Optimization Of Lipase Catalyzed Synthesis Of Ethyl Valerate Biology Essay

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Since the end of the last century, people are becoming more concerned about their health. Natural foods are a common requirement nowadays, which include natural ingredients. This suggests that natural flavor compounds could no more be obtained by extraction from plants alone because of the great demand. The main aim is not only to create natural flavors, but also to develop new technologies. This includes three principal techniques of biosynthesis that can be distinguished in the following ways: (1) use of enzymes (2) use of microorganisms, (3) plant cells and culture of tissues. Among those, application of enzymes is the most frequently used technique of biosynthesis [1].

Flavor esters have been generally produced by lipases from various sources in organic solvents. But solvent toxicity and high production costs are problems for most reactions. To facilitate these, solvent free system offers some advantages, where the absence of solvents facilitates downstream processing, thus offering significant cost saving and minimizing environmental impact. The number of publications referring to enzymatic synthesis of flavor esters in non-conventional media, particularly in presence of solvents, is numerous [1-3]. On the other hand, the number of articles discussed enzymatic synthesis in solvent free systems is considerably low [4].

Biotechnological production of flavor esters with lipases has recently received greater consideration with respect to the traditional methods and is undergoing a rapid development. This is due to the mild operating conditions, the higher degree of purity of the products and their acceptability in the food industries. An understanding of their biosynthesis will enable us to control the production of flavor esters in food products. The use of immobilized lipases is preferred due to its ease of handling, easy enzyme-product separation, and reusability [2].

Optimization of reaction process is very important in enzymatic synthesis to improve the reaction performance. However, most of the reported findings are based on the conventional study where only one parameter was varied at any one time, resulting in only an 'apparent' set of optimal conditions [1-3]. Understanding and modeling of both conventional and interactive effects of important parameters are essential in order to obtain a high performance synthesis [5].

A statistical based technique commonly used for this purpose is Response surface method (RSM), where the reactions are varied simultaneously in a suitable program manner to generate data for the development of empirical models. This technique of RSM is powerful tool to determine the optimum operating conditions necessary to scale up the process and to reduce the number of and cost of experiments. RSM has been successfully applied to the optimization of enzymatic syntheses of various fine chemical products [5].

Therefore, the purpose of this research is to study the optimization process of green synthesis of flavor esters via lipase-catalyzed reactions in solvent free system via statistical approach of Response surface methodology (RSM). Ethyl valerate which is known as the main component in green apple flavor was the targeted flavor ester in this investigation. It is necessary to identify the important factors that affect the performance of the process in small scale system, so that a suitable approach of scaling-up and a design model could be proposed prior to commercialization.

Materials and Methods

2.1 Materials

Novozym 435 as 10,000 PLU (from Candida antarctica lipase immobilized onto macroporous acrylin resin) was received from Novo Nordisk (Denmark). Ethanol (purity, 98 %) and valeric acid (purity, 99 %) were obtained from Merck (Germany). All other reagents were of analytical grade and used as received.

2.2 Enzymatic Synthesis

The reaction system consisted of ethanol and valeric acid (1:1) and 5 % of enzyme (w/w) were mix in screw-capped vial. The mixture was incubated at 37°C using a horizontal waterbath shaker. The shaking speed was set at 150 rpm and the reaction mixture was continuously reacted for 12 hours.

2.3 Analysis of Reaction Product

Determination of the percentage conversion of ethyl valerate (%):

The percentage conversion (%) of ethyl valerate was measured by determining the remaining unreacted fatty acids in the reaction mixture by titration with 1.0 M NaOH in an automatic titrator (Methrom, Switzerland). All the samples were assayed in triplicate and the experiment was repeated twice.

Conversion of flavour ester (%) =

Volume of NaOH used (without enzyme) - Volume of NaOH used (with enzyme) X 100 Ex. (1)

Volume of NaOH used (without enzyme)

2.4 Experimental Design

A five-level, four-factor central composite rotatable design (CCRD) was employed, requiring 30 experiments. The fractional factorial design consisted of sixtheen factorial points, eigth axial points and six centre points. The variables and their respective levels are presented in Table 1. Table 2 represents the actual experiments carried out for developing the model. The data obtained were fitted to a second-order polynomial equation:

Ex. (2)

Where Y= % conversion of flavour ester, b0, bi, bii and bij are constant coefficients and xi are the uncoded independent variables. Subsequent regression analysis, analysis of variance (ANOVA) and response surfaces were performed using Design Expert Software (version 7.1.6) from stat ease (Minneapolis, MN). Optimal reaction parameters for maximum conversion were generated using the software's numerical optimization function.

