Erucic acid production using porcine pancreas lipase: Enhancement by mixed surfactants

Biotechnology and Bioprocess Engineering 16: 327-336 (2011)

DOI 10.1007/s12257-010-0193-x

Erucic Acid Production Using Porcine Pancreas Lipase:

Enhancement by Mixed Surfactants

Debajyoti Goswami, Jayanta Kumar Basu, and Sirshendu De

Received: 14 June 2010 / Revised: 6 July 2010 / Accepted: 7 July 2010

© The Korean Society for Biotechnology and Bioengineering and Springer 2011

Abstract Application of mixed surfactants coupled with

statistical optimization in lipase catalyzed oil hydrolysis is

presented for the first time in this study. Selective hydro-

lysis of brown mustard oil to erucic acid by porcine pan-

creas lipase was enhanced by mixed surfactants comprising

of an oil-soluble nonionic surfactant (Span 80) and a water-

soluble nonionic surfactant (Tween 80). The production of

erucic acid was maximized using statistically designed

experiments and subsequent analysis of their result by

response surface methodology. The most significant vari-

ables were enzyme concentration and concentration of

Tween 80. Small changes in pH and concentration of Span

80 also produced a significant change in the production of

erucic acid. Temperature and speed of agitation were insigni-

ficant variables and were fixed at 35ºC and 900 rpm, respec-

tively. Under these conditions, the optimal combination of

other variables were pH 9.65, 2.13 mg/g enzyme in oil, 9.8

× 10−3 M Span 80 (in oil), and 4 × 10−3 M Tween 80 (in

buffer). These conditions led to formation of 99.69% of the

total erucic acid in 1.25 h. Interaction of enzyme concen-

tration with pH significantly affected erucic acid production.

Keywords: hydrolysis, mustard oil, porcine pancreas lipase,

mixed surfactant, response surface methodology

1. Introduction

Erucic acid, a major constituent (18 ~ 51%) of the fatty

acid profile of mustard oil [1], occupies mainly positions 1

and 3 of its triacylglycerol structure. As this acid can cause

different health problems like myocardial lipidosis and

myocardial necrosis [2], its allowable limit is 2% in edible

oil (www.cseindia.org/oil/CCFS_20080107.pdf.). So,

mustard oil can alternatively be used for production of erucic

acid. This acid and its derivatives have wide applications in

the area of healthcare products, surfactant synthesis, bio-

diesel, and in the manufacture of resins and nylon [1,3].

Conventional processes for oil hydrolysis, which includes

alkaline saponification followed by acidification, low-

temperature crystallization, Colgate-Emery steam splitting

and fractional distillation, have several disadvantages [4-6].

Lipase catalyzed hydrolysis has certain advantages over

those conventional processes, such as ambient process

conditions and high product purity. Non-regioselective

lipases produced by Pseudomonas cepacia, Geotrichum

candidum, and Candida rugosa isolate erucic acid more

slowly than 20-carbon and 18-carbon fatty acids [7]. So,

these lipases are not preferred for selective hydrolysis of

erucic acid. Regioselective lipases can selectively cleave

ester bonds at positions 1 and 3 at a much faster rate (50

~ 100 times) than the same bond at position 2 of the tri-

acylglycerol structure [8]. So, these lipases are quite effec-

tive in this case. Brown mustard oil from Brassica juncea

was chosen as the source for erucic acid in this study. In an

earlier study using this oil, regioselective lipases from por-

cine pancreas and Rhizopus arrhizus concentrated erucic

acid in the fatty acid fraction by 65 and 61%, respectively,

in 38 h, and Rhizomucor miehei lipase concentrated it by

54% in 8 h [9]. For the present study, cheap porcine

pancreas lipase, which exists as various isoenzymes in

different glycosylated forms along with some other enzymes

[10], was selected.

Several studies have examined the effects of mixed

surfactants on lipase activity. Pan et al. [11] determined

the effect of different concentrations of mixed nonionic

surfactants (a 4:1 ratio of Triton X-114 and Triton 45) on

Debajyoti Goswami, Jayanta Kumar Basu, Sirshendu De*

Department of Chemical Engineering, Indian Institute of TechnologyKharagpur, Kharagpur 721-302, IndiaTel: +91-3222-283-926, Fax: +91-3222-255-303E-mail: [email protected]

RESEARCH PAPER

328 Biotechnology and Bioprocess Engineering 16: 327-336 (2011)

the activity of Serratia marcescens ECU1010 lipase. The

mixed nonionic surfactants negligibly influenced lipase

activity at surfactant concentrations below 0.06 g/L, while

a relatively high activity of lipase was observed at non-

ionic surfactant concentrations from 0.06 ~ to 0.15 g/L.

