzyme in 1ml phosphatebuffer 25mM pH 7) was added to 1ml of the reaction mixture(0.8mM pNPB in phosphate buffer 25mM pH 7). Hydrolysis wasfollowed by measuring the change in absorbance over 2min [12].

2.6. Thermal stability

The Thermal stability was studied by measuring the residualactivity after incubation of the immobilized enzyme (3mg/ml of25mM sodium phosphate buffer, pH 7) at 40, 45, 50 and 55 �C. Freeand immobilized enzyme derivatives were heated for 24 h and theiractivity was measured using the p-NPB assay as described above.

2.7. Stability in methanol as co-solvent

The stability of immobilized enzymes was studied by incubationat 25 �C in aqueous conditions using methanol as co-solvents. Theincubation in co-solvents was performed for 24 h in 10, 30, 50 and70% methanol solution by adding the appropriate amount of water.Samples were taken after 24 h and their activity was measured bythe p-NPB assay.

2.8. Enzymatic transesterification of palm oil

The reactions were performed according to each design pointsand the results of FAME yield were used as the response values in

Table 1Independent variables and levels used for response surface design.

Independent variables Symbols Levels

�2 �1 0 1 2

reaction temprature A 30 35 40 45 50methanol:oil ratio B 1:1 3:1 5:1 7:1 9:1reaction time (h) C 12 18 24 30 36t-butanol concentration (wt.%) D 0 10 20 30 40CALB:RML ratio E 0.5:1 1:1 1.5:1 2:1 2.5:1

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857 849

order to optimize the reaction conditions. In a typical experiment,the reaction was performed in 10ml screw-capped vials undercontinuous stirring containing palm oil and anhydrous methanol,at oil-to-methanol molar ratio of 1:3, 1:5, 1:7 and 1:9. Methanolwas added by a two-step procedure and each one molar equivalentof methanol was added at the reaction time of 0, and in half time ofreaction time, respectively. The mixtures were incubated with theimmobilized lipases on silica-epoxy at 30, 35, 40, 45 and 50 �Cunder constant magnetic agitation of 250 rpm. Methanolysis re-actions were carried out with varying amount of CALB:RML ratioand t-butanol. After the reactions were completed, an aliquot ofreaction medium was taken centrifuged (12000 rpm, 10min),mixed with methyl laurate (as an internal standard) and analyzedby the GC method as described below.

2.9. Analysis of fatty acid methyl esters

Fatty acid methyl ester contents were analyzed based on ENstandard 14103 using a Thermo-Quest-Finnigan (Plymouth, Min-nesota, USA) GC instrument equipped with an RTX-1 column and aflame ionization detector (FID). Nitrogenwas used as the carrier gasat a constant flow of 1.2mL/min. A specified amount of methyllaurate as the internal standard and 0.5ml hexane were added tothe accurately weighted sample from the upper layer of the reac-tion mixture. Then, 2.0 ml of the diluted sample was injected intothe GC gas chromatograph. The column temperature was kept at150 �C for 0.5min, raised to 300 �C at 10 �C/min, and then main-tained at this temperature for 3min. The injector and detectortemperatures were set at 220 �C and 250 �C, respectively. Bycomparing the retention times and peak areas of standard fatty acidmethyl ester peaks, the total quantities of biodiesel in the reactionmixtures were calculated. Methyl laurate as an internal standardmaterial was used for quantification of FAME, which was calculatedby the following equations:

C ¼P

A� AIS

AIS� CIS � VIS

m� 100% (1)

whereP

A¼ total peak area; AIS¼ internal standard (methyl lau-rate) peak area; CIS¼ concentration of the internal standard solu-tion in mg/mL; VIS¼ volume of the internal standard solution usedin mL; m¼mass of the sample, in mg.

2.10. Experimental design

The biodiesel synthesis from palm oil was developed and opti-mized using response surface methodology (RSM) provided byDesign-Expert software version 7.0.0 (Stat-Ease Inc., Minneapolis,USA). The 5-level-5-factor Central Composite Design CCD has beenemployed in this study, requiring 50 experiments, consisting of 33factorial points, 9 axial points and 8 replicates at the center points.The center points are usually repeated 4e8 times to determine theexperimental error (pure error) and the reproducibility of the data.Four identified independent variables are A: Reaction temperature(30e50 �C); B: Methanol:oil ratio (1:1e9:1); C: Reaction time (h)(12e36 h); D: t-butanol concentration (wt.%) (0e40%) E: CALB:RMLratio (0.5:1e2.5; 1). The levels of each independent variable werechosen based on our previous investigations. The independentvariables are coded to two levels namely: low (�1) and high (þ1),the a value was fixed at 2 which is the distance of the axial pointfrom center and makes the design rotatable, the axial points arecoded as �2 (�a) and þ2 (þa). The complete CCD design matrix interms of independent variable is presented in Table 1.