Table 1. Coded and actual levels of variables for design of experimenta

Coded values of variables

Factor

Name

Unit

-1

0

1

α

A

Time

min

15

30

45

60

75

B

Temperature

°C

15

30

45

60

75

C

Enzyme Amount

% (w/w)

2.5

10

17.5

25

32.5

D

Shaking Speed

rpm

0

50

100

150

200

aStudy type, response surface; No. of experiments, 30; design, CCRD; response, Y1, name, flavour ester, unit, % conversion.

Table 2. Design matric of the actual experiments carried out for developing the model

Standard

A (min)

B % (w/w)

C (°C)

D (rpm)

Actual (%)

Predicted (%)

1

30

10

30

50

45.732

48.976

2

60

10

30

50

60.500

63.828

3

30

25

30

50

84.275

85.278

4

60

25

30

50

79.736

84.105

5

30

10

60

50

47.671

50.113

6

60

10

60

50

61.150

59.693

7

30

25

60

50

80.031

83.991

8

60

25

60

50

81.545

79.545

9

30

10

30

150

45.697

50.808

10

60

10

30

150

70.588

68.174

11

30

25

30

150

76.346

79.347

12

60

25

30

150

82.019

82.688

13

30

10

60

150

59.778

56.954

14

60

10

60

150

64.941

69.048

15

30

25

60

150

85.288

85.07

16

60

25

60

150

84.838

83.138

17

15

17.5

45

100

71.527

66.995

18

75

17.5

45

100

80.039

79.916

19

45

2.5

45

100

36.948

33.507

20

45

32.5

45

100

83.112

81.899

21

45

17.5

15

100

79.781

73.954

22

45

17.5

75

100

74.369

75.541

23

45

17.5

45

0

77.689

73.572

24

45

17.5

45

200

79.533

78.966

25

45

17.5

45

100

74.069

77.011

26

45

17.5

45

100

72.826

77.011

27

45

17.5

45

100

78.065

77.011

28

45

17.5

45

100

79.674

77.011

29

45

17.5

45

100

78.405

77.011

30

45

17.5

45

100

79.027

77.011

Result and Discussion

3.1 Model fitting and ANOVA

The coefficients of the empirical model and their statistical analysis, evaluated using Design Expert Software, are presented in Tables 3-5. The model F-value of 19.17 with a 'Prob > F' value of 0.0001 implied that the model was significant at the 1 % confidence level. The high coefficient of determination (R2= 0.9471) of the model indicated the suitability of the model for adequately representing the real relationship among the parameters studied. A high value of R2 (>0.950) has been also reported by Hari Krishna et al [6], for the lipase-catalysed synthesis of isoamyl isobutyrate and by Jei et al [7] for the enzymatic optimization of propylene glycol monolaurate by direct esterification. In this study, quadratic model was shown to be the most significant model due to the low value of probability (P=0.0001) and high value of coefficient determination (R2=0.9471). Similar quadratic response models have been reported by Shieh et al [8] and Chen et al [9] in the optimization of lipase-catalyzed synthesis of biodiesel (soybean oil methyl ester) and kojic acid monolaurate, respectively. The model indicates the significant terms was observed for linear (A and C), quadratic (C) and interactive effect (AC) according to the value of 'Prob > F' < 0.050. The final equation was derived in terms of coded factors for the synthesis of ethyl valerate as shown in Equation (3):

Y = +77.01 + 3.23A + 12.10B + 0.40C + 1.36D - 3.51AB - 1.32AC + 0.63AD - 0.11BC - 1.44BD + 1.25CD - 0.89A2- 4.83B2- 0.57C2- 0.18D2

Ex. (3)

where A is the time; B is the temperature; C is the amount of enzyme; D is the shaking speed.

Table 3. Statistical analysis: ANOVA

Source

Sum of squares

Degrees of freedom

Mean Square

F-value

Prob >F

Model

4748.83

14

339.20

19.17

<0.0001a

Residual

265.43

15

17.70

Lack of fit

225.05

10

22.51

2.79

0.1347

Pure error

40.37

5

8.07

Total

5014.26

29

aSignificance at 'Prob>F' is <0.0500

Table 4. Statistical analysis: regression analysis

Std. Dev.