Conversely, lipase activity decreased rapidly due to inhibi-

tion at the nonionic surfactant concentration above 0.15

g/L [11]. In mustard oil hydrolysis, application of surfactants

has been explored as a method of enhancement in a few

studies. Tinoi [12] carried out mustard oil hydrolysis by

lipases from Candida rugosa and Aspergillus sp. in the

presence of four different types of surfactants. Two of the

surfactants, tetraethylammonium chloride and dodecyltri-

methylammonium bromide, enhanced the production of

fatty acids by 60%. Other studies reported that the surfac-

tants sodium dodecyl sulfate (SDS), cetyl pyridinium chlo-

ride, and benzalkonium chloride act as non-irreversible

denaturants of porcine pancreas lipase in a certain concen-

tration range [13-15]. Sulfobetaines (TM 3-12 and TM 3-

14), which are zwitterionic surfactants, and nonionic Triton

X-100 or Tween-80 are also ineffective [16]. But, at low

levels, SDS can activate lipase [17,18].

To maximize erucic acid production in the presence of

surfactants, proper optimization is necessary. Classical

optimization methodology has disadvantages that include

the change of only one variable at a time, a large number

of requisite experiments and no consideration of interaction

effects among different variables [19]. A more useful

approach is a combination of mathematical and statistical

procedures called response surface methodology (RSM)

[20]. RSM has proved to be successful in optimizing

process parameters in lipase catalyzed reactions [21-23].

On the basis of these previous studies, critical process

parameters were chosen for the present study. Temperature,

pH, and enzyme concentration have a profound effect on

lipase catalyzed reactions [24-26]. Buffer concentration

and speed of agitation also significantly affect hydrolysis

[27,28]. A proper surfactant can be chosen from some

preliminary experiments. Surfactant concentration can also

affect the process significantly.

The present study aimed at determining the optimal

combination of the critical process parameters including

temperature, pH, enzyme concentration, buffer concen-

tration, speed of agitation, and surfactant concentration for

the maximum production of erucic acid from hydrolysis of

oriental brown mustard oil.

2. Materials and Methods

2.1. Materials

Porcine pancreas lipase (type II, activity 100 ~ 400 units/

mg solid, where one unit activity means production of 1

µmole fatty acid/h) was purchased from Sigma-Aldrich

(USA) and was used without further purification. Oriental

brown mustard oil from Brassica juncea was obtained

from local market of Kharagpur, India. Acetone, methanol,

sodium hydroxide, Titrisol buffer (boric acid/potassium

chloride/sodium hydroxide) of pH 9, SDS, Brij 35 (poly-

oxyethylene (23) lauryl ether), and Tween 80 (polyoxy-

ethylene sorbitan monooleate) were procured from Merck

India. Ethanol was obtained from Jiangsu Huaxi Inter-

national Trade Co. (China). Pure erucic acid (90%) was a

gift from Godrej Industries Pvt.. Tris (hydroxymethyl) amino-

methane was purchased from Himedia Laboratories Pvt.

(India). Maleic anhydride, CPC, Triton X-100 (octylphen-

oxy polyethoxy ethanol), boron trifluoride, and disodium

hydrogen phosphate were obtained from SRL (India).

Cetyl trimethyl ammonium bromide (CTAB) and Span 80

(sorbitan monooleate) were procured from Loba Chemie

Pvt. (India).

2.2. Experimental set up

A batch cylindrical reactor of inner diameter 6 cm and 250

mL volume was used along with mechanical stirrer incorpo-

rating a 2 cm-diameter four-bladed paddle type impeller.

These dimensions were chosen to keep the ratio of reactor

diameter and impeller diameter fixed at 1:3, to ensure a

constant turbulence for all reactor runs. A thermostatic water

bath (Thermocon, India) was used to keep the temperature

constant (± 1°C). Reactions were carried out at atmospheric

pressure.

2.3. Procedure

The basic procedure has been previously described [29].