The experiments were run at random in order to minimize er-rors from the systematic trends in the variables.

2.11. Statistical analysis

Optimization of the experimental results obtained from centralcomposite designwere analyzed by response surface methodology.A mathematical model, following a second-order polynomial Eq.(2) which includes all interaction terms was used to calculate thepredicted response:

Y ¼ b0 þX4

i¼1

biXi þX4

i¼1

biiX2i þ

X3

i¼1

X4

j¼iþ1

bijXiXj þX4

i¼1

biiiX3i (2)

where Y is the yield of biodiesel from palm oil, b0 is the offset term,bi is the linear effect, bii is the squared effect, bij is the interactioneffect, Xi is the i th independent variable and Xj is the j th inde-pendent variable. The data were interpreted using F-test. Analysisof variance (ANOVA), regression analysis and plotting of contourplot were used to establish the optimum conditions for the FAMEyield.

3. Results and discussion

3.1. Optimization of immobilization condition

In our previous work, a novel process for biodiesel productionusing mixed covalently immobilized enzymes RML and CALB wassuccessfully developed and the optimal conditions were investi-gated [9]. Both enzymes were immobilized on epoxy functionalizedsilica individually so there was the limitation of themass transfer ofreactants in reaction mixture. In this report the lipases were coimmobilized in same time on silica support. Co-immobilizedenzyme systems are may be the most common type of immobi-lized multi-enzymatic systems. Co-immobilization eliminates lagtime and increases the reaction rate [8]. In this investigation weused non-specific sequential immobilization of two lipases. Thereare other approaches for co-immobilization such as random co-immobilization, positional immobilization, site-specific co-immo-bilization, and scaffold-free cross-linking [10].

The amount of immobilized enzyme and activity of preparedbiocatalysts are shown in Fig. 1. In 24 h, using a ratio of 3mg ofsupport and 1ml of phosphate buffer 25mM (pH 7), CALB and RMLwas sequentially immobilized. As can be seen, by increase the ratioof CALB to RML, the amount of immobilized enzyme decrease butthe specific activity is almost the same for all preparations.

The overall activities are lower than CALB-epoxy and RML-epoxy individually. Lipases have a peculiar mechanism of action,the so called interfacial activationwhich requires somemovementsof the enzyme structure between the closed form (where the activesite is isolated from the reaction medium by a polypeptide chaincalled lid) and the open form (with the active center exposed to themedium) [16e19]. Both open and close forms of lipases are in anequilibrium affected by the immobilization conditions. In thepresence of hydrophobic substrates, lipases may become stronglyadsorbed on the interface of hydrophobic surface and the

Fig. 1. The amount of co-immobilized enzymes and specific activity of free andimmobilized enzymes.

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857850

conformational equilibrium is shifted towards the open form of thelipases. The lid may have different configurations, in the case of thelipase from Candida antarctica (form B) (CALB) the lid is very smalland does not fully isolate the active center from the medium [20],but CALB is still able to become adsorbed on hydrophobic surfaces[21,22]. One reason that CALB did not activate after immobilizationis its small lid. As can be seen in Fig. 1 by increasing CALB:RML ratiofrom 1:1 to 4:1, the amount of immobilized enzyme on the supportwere decreased (15.0e4.15mg/g support). The specific activity offree CALB and RML (49.5 and 43.9 U/mg respectively) decreased to8.8 and 9.6 U/mg after immobilization for CALB-epoxy and RML-epoxy respectively which is common phenomenon after immobi-lization. It has been reported that the immobilization of proteins onsolid substrates may cause secondary structural changes [23e25].These changes lead to proteins losing their a-helical structure andgaining b-sheet structure. The specific activity of co-immobilized

Fig. 2. Thermal stability of co-immobilized derivatives. The incubation of enzyme derivaCALB:RML 1:1, (6) crude CALB, (7) crude RML was carried out in 25 mM sodium phosphateHydrolytic activity of enzyme derivatives was determined by measuring the increase in absonitrophenyl butyrate. Results are the mean of duplicates.

systems for CALB:RML ratio of 4:1, 2:1, 2.5:1 and 1:1 were almostthe same 6.1, 5.1, 4.9 and 5.1 U/mg respectively.

3.2. Thermal stability

As can be seen in Fig. 2 all co-immobilized derivatives havegreater enzyme activity compared with single immobilizedenzyme. Single immobilized enzyme preserved 50 and 40% of itsinitial activity in 50 and 70 �C respectively. Among the two enzymepreparations the highest residual activity in 50 and 70 �C wasachieved for CALB:RML ratio of 4:1 (ca. 60% residual activity), afterthat CALB:RML ratio of 2:1 preserved almost 50% of its initial ac-tivity in high temperatures.