4.21

Mean

71.84

R-squared

0.9471

Adj-R-Squared

0.8977

Pred-R-Squared

0.7299

Adeq Precision

17.335

Table 5. Statistical analysis: coefficient of models

Factor

Coefficient Estimate

Prob >F

Intercept

77.01

<0.0001

A-Time

3.23

0.0019*

B-Temperature

0.40

0.6507

C-Enzyme Amount

12.10

<0.0001*

D-Shaking Speed

1.36

0.1351

AB

-1.32

0.2293

AC

-3.51

0.0045*

AD

0.63

0.5590

BC

-0.11

0.9210

BD

1.25

0.2522

CD

-1.44

0.1909

A2

-0.89

0.2859

B2

-0.57

0.4919

C2

-4.83

<0.0001*

D2

-0.18

0.8239

aA = Time; B = Temperature; C = Enzyme amount; D = Shaking Speed.

bSignificance at 'Prob > F' is <0.0500

3.2 Response surface plot

Equation (3) was then used to facilitate plotting of the response surfaces. Two parameters were plotted at one time on the X1 and X2 axes, respectively, with another parameter set at their centre point value (coded level:0). Fig. 1 a-c illustrate the response surface plots as function of time (A) versus temperature (C), amount of enzyme (B) and shaking speed (D), respectively. Generally, all figures show the percentage conversion of ethyl valerate was increased with increasing the temperature, amount of enzyme and shaking speed of @85.00 %. However, it was found that the percentage conversion was sligthly decreased with increasing the temperature from 52.50 to 60.00°C (77.6 %). An increment in the reaction temperature improved the substrates solubility and dissociation and decrease in the binding equilibrium, leading to unfavorable esterification conditions [10]. Furthermore, the use of low temperature is beneficial in that, power costs can be reduced and enzyme stability can be preserved during prolonged operation. The similar finding were also reported by Hari Krishna et al [6], and Soo et al [11], for the lipozyme-catalyzed synthesis of amino acid esters and isoamyl isobutyrate, respectively. In enzymatic reaction, organic solvent was usually used to improve the solubility of the substrates and enhance the production yield. In order to reduce the cost and solvent toxicity, a solvent free system was applied in this study. The result shows that at optimized variables of temperature, amount of enzyme and shaking speed, it could lead to produce high conversion of flavor ester even in a shorter time period. This is contrast with the work that has been done by Chaabouni et al [4], whereby the equilibrium conversion of ethyl valerate using immobilized Staphylococcus stimuli in the presence of organic solvent only acheived at 18 hours of incubation period. On the other hand, the use of solvents free system also lead us to purify the product easily without any toxicity and inflammability problems.

Fig. 2 a and b depict the positive effects to the response, whereby increasing the amount of enzyme and shaking speed will increase the conversion of flavour ester at any given temperature. The result shows at temperature from 30 to 60 °C, with increasing amount of enzyme and shaking speed will increase the percentage conversion of ester of approximately 78 %. Among the parameters, enzyme amount and shaking speed show the most significant effect to the response. Only small differences of 1 % was observed in the percentage conversion by increasing the temperature from 30 to 60 °C at fixed enzyme amount of 10 % (w/w). Meanwhile, increasing the amount of enzyme from 10 % (w/w) to 25 % (w/w) at fixed temperature at 30 °C, it gave a difference in percentage conversion of 25 %. This finding is similar with what was reported by Jei et al [7], that an increase in temperature and enzyme amount will increase the production of propylene glycol monolaurate. This was due to the improvement of substrate solubility by reducing mass transfer limitations and thus makes the substrates more available to the enzyme. Fig 2b shows, by increasing the temperature from 30 to 60 °C at fixed shaking speed at 50 rpm, the percentage conversion of ethyl valerate was decreased from 76 % to 74.45 %, whereas increasing the shaking speed from 50 to 150 rpm at fixed temperature at 30 °C, gave difference in the conversion of only 0.5 %. According to analysis of variance, we can observed that shaking speed and temperature show insignificant effects to the percentage conversion of ethyl valerate with the P-value > 0.05. This indicates that, both of the factors are not the major influence in the enzyme reactions.