Initially, different concentrations of SDS and Span 80 were

tested at 35ºC, pH 9, 10 mg/g oil lipase, buffer concen-

tration of 3 g/g oil with a reaction time of 6 h. After that,

SDS, CPC, CTAB, Span 80, Triton X-100, Brij 35, and

Tween 80 were tested at 35ºC, pH 7, 10 mg/g oil lipase,

buffer concentration of 1 g/g oil. Next, Span 80 was tested

under the same conditions with a buffer concentration of

0.2 g/g oil. Finally, some combinations of Span 80 (added

in the oil phase) and Tween 80 (added in the buffer phase)

were tested under the same conditions with a buffer concen-

tration of 0.2 g/g oil. Further experiments, each 2 h in

duration and designed by fractional factorial design (FFD)

method, were carried out with the mixed surfactant system

(Span 80 and Tween 80) to ascertain the most significant

variables. Next, 1.25 h experiments were designed based

on a full factorial central composite design (FFCCD)

method using those most significant variables. The results

were used to determine the optimal process conditions by

numerical optimization. Each reaction was terminated by

Erucic Acid Production Using Porcine Pancreas Lipase: Enhancement by Mixed Surfactants 329

addition of a certain volume of neutralized 1:1 (v/v) acetone-

ethanol solution to the reaction mixture.

2.4. Analysis of erucic acid

2.4.1. Preparation of methyl erucate

The oil phase was separated from the aqueous phase of the

product mixture. Then, a certain volume of oil sample was

collected in a 15 mL screw-cap vial and a certain volume

of boron trifluoride-methanol (14% v/v) solution was mixed

with it. The mixture was heated at 55ºC for 1.5 h with

stirring for 10 sec in every 15 ~ 20 min [30]. Prepared

sample was further analyzed by gas chromatography as

described below.

2.4.2. Capillary gas chromatography

A sample of 0.2 µL was injected in a model GC 8610 gas

chromatograph (Chemito Instruments, India) with an

attached BPX 70 type SGE forte GC capillary column (25

m × 0.53 mm × 0.5 µm). Before each injection, preheating

was done for 30 min at 230ºC. The initial oven temperature

was 60ºC and was then increased by 10ºC/min to 150ºC,

followed by an increase of 5ºC/min to 230ºC. Injector and

detector temperature were 240 and 280ºC, respectively. A

split flow (10:1) was used and capillary pressure was 0.2 ~

0.4 bar. The response was calculated from the following

equation:

Percentage of total erucic acid formed (%) =

where the percentage of erucic acid in the fatty acid profile

of oriental mustard oil (Brassica juncea) was taken as 49%

(http://www.regional.org.au/au/gcirc/canola/p-08.htm?print=1).

2.5. Experimental design by FFD

Preliminary experimental results established that a mixed

surfactant system comprising Span 80 and Tween 80 was

primarily suitable for enhancement of erucic acid produc-

tion at a buffer concentration of 0.2 g/g oil. Selected factors

were temperature, pH, enzyme concentration, concentration

of Span 80, concentration of Tween 80, and speed of

agitation. The 26-2 FFD was used to screen these six factors

to discern those most significant. These test variables were

coded according to the following equation for development

of the regression equation:

xi = (Xi − Xi*) / ∆Xi (1)

where xi is the coded value of the i th independent factor or

variable; Xi is the uncoded value of the i th independent

variable; Xi* is the uncoded value of the i th independent

variable at the centre point and ∆Xi is the step change value

[31]. The system or process is generally controlled by some

of the main effects and low-order interactions according to

the ‘sparsity of effects’ principle [32]. The model involving

only low order interactions is written as:

Y = c0 + Σ ci xi + ΣΣ cijxixj (2)

where Y is the response (i.e., ‘percentage of total erucic

acid formed’). The term ‘c0’ stands for intercept. A total of

20 experiments were carried out based on a fractional

factorial design. ‘Design Expert’ software, version 7.1.3

(Stat-Ease, USA) was applied to analyze the result.

2.6. Path of steepest ascent method

When the mean response of the center points exceeds the

mean response of the factorial points in a FFD, the

optimum lies near or within the experimental design space.

Otherwise, the optimum lies outside the experimental

design space and the method of steepest ascent is necessary

[20,32]. The direction of the steepest ascent is the direction

in which response increases most rapidly. This direction is

parallel to the normal of contour plot of model described

by Eq. (2) and passes through the centre point of the FFD.

The step along the path of steepest ascent for each variable

(xi) will be proportional to its regression coefficient ci in

Eq. (2) [20,33].

2.7. Experimental design, analysis, and optimization by

FFCCD

A FFCCD [20] was used to obtain data to fit the following

empirical quadratic model for four screened variables:

Y = b0 + b1q1 + b2q2 + b3q3 + b4q4 + b11q12 + b22q2

2

+ b33q32 + b44q4

2 + b12q1q2 + b13q1q3 + b14q1q4

+ b23q2q3 + b24q2q4 + b34q3q4 + r (3)

where the screened variables are q1, q2, q3 and q4. Y and b0

are response and intercept, respectively. First order effects

for variables are represented by the coefficients b1 to b4.