3.3. Stability in methanol

Fig. 3 shows the stability of the co-immobilized preparationscompared to the CALB-epoxy in the presence of various amount ofmethanol. All co-immobilized derivatives had greater activity invarious methanol contents compared with one enzyme immobi-lized on the support. In 10 and 30wt% of methanol, all co-immobilized derivatives preserved almost 100% of their activity.In 50 and 70wt% of methanol, the residual activity of CALB-epoxydecreased to 38 and 29% of their initial activity respectively. Onthe other hand covalently immobilized CALB:RML with ratio 4:1showed excellent stability (61%) in 70%methanol. As can be seen inFigs. 3 and 4 increasing the ratio of CALB relative to RML cause toimprovement in both thermal and methanol stability.

3.4. Optimization of biodiesel production parameters

The experimental data obtained from CCD were analyzed usingresponse surface methodology. The waste cooking oil methyl ester

tives (1) CALB-epoxy, (2) CALB:RML 4:1, (3) CALB:RML 2:1, (4) CALB:RML 1.5:1, (5)buffer, pH 7, at different temperatures (A) 25, (-) 40, (:) 45, ( � ) 50 and (*) 55 �C.rbance at 348 nm produced by the release of p-nitrophenol during the hydrolysis of p-

Fig. 3. Stability of various enzyme derivatives (1) CALB-epoxy, (2) CALB:RML 4:1, (3) CALB:RML 2:1, (4) CALB:RML 1.5:1, (5) CALB:RML 1:1 (6) crude CALB, (7) crude RML in differentmethanol content (-) 10, (:) 30, ( � ) 50 and (*) 70 wt% after 24 h. Hydrolytic activity of enzyme derivatives was then determined by measuring the increase in absorbance at348 nm produced by the release of p-nitrophenol during the hydrolysis of p-nitrophenyl butyrate.

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857 851

yield ranged from 5.8% to 78.3%. Design Expert 7.0.0 program wasused to calculate the effect of each factor and its interactions.

Among the models that fitted to the response (linear, two factorinteraction (2FI), quadratic and cubic polynomial), the quadraticmodel was selected as a best model due to its highest order poly-nomial with significance of additional terms and themodel was notaliased. This quadratic model was suggested by the RSM software asshown in Table 2. The model expressed by Eq. (3) represents wasteoil methyl ester yield (Y) as a function of reaction temperature (A),methanol/oil molar ratio (B), reaction time (C), t-butanol concen-tration (D) and CALB:RML ratio (E).

Y ¼ þ58:72� 3:01A� 9:04Bþ 3:80Cþ 5:21Dþ 5:85E

� 5:82AB� 5:21AC þ 0:41AD� 1:80AEþ 4:71BC

þ 4:28BD � 0:90BEþ 3:50CDþ 1:58CEþ 1:65DE

� 0:87 A2 � 9:93B2 � 8:27C2 � 0:95D2 � 4:21E2 (3)

Positive sign in front of the terms indicates synergistic effect inincrease FAME yield, whereas negative sign indicates antagonisticeffect [26]. The results at each point based on the central compositedesign (CCD) and their corresponding predicted values are pre-sented in Table 3. The result of statistical analysis of variance(ANOVA)whichwas carried out to determine the significance (by F-test) and fitness of the quadratic model as well as the effect ofsignificant individual terms and their interaction on the selectedresponses are presented in Table 4. The statistical significance of Eq.(3) was controlled by F-test. Values of probability (P)> F less than0.05 indicate that model terms are significant. Values greater than0.05 indicate that the model terms are not significant. The smallerthe p-value, the more significant the corresponding coefficient is.

From the ANOVA results, the main model terms suggested thatall variables had significant influence on FAME yield response. Theinteraction terms which were had significant effects were existbetween the main factors (AB, AC, AD, AE, BC, BD, BE, CD, CE andDE), while the significant quadratic terms were A2, B2, C2, D2 and

E2.The terms incorporated in the model F-value of 11.43 with p-

value<0.0001 implies that the model is significant at 95% confi-dence level. The smaller the p-value, the bigger the significance ofthe corresponding coefficient is.

The goodness of fit of regression equation developed could bemeasured by adjusted determination coefficient. The R2 value of0.89 and adjusted R2 of 0.81 shows that the model could be sig-nificant predicting the response. The Predicted R2 of 0.63 is inreasonable agreement with the adjusted R2. The model alsodepicted the statistically non significant lack of fit (p 0.4429),indicating that the responses are adequate for employing in thismodel showed that the model satisfactorily fitted to experimentaldata (Fig. 4a). Insignificant lack of fit is most wanted as significantlack of fit indicates that there might be contribution in theregressor-response relationship that is not accounted for by themodel [27].

This analysis was examined using the normal probability plot ofthe residuals (Fig. 4b) and the plot of the residuals versus predictedresponse (Fig. 4c). The normal probability plot of the residuals in-dicates that the errors are distributed normally in a straight lineand insignificant. On the other hand, the plot of residuals versuspredicted response showed a structureless plot suggesting that themodel is adequate and that the model does not show any violationof the independence or constant variance assumption [26].