Fig 3 represents the effect of amount of enzyme (C) versus shaking speed (D) at fixed time, 45 minutes and temperature, 45 °C. At high amount of enzyme (25 % (w/w) and shaking speed (150 rpm), maximum conversion of more than 80 % was observed. Amount of enzyme shows better influence compared to shaking speed. By referring the 3D surface graph, an increase in shaking speed from 50 rpm to 150 rpm at amount of enzyme 10 % (w/w), gave the difference in percentage conversion of only 5 %. However, by increasing the amount of enzyme from 10 % (w/w) to 25 % (w/w) at the fixed shaking speed 50 rpm, it gave the difference in percentage conversion of 27 %. This was due to the increase in acceleration of enzyme movement which resulted in high reaction rate between the substrates and enzyme molecules. Higher enzyme amount also increased the formation of acyl-enzyme intermediate to produce the product, which was in agreement with the results by Keng et al [12] and Gunawan et al [13] on the synthesis of palm-based wax esters using Lipozyme RM IM.

(b)

(a)

(c)

Fig 1. (a) Response surface plot showing the effect of time (A) versus amount of enzyme (B) on the synthesis of ethyl valerate at fixed temperature at 45 °C and shaking speed at 100 rpm. (b) Response surface plot showing the effect of time (A) versus temperature (C) on the synthesis of ethyl valerate at the fixed amount of enzyme at 17.50 % (w/w) and shaking speed at 100 rpm. (c) Response surface plot showing the effect of time (A) versus shaking speed (D) on the synthesis of ethyl valerate at fixed amount of enzyme 17.50 % (w/w) and temperature at 45 °C.

(b)

(a)

Fig. 2. (a) Response surface plot showing the effect of temperature (B) versus amount of enzyme (C) on the synthesis of ethyl valerate at fixed time 45 minutes and shaking speed at 100 rpm. (b) Response surface plot showing the effect of amount of enzyme (B) versus shaking speed (D) on the synthesis of ethyl valerate at fixed time at 45 minutes and temperature at 45 °C.

Fig. 3. Response surface plot showing the temperature (C) versus shaking speed (D) on the synthesis of ethyl valerate at fixed time at 45 minutes and amount of enzyme at 17.50 % (w/w).

3.3 Optimization of reaction

The optimum condition for the lipase-catalyzed synthesis of ethyl valerate was predicted using the optimization function of the Design Expert Software. Table 6 shows the optimum condition of their experimental and predicted values. Comparison of experimental and predicted values revealed good correspondence between them, implying that empirical model derived from RSM can be used to adequately describe the relationship between the factors and response in lipase-catalyzed synthesis of ethyl valerate. From an economic viewpoint, it is desirable to choose the lowest possible reaction time, temperature, amount of enzyme and shaking speed for practical esterification of ethyl valerate. The optimum conditions can be used for future upscale synthesis of ethyl valerate. Novozym 425 can work well up to temperature of 60.00 °C as reported by the most manufacturer. Many reactions were undertaken at temperature range 30.00-70.00 °C to test for its performance [14]. Meanwhile a temperature of 30 °C was sufficient to produce high yield of over 80.00% in lipase-catalyzed synthesis of ethyl valerate. From economic standpoint, it would be favorable to use the minimum time and enzyme amount to attain maximum conversion. If it was necessary to complete the synthesis with the highest percentage conversion without concern for cost, the amount of enzyme should be considered first, and then the other factors could be maximized [13]. All optimum conditions can be used to produce high % conversion of ethyl valerate.

Table 6. Predicted and actual values of optimisation condition

 

Optimum Condition

 

 

No.

A (Min)

B w/w (%)

C(°C)

D(rpm)

Predicted Conversion (%)

Actual Conversion (%)

1

47.98

25

30

51.09

84.608

84.281

2

49.51

25

30

50

84.623

84.187

3

48.53

25

30.01

50

84.628

82.527

4

45.34

25

33

50

84.594

82.288

5

48.59

24.99

59.99

150

84.594

85.157

A: Time (minute), B: Amount of enzyme % (w/w), C: Temperature (°C), and D: shaking speed (rpm).

Conclusion

Comparison of predicted and experimental values revealed a good correspondence between them, implying that empirical models derived from RSM can be used to adequate describe the relationship between factors and response in lipase-catalyzed synthesis of ethyl valerate. This models can be used to predict flavour ester conversion under any given conditions within the experimental range. We have demonstrated that optimum synthesis of flavour esters can be successfully predicted by RSM.

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