Quadratic effects are signified by coefficients b11 to b44.

The coefficients b12, b13, b14, b23, b24 and b34 represent

mutual interaction effects for the variables. The term ‘r’

symbolizes residual (i.e., difference between predicted and

measured value of the response [31]).

Those significant test variables were coded according to

the equation:

qi = (Qi − Qi*) / ∆Qi (4)

where qi and Qi signify the coded and uncoded value of the

i th test variable, respectively, whereas the uncoded value

of the i th test variable at the centre point and the step

change value are represented by Qi* and ∆Qi, respectively

[31]. This study used a 24 FFCCD to fit a second order

Net amount of erucic acid in product g( ) 100×

Net amount of erucic acid in oil g( )----------------------------------------------------------------------------------------------------------------


polynomial model. This design took into account six

replicates at the centre points and four significant variables

with five levels and two star points for each of them. Thus,

a total of 30 experiments were necessary taking four

significant variables into consideration [31]. Numerical

optimization as well as analysis of the response surface

contour plots yields optimal values of these significant

variables.

3. Results and Discussion

3.1. Effect of surfactant(s) and selection

From the results of preliminary experiments, different sur-

factants at different concentration ranges were found to

decrease erucic acid formation, ranging from moderately to

extensively. Only Span 80 showed considerable enhance-

ment at a buffer concentration of 0.2 g/g oil.

A mixed surfactant system comprised of Span 80 and

Tween 80 enhanced erucic cid formation by as much as

57% at a buffer concentration of 0.2 g/g oil. Mixed emul-

sifiers impart greater stability to emulsions than single

ones, especially if one is preferentially oil-soluble and the

other is preferentially water-soluble [34]. The combination

of ‘Span’ and ‘Tween’ is a good example of such a mixed

emulsifier. ‘Spans’ are preferentially oil-soluble and ‘Tweens’

are preferentially water-soluble. As surfactant molecules

can diffuse from both the oil and water phases simultane-

ously, the adsorbed surfactant mixture is more rapidly re-

equilibrated after a local disturbance. This makes film rup-

ture more difficult and adds extra stability to the emulsion

[34].

Generally, surfactant mixtures perform better than pure

surfactants for a wide variety of applications in forming

emulsions [35,36]. Emulsions with mixed surfactants dis-

perse and solubilize more dispersed phase into the con-

tinuous phase compared to a single surfactant [37-40]. In

the case of Span surfactants, the surface bend of the drop-

lets is quite marked for the large surfactant hydrophobic

tail and the small hydrophilic head [41]. This limits the

quantity of water contained by the droplets. On addition of

a more hydrophilic surfactant, like Tweens, the surface

bend of droplets diminishes leading to the increase in

emulsion area. Consequently, more water is dissolved with

the surfactant mixture compared to a single surfactant [41].

For nonionic surfactants containing polyoxyethylene chain

(e.g., Tween 80), solubilization of substrate can also occur

within the polyoxyethylene shell.

Nonionic surfactants like Span 80 and Tween 80 can

enhance the stability of the lipase structure. These surfactants

contain polyol (sorbitol) and sugar groups. Stabilizing addi-

tives like polyols and sugars affect biochemical equilibria

when added to aqueous biomolecule solutions [42]. These

additives increase the thermal stability of proteins, and the

increase in the surface tension of solvent water in their

presence helps preferential hydration [43-45]. As high

surface tension inactivates enzyme by its denaturation,

surfactants stabilize enzyme by decreasing surface tension.

In one study, the combination of Tween 20 and Span 20

stabilized emulsions to a maximum at a particular mole

ratio of 1:3 due to the large electrostatic repulsion between

films [46]. The superior surface viscosity and elasticity due

to interactions between dissimilar surfactants also impart

added stability.

3.2. FFD for screening of variables

Table 1 represents range and levels of different variables or

factors for FFD with mixed surfactant system comprising

of Span 80 and Tween 80. In this case, reaction time was

restricted to 2 h. In the case of surfactant enhanced ricinoleic

acid production from castor oil, a buffer concentration of

0.2 g/g oil was optimal [29]. Formation of water in an oil

emulsion stabilized by the nonionic surfactant Span 80 was

considered to be main reason for that enhancement. So, in

this case, a buffer concentration of 0.2 g/g oil was explored.