3.5. Parameter study and interaction between independentvariables

As mentioned previously in our previous reports we investi-gated methanolysis of waste cooking oil by a mixture of RML andCALB covalently immobilized individually on epoxy functionalizedsilica [9]. It has been reported by usingmixture of 1,3-specific lipaseand non-specific lipase the acyl-migration step which is the rate-determining step of biodiesel production was removed, andenzyme activity notably increased [28].

Fig. 4. Predicted fatty acid methyl ester yield versus experimental fatty acid methylester yield (a), Normal probability plots of residuals (b) and plot of the residuals versusthe predicted response (c).

Table 2Sequential model sum of squares.

Source Sum of squares df Mean squar

Mean 77362.11 1 77362.11Linear 6664.06 5 1332.812FI 3975.23 10 397.52Quadratic 5693.30 5 1193.06Cubic 1007.27 15 67.15Residual 1099.23 14 78.52Total 96073.20 50 1921.46

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857852

There are few reports about using co-immobilized 1,3-specificand non-specific lipases for biodiesel production. Lee and co-workers investigated transesterification and esterification using amixture of immobilized lipases Candida rugosa and Rhizopus oryzaelipases. In the batch process, the conversion yield was 98.33% at 4 h.In the continuous process, the conversion yield of biodiesel was97.98% at 3 h. [29]. In another research they simultaneouslyimmobilized Candida rugosa lipase and Ryzopus oryzae lipase onsilica gel and may be this is only report about immobilizing twolipases on the same carrier. Biodiesel was then produced by usingthe co-immobilized enzyme matrix. Under optimal immobilizationconditions, the activity was approximately 16,000 U/g$matrix.When co-immobilized enzyme was used conversion of biodieselreached about 99% [7].

Guan et al., employed a mixture of Rhizomucor miehei andPenicillium cyclopium lipases to catalyze methanolysis of soybeanoil in aqueous medium for biodiesel production. Under optimizedconditions, the ratio of biodiesel conversion after 12 h at 30 �C,using RML alone, was 68.5%. When RML was assisted by addition ofMDL, biodiesel conversion ratio was increased to >95% under thesame reaction conditions [30].

Biodiesel conversion from soybean oil reached a maximum of70% at 18 h using immobilized 1,3-specific Rhizopus oryzae lipasealone. Biodiesel conversion failed to reach 20% after 30 h whenimmobilized nonspecific Candida rugosa lipase alone was used. Toincrease the biodiesel production yield, a mixture of immobilized1,3-specific R. oryzae lipase and nonspecific C. rugosa lipase wasused. Using this mixture a conversion of greater than 99% at 21 hwas attained. When the stability of the immobilized lipasesmixture was tested, biodiesel conversion was maintained at over80% of its original conversion after 10 cycles [28].

The maximum and minimum yield of FAME in our systemwere78.3 and 5.8%, may be this is because of lower activity of RML inproducing biodiesel. Previously our group reported low conversionfor CALB or RML individually immobilized on silica-epoxy in bio-diesel production (41.3 and 37.9% respectively) [13]. In anotherinvestigation based on co-immobilized Thermomyces lanuginosalipase (TLL)-CALB and we achieved 90.2% FAME yield (unpublisheddata).

Fig. 5(aee) shows the effect of four factors: temperature,methanol to oil ratio, reaction time, t-butanol and CALB:RML ratioas one factor on biodiesel yield. The 3D response surface revealedthat increment of reaction temperature from low level (35 �C) tohigh level (45 �C) leads to a little increase in FAME content. On thecontrary, the increase of methanol to oil (from 3:1 to 7:1) does notimprove the FAME yield. The biodiesel content were raised by in-crease in reaction time, t-butanol ratio and CALB:RML ratio. The onefactor graphs and interaction graphs have least significant differ-ence (LSD) bars at the end points of each line on the graph. Theheight of the bars is determined by the design, model, confidencelevel and unexplained variation. If the ANOVA shows a significantresult for the overall model test, these bars can be used test for asignificant difference in the predictions.

These bars represent the 95% confidence interval for that

e F value Prob> F

Suggested Aliased4.87 0.00121.67 0.127716.42 <0.00010.86 0.6174

Table 3Experimental design for five-level five-factor surface response design on transesterification and esterification of palm oil using immobilized lipases.

Experimental Type Actual values of variables Fatty acid methyl ester yield(%)

A: Reactiontemperature

B: Methanol:oilratio

C: Reaction time(h)

D: t-butanol concentration(wt.%)

E:CALB:RMLratio

Experimental

1 Center 40 5 24 20 1.50 62.12 Center 40 5 24 20 1.50 58.23 Center 40 5 24 20 1.50 68.24 Center 40 5 24 20 1.50 65.85 Center 40 5 24 20 1.50 54.66 Center 40 5 24 20 1.50 54.07 Center 40 5 24 20 1.50 42.58 Center 40 5 24 20 1.50 57.59 Axial 40 5 24 40 1.50 78.310 Axial 40 9 24 20 1.50 15.011 Axial 40 5 36 20 1.50 37.612 Axial 40 5 24 0 1.50 38.413 Axial 40 5 24 20 2.50 48.914 Axial 40 5 12 20 1.50 20.515 Axial 40 5 24 20 0.50 41.716 Axial 30 5 24 20 1.50 50.417 Axial 50 5 24 20 1.50 66.918 Fact 40 1 24 20 1.50 29.819 Fact 45 3 18 30 1.00 49.420 Fact 45 7 18 30 1.00 18.021 Fact 45 7 30 30 2.00 40.422 Fact 35 3 18 10 2.00 45.523 Fact 35 7 30 10 2.00 25.524 Fact 45 3 30 10 1.00 27.725 Fact 45 3 18 10 1.00 65.326 Fact 45 3 30 30 2.00 56.027 Fact 35 3 18 30 1.00 14.828 Fact 35 7 18 10 2.00 11.529 Fact 35 3 30 10 2.00 52.630 Fact 45 7 30 10 2.00 20.831 Fact 35 7 18 30 2.00 22.532 Fact 35 3 30 10 1.00 30.633 Fact 35 7 18 10 1.00 10.334 Fact 35 7 30 10 1.00 18.335 Fact 45 3 18 30 2.00 66.936 Fact 45 3 30 30 1.00 46.837 Fact 35 7 30 30 2.00 74.138 Fact 45 7 30 10 1.00 13.239 Fact 45 3 18 10 2.00 58.840 Fact 45 7 18 30 2.00 24.741 Fact 35 3 18 10 1.00 24.042 Fact 35 7 30 30 1.00 36.743 Fact 35 7 18 30 1.00 11.944 Fact 35 3 18 30 2.00 35.645 Fact 45 3 30 10 2.00 49.646 Fact 45 7 18 10 2.00 14.347 Fact 35 3 30 30 2.00 49.248 Fact 45 7 18 10 1.00 5.849 Fact 45 7 30 30 1.00 24.250 Fact 35 3 30 30 1.00 31.3

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857 853

particular average value. This bar will not encompass 95% of thedata points because it is an interval for an average, not for in-dividuals. In Fig. 5 it can be seen that these confidence intervals arenot overlapping, then it can be concluded that the means aresignificantly different. Center Points are experimental runs with allnumerical factor levels set at the midpoint of their high and lowsettings. Replicated center points are used to estimate pure errorfor the lack of fit test. In this design it can be seen that eight centerpoints are relatively close to each other.

Fig. 6 shows that surface and contour plots of biodiesel yieldfrom transesterification of palm oil by methanol and the effect ofimportant variables.

Fig. 6a shows the interaction effect between reaction tempera-ture and methanol to oil ratio toward biodiesel yield. The 3D

response surface revealed that increment of reaction temperaturefrom low level (35 �C) to high level (45 �C) leads to the increase ofFAME content at low level of methanol content (3:1) on the con-trary; the increase of CALB does not improve the biodiesel yield athigh level of methanol (7:1). This is in agreement with previousreports about the negative effect of methanol on the enzyme.Fig. 6b depicts that in 18 h reaction time, temperature is not a keyfactor, but in longer reaction time (30 h) by increasing temperature,FAME yield improve.

Tertiary alcohols such as t-amyl alcohol and t-butyl alcohol havebeen shown to be good co-solvents for enzyme catalysed produc-tion of biodiesel, this is because these alcohols could significantlyimprove the solubility of bothmethanol and glycerol in the reactionmixture and so remarkably reduce or eliminate their inactivation

Table 4Analysis of variance (ANOVA) for the fitted quadratic polynomial model for optimization of transesterification parameters.

Source Sum of squares df Mean square F value p-value Prob > F

Model 16604.59 20 830.23 11.43 <0.0001 significantA-Reaction Temperature 362.71 1 362.71 4.99 <0.0333B-methanol to oil ratio 3266.15 1 3266.15 44.96 <0.0001C-reaction time 577.22 1 577.22 7.95 0.0086D-t-butanol ratio 1087.33 1 1087.33 14.79 0.0006E-CALB:RML 1370.66 1 1370.66 18.87 0.0002AB 1085.20 1 1085.20 14.94 0.0006AC 868.92 1 868.92 11.96 0.0017AD 5.32 1 5.32 0.073 0.7886AE 103.50 1 103.50 1.42 0.2423BC 710.17 1 710.17 9.78 0.0040BD 586.10 1 586.10 8.07 0.0082BE 26.01 1 26.01 0.36 0.5542CD 393.05 1 393.05 5.41 0.0272CE 109.34 1 109.34 1.51 0.2297DE 87.62 1 87.62 1.21 0.2811A2 24.24 1 24.24 0.33 0.5680B2 3157.14 1 3157.14 43.46 <0.0001C2 2188.74 1 2188.74 30.13 <0.0001D2 28.60 1 28.60 0.39 0.5353E2 566.58 1 566.58 7.80 0.0092Residual 2106.50 29 72.64Lack of fit 1656.86 22 75.31 1.17 0.4429 Not significantPure error 499.64 7 64.23Cor Total 18711.09 49