Table 2 shows a FFD matrix in coded units along with

the observed responses. The factors were screened by a

26-2 FFD based on the results in Table 2. The regression

equation is:

Y = −12215.95 − 5683x1 + 10833.2x2 − 12.05x3 − 8597.5x4

+ 400.52x5 − 5.42x6 + 3325.68x1x2 + 128.84x1x3

– 3461x1x4 − 305.67x1x5 + 3.68 x1x6 + 7268.5x2x4

+ 8.29x2x6 (5)

The model F value of 6.38 and probability of 0.043

indicated the significance of the model. The variables

having a markedly low probability value (< 0.05) were

considered to have significant effects. These factors were

pH (p = 0.004), enzyme concentration (p = 0.013), concen-

tration of Span 80 (p = 0.007) and concentration of Tween

80 (p = 0.005).

Table 1. Experimental range and levels of the independentvariables for fractional factorial design

VariablesRange and levels

−1 0 1

Temperature (x1), (ºC)pH (x2)Enzyme concentration (x3), (mg/g oil)Concentration of Span 80 (x4) × 103, (M in oil)Concentration of Tween 80 (x5) × 103, (M in buffer)Speed of agitation (x6) (rpm)

257251.5

700

3586

103

900

1,1451,1091,1101,1151,104.5

1,100


Temperature (p = 0.067) and speed of agitation (p =

0.421) were insignificant, and so were fixed at centre point

values in the FFD (35ºC and 900 rpm, respectively).

3.3. Path of steepest ascent

The optimum point is not within or near this design space,

as the mean response of the factorial points (59.76%)

exceeded the mean response of the centre points (25.07%),

necessitating a method of steepest ascent. Here, each ex-

periment was 2 h in duration. The significant variables

from the fractional factorial method were pH, enzyme

concentration, concentration of Span 80 and concentration

of Tween 80. In Eq. (5), regression coefficients of pH (x2)

and concentration of Tween 80 (x5) are positive, whereas

coefficients of enzyme concentration (x3) and concentration

of Span 80 (x4) are negative. This means that an increase

in pH and concentration of Tween 80, with a simultaneous

decrease in enzyme concentration and concentration of

Span 80 can lead to an increased response [33]. By chang-

ing pH by 0.2 units (i.e., by 2.5%), enzyme concentration

changes by only 0.03% and concentration of Tween 80

changes by only 9 × 10−4 %. Both changes are insignificant.

So, these variables were kept constant at their centre point

values. The corresponding change in concentration of Span

80 is 2%, which is significant. Table 3 shows the results of

steepest ascent path. Run No. 4 resulted in a maximum

response of 72.25%. This sudden increase of response

occurs due to the attainment of optimum pH of porcine

pancreas lipase (8.8) in the presence of a cis-unsaturated

fatty acid like erucic acid [47]. So, the conditions corre-

sponding to this particular run pH 8.8, enzyme concen-

tration of 6 mg/g oil, concentration of Span 80 of 9.2 ×

10−3 M in oil and concentration of Tween 80 of 3 × 10−3 M

in buffer were selected as centre point conditions for 24

FFCCD. Temperature and speed of agitation remained

fixed at 35ºC and 900 rpm, respectively.

3.4. Results of CCD

The range and levels of significant variables considered in

the CCD are shown in Table 4. Table 5 shows the statistical

combination of design variables with response (i.e., ‘per-

centage of total erucic acid formed’). All the CCD-based

experiments were carried out for 1.25 h.

Significance of the model is represented by the F-value

of 10.01. The model p-value was < 1 × 10−4, meaning that

there was only a 0.01% chance that noise could cause this

error. The determination coefficient (R2 = 0.903) revealed

that the model was unable to explain only 9.67% of the

total variations, indicating a very good fit for the model. A

high adjoint determination coefficient (Adj R2 = 0.813)

was indicative of the model’s high applicability. The high

correlation coefficient (R = 0.95) revealed the close agree-

ment of the actual and predicted values [31]. The regre-

ssion equation defining the empirical relation between

response and the design variables in the coded unit is:

Table 2. Experimental design and results of fractional factorialdesign

Run x1 x2 x3 x4 x5 x6

Response (Percentage of total erucic acid formed)