R-squared 0.8874Standard of deviation 8.52 Adj R-squaredb 0.8098Mean 39.34 Pred R-squaredc 0.6309C.V.a 21.67 Adeq Precisiond 11.669

a Coefficient of variation.b Adjusted R2.c Predicted R2.d Adequate precision.

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857854

effects on the lipase [31], on the other hand in Fig. 6c it can be seenthat lower amount of t-butyl alcohol (10wt%) gave rise to higherFAME yield than higher amount (30wt%).

One of the main factors which was investigated in this report isCALB:RML ratio and its influence on the on the reaction yield. Ascan be seen in Fig. 6deg, in both low and high levels of tempera-ture, methanol:oil, time of reaction and t-butanol content, higherratio of CALB:RML resulted to higher FAME percent. R. miehei lipaseis a 1,3-specific lipase and cannot hydrolyze fatty acids on thesecond position of 1,2-diglyceride however it has the ability tomove a fatty acid from this position to the third position (acylmigration) which allows biodiesel conversion to reach high rates.The combination of RML and CALB as a non-specific lipase in allreaction conditions resulted to higher yields and clearly indicatethe advantage of using enzyme mixture.

The interaction betweenmethanol:oil ratio: reaction time and t-butanol content are depicted in Fig. 6h and i respectively. Generallyenzyme immobilization increases the solvent stability of the en-zymes but high concentration of methanol (>1/2 molar equivalent)will typically inactivate the catalyst. Fig. 6h show that in short re-action times (18 h) the destructive effect of high molar ratio ofmethanol is prominent, but in higher reaction times (30 h) theFAME yields are higher, this is due to consumption of methanolbefore adding the next methanol to the reaction mixture. Also theFig. 4i that shows the interaction of low and high levels of t-butanolon methanol to oil ratio indicates co solvent can decrease thedestructive effect of methanol on biocatalyst deactivation. It can beconcluded that high methanol:oil ratio should be used in longerreaction time or in presence of a co solvent.

Finally Fig. 6j shows again the positive effect of high amount of

t-butanol on biodiesel yield at both high and low level of reactiontime.

3.6. Validation of the model

The composition of optimum waste oil methyl ester yield wereobtained from the regression model Eq. (3). In order to confirm theaccuracy of the model, a series of three experiments were carriedout, whose reaction conditions was selected among the range ofvariables. In this way, reaction variables and corresponding yieldsfor each reaction are shown in Table 5. As can be seen in the table,achieved experimental values are close to theoretical calculateddata provided by the proposed models. The overall average opti-mized conditions for biodiesel yield were obtained as follows:temperature (35.6 �C), methanol:oil ratio (5.9), reaction time 33.5 h,t-butanol (wt%) 39.9%, CALB:RML ratio 2.5:1, with biodiesel yield of78.3%. The predicted biodiesel yield was 75.2%. This means that theexperimental value obtained was reasonably close to the predictedvalue calculated from themodel. It can be concluded that themodelfrom central composite design was accurate and reliable for pre-dicting the methyl ester yield for lipase-catalysed trans-esterification of waste oil.

4. Conclusions

The aim of this investigation was transesterification of palm oilto methyl esters using co-immobilized lipases. Lipase from Rhizo-mucor miehei and Candida antarcticawere used, in co-immobilizedform, for improving the production of FAME. The conversion ofFAME reached 78.3% under optimal reaction conditions in

Fig. 5. Effect of independent variable (a) temperature, (b) methanol to oil ratio, (c) reaction time, (d) t-butanol % and (e) CALB:RML ratio.

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857 855

Fig. 6. Response surface plot and contour plot of FAME conversion; (a) methanol to oil ratio vs. temperature, (b) reaction time vs temperature, (c) t-butanol vs. temperature, (d)CALB:RML ratio vs. temperature, (e) CALB:RML ratio vs. reaction time, (f) CALB:RML ratio vs. t-butanol, (g) CALB:RML ratio vs. methanol to oil ratio, (h) reaction time vs. methanol tooil ratio, (i) t-butanol vs. methanol to oil ratio, (j) t-butanol vs. reaction time.

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857856

Table 5Optimization criteria for maximum FAME yield and results of model validation at the optimum condition.

variables Goal Lower limit Upper limit

Reaction temprature In range 35 45Methanol:oil ratio In range 1 9Reaction time (h) In range 12 36t-butanol concentration (wt.%) In range 0 40CALB:RML ratio In range 0.5 2.5FAME yield (%) Maximize 5.8 78.3

Entry Reactiontemprature

Methanol:oilratio

Reactiontime (h)

t-butanolconsentration (wt%)

CALB:RMLratio

PredictedFAMEyield (%)

ExperimentalFAMEyield (%)

1 35.6 5.9 33.5 39.9 2.5 78.3 75.22 38.3 5.5 28.4 40.00 2.2 76.3 74.13 39.3 5.3 29.3 40.00 1.9 75.5 72.84 45.0 3.0 18 11.4 1.6 64.9 60.25 43.0 4.3 18 10.0 1.4 54.3 49.5

M. Shahedi et al. / Renewable Energy 141 (2019) 847e857 857

CALB:RML ratio 2.5:1, 39.9% t-butanol consentration, methanol:oilratio 5.9, 35.6 �C and 33.5 h. This study revealed increasing theamount of nonspecific enzyme CALB relative to 1,3-specific enzymeresulted to improving the thermal stability, methanol stability andFAME yield.

Acknowledgements

The authors would like to acknowledge Iranian National ScienceFoundation (INSF) for financial support and Novozymes for kindlyproviding enzymes for this research.

References

[1] W.A. Mehdi, A.A. Mehde, O. Severgün, S. Çakar, M. €Ozacar, Lipase-based onstarch material as a development matrix with magnetite cross-linked enzymeaggregates and its application, Int. J. Biol. Macromol. 120 (2018) 1533e1543.

[2] S. Hama, H. Noda, A. Kondo, How lipase technology contributes to evolution ofbiodiesel production using multiple feedstocks, Curr. Opin. Biotechnol. 50(2018) 57e64.

[3] M. Lotti, J. Pleiss, F. Valero, P. Ferrer, Enzymatic production of biodiesel:strategies to overcome methanol inactivation, Biotechnol. J. 13 (2018)1700155.

[4] Z. Gao, Y. Yi, J. Zhao, Y. Xia, M. Jiang, F. Cao, H. Zhou, P. Wei, H. Jia, X. Yong, Co-immobilization of laccase and TEMPO onto amino-functionalized magnetic Fe3 O 4 nanoparticles and its application in acid fuchsin decolorization, Bio-resour. Bioprocess. 5 (2018) 27.

[5] D.B. Magadum, G.D. Yadav, Design of tandem catalyst by co-immobilization ofmetal and enzyme on mesoporous foam for cascaded synthesis of (R)-phenylethyl acetate, Biochem. Eng. J. 129 (2018) 96e105.

[6] D.B. Magadum, G.D. Yadav, One-pot synthesis of (R)-1-(pyridin-4-yl) ethylacetate using tandem catalyst prepared by co-immobilization of palladiumand lipase on mesoporous foam: optimization and kinetic modeling, Chirality29 (2017) 811e823.

[7] J.H. Lee, S.B. Kim, H.Y. Yoo, J.H. Lee, S.O. Han, C. Park, S.W. Kim, Co-immobi-lization of Candida rugosa and Rhyzopus oryzae lipases and biodiesel pro-duction, Kor. J. Chem. Eng. 30 (2013) 1335e1338.

[8] Q. Ji, B. Wang, J. Tan, L. Zhu, L. Li, Immobilized multienzymatic systems forcatalysis of cascade reactions, Process Biochem. 51 (2016) 1193e1203.

[9] M. Babaki, M. Yousefi, Z. Habibi, M. Mohammadi, Process optimization forbiodiesel production from waste cooking oil using multi-enzyme systemsthrough response surface methodology, Renew. Energy 105 (2017) 465e472.

[10] S. Schoffelen, J.C. van Hest, Chemical approaches for the construction of multi-enzyme reaction systems, Curr. Opin. Struct. Biol. 23 (2013) 613e621.

[11] M. Babaki, M. Yousefi, Z. Habibi, M. Mohammadi, P. Yousefi, J. Mohammadi,J. Brask, Enzymatic production of biodiesel using lipases immobilized on silicananoparticles as highly reusable biocatalysts: effect of water, t-butanol andblue silica gel contents, Renew. Energy 91 (2016) 196e206.

[12] M. Babaki, M. Yousefi, Z. Habibi, M. Mohammadi, J. Brask, Effect of water,organic solvent and adsorbent contents on production of biodiesel fuel fromcanola oil catalyzed by various lipases immobilized on epoxy-functionalizedsilica as low cost biocatalyst, J. Mol. Catal. B Enzym. 120 (2015) 93e99.

[13] M. Babaki, M. Yousefi, Z. Habibi, J. Brask, M. Mohammadi, Preparation ofhighly reusable biocatalysts by immobilization of lipases on epoxy-functionalized silica for production of biodiesel from canola oil, Biochem.Eng. J. 101 (15) (2015) 23e31.