1 −1 −1 +1 −1 +1 +1 40.92

2 +1 −1 +1 −1 −1 +1 95.27

3 +1 −1 +1 +1 −1 −1 37.91

4 −1 −1 −1 −1 −1 −1 98.10

5 +1 +1 −1 +1 −1 −1 67.82

6 −1 +1 +1 +1 −1 +1 79.10

7 +1 +1 −1 −1 −1 +1 42.80

8 0 0 0 0 0 0 21.08

9 0 0 0 0 0 0 26.30

10 +1 −1 −1 −1 +1 −1 98.50

11 0 0 0 0 0 0 25.90

12 −1 +1 −1 −1 +1 +1 43.15

13 −1 +1 −1 +1 +1 −1 48.39

14 −1 −1 +1 +1 +1 −1 48.98

15 +1 +1 +1 +1 +1 +1 73.77

16 −1 −1 −1 +1 −1 +1 55.98

17 +1 +1 +1 −1 +1 −1 35.00

18 +1 −1 −1 +1 +1 +1 52.58

19 0 0 0 0 0 0 26.98

20 −1 +1 +1 −1 −1 −1 37.83

Table 3. Experimental design and results of the steepest ascent path

Run No. pHEnzyme concentration

(mg/g oil)Concentration of Span 80

× 103 (M in oil)Concentration of Tween 80 ×

103 (M in buffer)Response (Percentage of total

erucic acid formed)

Origin 8.0 6 10.0 3 25.07

1 8.2 6 9.8 3 28.47

2 8.4 6 9.6 3 33.43

3 8.6 6 9.4 3 66.33

4 8.8 6 9.2 3 72.25

5 9.0 6 9.0 3 32.37

6 9.2 6 8.8 3 28.25


Y = 50.80 + 4.05q1 + 6.30q2 + 3.48q3 + 4.97q4 − 11.26q12

+ 7.15q22 − 8.26q3

2 + 6.68q42 − 11.15q1q2 + 3.52q1q3

+ 3.58q1q4 − 5.50q2q3 − 2.15q2q4 − 5.68q3q4 (6)

Table 6 presents the significance of each coefficient on

the basis of their probability values (p-values). Smaller p-

values indicate greater significance of the corresponding

coefficient [31]. The first order main effect of pH was not

significant (p = 0.073), whereas its quadratic main effect (p

< 0.001) was highly significant. So, a small change in pH

could markedly change the response. The first order main

effect of the Span 80 concentration was not significant (p

= 0.119), but its quadratic effect was highly significant (p

= 0.001). So, a small change in Span 80 concentration

could also lead to a large variation in erucic acid formation.

Both first order (p = 0.009) and quadratic (p = 0.002) main

effects of enzyme concentration were significant, indicat-

Table 4. Experimental range and levels of the independent variables for central composite design

VariablesRange and levels

−2 −1 0 1 2

pH (q1)Enzyme concentration (q2) (mg/g oil)Concentration of Span 80 (q3) × 103 (M in oil)Concentration of Tween 80 (q4) × 103 (M in buffer)

6.825.21

7.847.22

8.869.23

9.88

11.24

10.81013.25

Table 5. Full factorial central composite design matrix of four variables in coded and natural units along with the observed response(Percentage of total erucic acid formed)

Obs.No.

q1 q2 q3 q4 pH Enzyme

concentration(mg/g oil)

Concentration of Span 80 × 103

(M in oil)

Concentration of Tween 80 × 103

(M in buffer)

Percentage of total erucic acid formed

(%)