[14] J. Verhoef, E. Barendrecht, Mechanism and reaction rate of the Karl-Fischertitration reaction: Part I. Potentiometric measurements, J. Electroanal. Chem.Interfacial Electrochem. 71 (1976) 305e315.

[15] M.M. Bradford, A rapid and sensitive method for the quantitation of micro-gram quantities of protein utilizing the principle of protein-dye binding, Anal.Biochem. 72 (1976) 248e254.

[16] L. Brady, A.M. Brzozowski, Z.S. Derewenda, E. Dodson, G. Dodson, S. Tolley,J.P. Turkenburg, L. Christiansen, B. Huge-Jensen, L. Norskov, A Serine ProteaseTriad Forms the Catalytic Centre of a Triacylglycerol Lipase, 1990.

[17] A. Brzozowski, U. Derewenda, Z. Derewenda, G. Dodson, D. Lawson,J. Turkenburg, F. Bjorkling, B. Huge-Jensen, S. Patkar, L. Thim, A Model forInterfacial Activation in Lipases from the Structure of a Fungal Lipase-InhibitorComplex, 1991.

[18] U. Derewenda, A.M. Brzozowski, D.M. Lawson, Z.S. Derewenda, Catalysis at theinterface: the anatomy of a conformational change in a triglyceride lipase,Biochemistry 31 (1992) 1532e1541.

[19] Z.S. Derewenda, U. Derewenda, G.G. Dodson, The crystal and molecularstructure of the Rhizomucor miehei triacylglyceride lipase at 1.9 Å resolution,J. Mol. Biol. 227 (1992) 818e839.

[20] J. Uppenberg, M.T. Hansen, S. Patkar, T.A. Jones, The sequence, crystal struc-ture determination and refinement of two crystal forms of lipase B fromCandida Antarctica, Structure 2 (1994) 293e308.

[21] N. Rueda, J.C. Dos Santos, R. Torres, O. Barbosa, C. Ortiz, R. Fernandez-Lafuente,Reactivation of lipases by the unfolding and refolding of covalently immobi-lized biocatalysts, RSC Adv. 5 (2015) 55588e55594.

[22] K. Hernandez, C. Garcia-Galan, R. Fernandez-Lafuente, Simple and efficientimmobilization of lipase B from Candida Antarctica on porousstyreneedivinylbenzene beads, Enzym. Microb. Technol. 49 (2011) 72e78.

[23] U. Guzik, K. Hupert-Kocurek, D. Wojcieszy�nska, Immobilization as a strategyfor improving enzyme properties-application to oxidoreductases, Molecules19 (2014) 8995e9018.

[24] G. Anand, S. Sharma, A.K. Dutta, S.K. Kumar, G. Belfort, Conformational tran-sitions of adsorbed proteins on surfaces of varying polarity, Langmuir 26(2010) 10803e10811.

[25] A. Sethuraman, G. Vedantham, T. Imoto, T. Przybycien, G. Belfort, Proteinunfolding at interfaces: slow dynamics of a-helix to b-sheet transition, Pro-teins: Struct. Funct. Bioinf. 56 (2004) 669e678.

[26] H. Lee, R. Yunus, J.C. Juan, Y.H. Taufiq-Yap, Process optimization design forjatropha-based biodiesel production using response surface methodology,Fuel Process. Technol. 92 (2011) 2420e2428.

[27] M.Y. Noordin, V.C. Venkatesh, S. Sharif, S. Elting, A. Abdullah, Application ofresponse surface methodology in describing the performance of coated car-bide tools when turning AISI 1045 steel, J. Mater. Process. Technol. 145 (2004)46e58.

[28] J.H. Lee, D.H. Lee, J.S. Lim, B.-H. Um, C. Park, S.W. Kang, S.W. Kim, Optimizationof the process for biodiesel production using a mixture of immobilizedRhizopus oryzae and Candida rugosa lipases, J. Microbiol. Biotechnol. 18(2008) 1927e1931.

[29] J.H. Lee, S.B. Kim, C. Park, B. Tae, S.O. Han, S.W. Kim, Development of batch andcontinuous processes on biodiesel production in a packed-bed reactor by amixture of immobilized Candida rugosa and Rhizopus oryzae lipases, Appl.Biochem. Biotechnol. 161 (2010) 365e371.

[30] F. Guan, P. Peng, G. Wang, T. Yin, Q. Peng, J. Huang, G. Guan, Y. Li, Combinationof two lipases more efficiently catalyzes methanolysis of soybean oil forbiodiesel production in aqueous medium, Process Biochem. 45 (2010)1677e1682.

[31] N.-W. Li, M.-H. Zong, H. Wu, Highly efficient transformation of waste oil tobiodiesel by immobilized lipase from Penicillium expansum, Process Biochem.44 (2009) 685e688.