1 −1 −1 −1 −1 7.8 4 7.2 2 2.36

2 1 −1 −1 −1 9.8 4 7.2 2 17.00

3 −1 1 −1 −1 7.8 8 7.2 2 48.43

4 1 1 −1 −1 9.8 8 7.2 2 32.25

5 −1 −1 1 −1 7.8 4 11.2 2 39.21

6 1 −1 1 −1 9.8 4 11.2 2 57.30

7 −1 1 1 −1 7.8 8 11.2 2 52.56

8 1 1 1 −1 9.8 8 11.2 2 45.95

9 −1 −1 −1 1 7.8 4 7.2 4 16.50

10 1 −1 −1 1 9.8 4 7.2 4 69.36

11 −1 1 −1 1 7.8 8 7.2 4 77.83

12 1 1 −1 1 9.8 8 7.2 4 36.89

13 −1 −1 1 1 7.8 4 11.2 4 30.08

14 1 −1 1 1 9.8 4 11.2 4 72.19

15 −1 1 1 1 7.8 8 11.2 4 44.63

16 1 1 1 1 9.8 8 11.2 4 57.74

17 −2 0 0 0 6.8 6 9.2 3 3.39

18 2 0 0 0 10.8 6 9.2 3 13.50

19 0 −2 0 0 8.8 2 9.2 3 67.36

20 0 2 0 0 8.8 10 9.2 3 96.78

21 0 0 −2 0 8.8 6 5.2 3 24.32

22 0 0 2 0 8.8 6 13.2 3 16.54

23 0 0 0 −2 8.8 6 9.2 1 77.92

24 0 0 0 2 8.8 6 9.2 5 82.47

25 0 0 0 0 8.8 6 9.2 3 50.50

26 0 0 0 0 8.8 6 9.2 3 52.56

27 0 0 0 0 8.8 6 9.2 3 50.00

28 0 0 0 0 8.8 6 9.2 3 48.70

29 0 0 0 0 8.8 6 9.2 3 52.00

30 0 0 0 0 8.8 6 9.2 3 51.00


ing a highly influential impact of enzyme concentration on

response. In addition, the first order main effect of concen-

tration of Tween 80 was significant (p = 0.032) and its

quadratic effect was highly significant (p = 0.004), indicat-

ing a significant effect of concentration of Tween 80 on

response. Thus, enzyme concentration and concentration of

Tween 80 were the most significant variables. In particular,

the Tween 80 concentration was more important than the

concentration of Span 80 in controlling response. This

results was consistent with earlier observations that Tween

surfactant stabilizes aqueous film more than Span surfactant

[48,49]. Presently, the volume fraction of emulsified oil in

the aqueous phase was also much higher for the Tween

surfactant than for the Span surfactant. Pure Tween is

much more surface active than pure Span surfactant. As

Tween is normally more adsorbed, its Gibbs elasticity is

higher leading to a decrease in the interdroplet film

thinning rate and decreased probability of rupture [48]. The

lower interfacial tension in systems containing Tween

surfactant favors film stability, as it reduces the capillary

pressure of the droplets and, consequently, the driving pre-

ssure of film thinning. The voluminous water-penetrating

polyoxyethylene chains of the Tween surfactant enhance

steric repulsion between the film surfaces and thus, de-

creases the chance of coalescence [49]. The results from

Table 6 show that the pH-enzyme concentration interaction

is highly significant (p = 0.001) among the interaction

effects. Interactions between enzyme concentration and

Span 80 concentration (p = 0.049), and between the

concentration of Span 80 and the concentration of Tween

80 (p = 0.043) were also significant.

Response for the different levels of the design variables

could also be predicted from contour diagrams (Figs. 1, 2,

3, and 4). The elliptical nature of Fig. 1 was clearly indi-

cative of a very significant interaction between pH and

enzyme concentration. The response curves in Fig. 4 were

evidence of a significant interaction between enzyme con-

centration and concentration of Span 80. But, the relatively

circular nature of Figs. 2 and 3 was indicative of an insigni-

ficant interaction between pH and both the concentration of

Span 80 and the concentration of Tween 80. The optimum

range of pH and enzyme concentration was 9.30 ~ 9.80

(Figs. 1, 2, and 3) and 2 ~ 2.50 mg/g oil (Figs. 1 and 4),

respectively. Optimum range of concentration of Span 80

was 9.2 × 10−3 – 1.02 × 10−3 M (in buffer) (Figs. 2 and 4).

The optimum range for concentration of Tween 80 was 3.7

× 10−3 – 4 × 10−3 M (in oil) (Fig. 3).

Table 6. The least squares fit and significance of regressioncoefficients in full factorial central composite design

Model termRegression coefficient

Standard error

p-value

Interceptq1

q2

q3

q4

q12

q22

q32

q42

q1q2

q1q3

q1q4

q2q3

q2q4

q3q4

50.80 4.05 6.30 3.48 4.97

−11.26 7.15

−8.26 6.68

−11.15 3.52 3.58

−5.50 −2.15 −5.68

4.212.102.102.102.101.971.971.971.972.582.582.582.582.582.58

−

0.0730.0090.1190.032

< 0.0010.0020.0010.0040.0010.1920.1860.0490.4180.043 Fig. 1. Contour plot of percentage of total erucic acid formed (%):

the effect of pH, enzyme concentration, and their mutual inter-action on erucic acid production. Other variables are fixed at theirspecified level.

Fig. 2. Contour plot of percentage of total erucic acid formed (%):the effect of pH, concentration of Span 80, and their mutualinteraction on erucic acid production. Other variables are fixed attheir specified level.


The normal (%) probability plot of the residuals (Fig. 5)

clearly demonstrated the normal and insignificant distribu-

tion of the errors. There was a good agreement between the

actual (experimental) data and the data predicted from the

model (Fig. 6).

Numerical optimization revealed that following optimal

values of design variables: pH 9.65, enzyme concentration

2.13 mg/g oil, Span 80 concentration of 9.8 × 10−3 M (in

oil) and Tween 80 concentration of 4 × 10−3 M (in buffer).

Under this optimum set of conditions, the predicted response

of the model was 99.69% in 1.25 h. An actual experiment

conducted under the same conditions achieved a 94.5%

response.

The optimal combination of design variables using only

free lipase in the absence of any surfactant was determined

to be: Temperature 24.2ºC, pH 8.7, enzyme concentration

2.71 mg/g oil, and buffer concentration 1.25 g/g oil. These

conditions produced a response of 95.5% in 6 h (un-

published results). So, the aforementioned mixed surfactant

system enhances the efficiency of the system quite effec-

tively as it reduces the reaction time by around 80%.

4. Conclusion

A mixed surfactant system consisting of oil soluble nonionic

surfactant Span 80 and water soluble nonionic surfactant

Tween 80 significantly enhances the selective production

of erucic acid. This is achieved at a particular buffer

concentration of 0.2 g/g oil specifying the advantage of

water in oil emulsion. A single surfactant system is non-

Fig. 3. Contour plot of percentage of total erucic acid formed (%):the effect of pH, concentration of Tween 80, and their mutualinteraction on erucic acid production. Other variables are fixed attheir specified level.

Fig. 4. Contour plot of percentage of total erucic acid formed (%):the effect of enzyme concentration, concentration of Span 80, andtheir mutual interaction on erucic acid production. Other variablesare fixed at their specified level.

Fig. 5. Normal % probability plot of internally studentized residuals.

Fig. 6. Comparison of predicted and actual values of response.


effective. The optimum pH of 9.65 is higher than the

optimum (8.7) in the absence of surfactant. It falls outside

the experimental range (7 ~ 9) of the FFD, proving the

necessity of steepest ascent path. The optimum enzyme

concentration is 2.13 mg/g oil, whereas it is 2.71 mg/g oil

using only free lipase without any surfactant, highlighting

the importance of mixed surfactants in reducing the con-

sumption of lipase by nearly 21%. The most important

aspect of this mixed surfactant system comprised of Span

80 and Tween 80 is in decreasing the reaction time by

nearly 80%, from 6 to 1.25 h, with a marginal advancement

of response from 95.5 to 99.69%. The constant buffer

concentration of 0.2 g/g oil is also quite lower with respect

to the optimum concentration without any surfactant (1.25

g/g oil). Only the constant temperature used (35ºC) greatly

exceeds the optimum temperature obtained in the absence

of surfactant (24.2ºC). Probability values indicate that

enzyme concentration and concentration of Tween 80 are

the two significant process variables. Quadratic main effects

of all the four process variables (pH, enzyme concentration,

concentration of Span 80 and concentration of Tween 80)

are significant. So, a small change of each of these variables

can considerably change the response. The interaction

between pH and enzyme concentration is most significant.

Interaction between enzyme concentration and concentration

of Span 80, and that between concentration of Span 80 and

concentration of Tween 80 are also significant, implying a

strong impact of these process variables on the selective

production of erucic acid.

Acknowledgement

Pure erucic acid (90%) was a kind gift from M/s Godrej

Industries Pvt. Ltd., India.

Nomenclature

b0 : Intercept in quadratic regression equation (Eq. 3)

b1,2,3,4 : Regression coefficients for first order terms of

variables in quadratic regression equation (Eq. 3)

b11,22,33,44 : Regression coefficients for second order terms of

variables in quadratic regression equation (Eq. 3)

b12,13,14,23,24,34: Regression coefficients for first order interac-

tion terms of variables in quadratic regression equa-

tion (Eq. 3)

c0 : Intercept in regression equation from FFD method

(Eq. 2)

ci : Coefficients for first order effect of variables in

regression equation from FFD method (Eq. 2)

cij : Coefficients for first order interaction effect of

variables in regression equation from FFD method

(Eq. 2)

p : Probability value (associated with a particular effect)

qi : Coded value of the i th screened variable used in

a quadratic regression equation (Eq. 3)

Qi : Uncoded value of the i th screened variable used in

a quadratic regression equation (Eq. 3)

Qi* : Uncoded value of the i th screened variable at the

centre point used in a quadratic regression equation

(Eq. 3)

∆Qi : Step change value of the i th screened variable

used in quadratic regression equation, Eq. (5.3)

r : residual in Eq. (3)

xi : The coded value of the i th independent variable

Xi : The uncoded value of the i th independent variable

Xi* : The uncoded value of the i th independent variable

at the centre point

∆Xi : The step change value

Y : The response (percentage of total erucic acid

formed) as described in Eqs. (2) and (3)

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Erucic acid production using porcine pancreas lipase: Enhancement by mixed surfactants

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