Optimization of Temperature, Moisture Content and Inoculum Size in Solid State Fermentation to Enhance Mannanase Production by Aspergillus terreus SUK-1 using RSM
Jahwarhar Izuan Abdul Rashid,
Wan Mohtar Wan Yusoff
Optimization of three parameters, temperature (25-35°C), moisture content (40% (w/v)-60% (w/v) and inoculum sizes (5% (w/v)-15% (w/v) were investigated and optimized by Response Surface Methodology (RSM) for optimal mannanase production by Aspergillus terreus SUK-1. A second order polynomial equation was fitted and the optimum condition was established. The result showed that the moisture content was a critical factor in terms of its effect on mannanase. The optimum condition for mannanase production was predicted at 42.86% (w/v) initial moisture (31°C) temperature and 5.5% (w/v) inoculum size . The predicted optimal parameter were tested in the laboratory and the mannanase activity 45.12 IU mL-1 were recorded to be closed to the predicted value (44.80 IU mL-1). Under the optimized SSF condition (31°C, 42.86% moisture content (w/v) and 5.5% inoculum size (w/v)), the maximum mannanase production was to prevail about 45.12 IU mL-1 compare to before optimized (30°C, 50% moisture content (w/v) and 10% inoculum size (w/v)) was only 34.42 IU mL-1.
to cite this article:
Jahwarhar Izuan Abdul Rashid, Noraini Samat and Wan Mohtar Wan Yusoff, 2011. Optimization of Temperature, Moisture Content and Inoculum Size in Solid State Fermentation to Enhance Mannanase Production by Aspergillus terreus SUK-1 using RSM. Pakistan Journal of Biological Sciences, 14: 533-539.
Received: January 24, 2011;
Accepted: August 24, 2011;
Published: August 30, 2011
Agro-industrial waste represents abundant renewable carbon source generated
years from agricultural sector (Francis et al., 2003).
Palm Kernel Cake (PKC) is one such agro-industrial waste with good potential
to be used widely as a major feed ingredient for chicken feeds (Marini
et al., 2006). Since most of PKC consists of mannan that can be degrade,
the PKC has gained interest as an inexpensive substrate for the production of
mannanase enzyme especially in Solid Substrate Fermentation (SSF). SSF is defined
as process performed in the absence or near-absence of free water, employing
a natural substrate or an inert support (Sabu et al.,
2006). SSF has many advantages to enhance microbial enzyme production since
it is economical technology due to its low capital investment and low operating
expenses (Latifian et al., 2007). Selection of
process parameters and their optimization are other key aspects of SSF including
parameters such as moisture content, incubation temperature and age and size
of inoculum (Manpreet et al., 2005).
Mannan degrading enzyme have been reported to be produced by several filamentous
fungi such as Aspergillus niger (Abdeshahian et
al., 2010), Trichoderma reesei (Atisan-Atac
et al., 1993), Trichoderma harzianum (Torrie
et al., 1990) and Sclerotium rolfsii (Gubitz
et al., 1997). Filamentous fungi are commonly used in industrial
enzyme since have ability to secrete large amount of protein into the growth
medium. Meanwhile, Aspergillus species have been known as potential fungi
in the production of a wide range of microbial enzyme (Gao
et al., 2008).
Mannanase have been found practical in several industrial purpose including
improving the quality of animal feed stuff, bioleaching of pulp in the paper
industry, bioconversion of biomass wastes to fermentable sugar and reducing
the viscosity of coffee extract (Wong and Saddler, 1993;
Gubitz et al., 1997; Chandrakant
and Bisaria, 1998; Hagglund et al., 2003).
Furthermore, the mannooligosaccharides which derived from the hydrolysis of
mannanase and mannan have been report to use as no nutritional food additives
selective growth of human-beneficial intestinal micro flora, bifidobacterium
species (Tomori, 1990).
Response Surface Methodology (RSM) is a collection of statistical techniques
for experiment designing, model developing, factors evaluating and optimum conditions
searching (Myers and Montgomery, 2002). RSM could overcome
the shortcoming of the classical or empirical methods such as one-factor at-a-time-technique
which is time-consuming process but also can led misinterpretation of results,
especially because the interaction between different factors is overlooked (Lotfy
et al., 2007). The aim of this study was to evaluate the effects
of moisture content, temperature and inoculum size on mannanase production by
our locally strain, Aspergillus terreus SUK-1 using RSM and to search
for optimal condition to achieve a maximum mannanase production.
MATERIALS AND METHODS
Microorganism: A local isolate, Aspergillus terreus SUK-1 from School of Biosciences and Biotechnology, Universiti Kebangsaan Malaysia, were grown and maintained on Potato Dextrose Agar (PDA). Spore suspension of 107 spore mL-1 was prepared by harvesting from 7 days old cultures of both molds with 15 mL sterile distilled water and 10% (w/v) of inoculum (of the tested ratios) was used in all experiments.
Substrate and medium: Palm kernel cake was supplied by MARDI and used
as a solid substrate and PKC was ground to a particle size of 2 mm. The medium
employed (Sternberg, 1976) are shown in Table
Solid state fermentation: Fermentation was carried out in Erlenmeyer
flask 250 mL containing 25 g of Palm Kernel Cake (PKC) and Sternbergs
medium (Sternberg, 1976). The mixtures were autoclaved
at 121°C for 15 min. Each flask was then inoculated spore suspension of
A. terreus SUK-1. All flasks were incubated for 4 days. Duplicate flasks
were set up under various experiments according the experimental design.
Crude enzyme extraction: Mannanase enzyme was extracted from fermented PKC by adding 100 mL of distilled water into the flask containing 10 g of PKC and agitated at 150 rpm for 24 h at 10°C. The suspended materials and fungal biomass were then separated by filtration using Whatman filter paper No. 1. The clarified extract was used as the source of mannanase enzyme.
Enzyme assay: Mannanase activity was carried out according to the method
described by McCleary (1978) using Azo Carob Galactomannan
as substrate. One unit (U) of mannanase activity was defines as mannose released/min/g
|| Fermentation medium for mannanase production
|| Range of variables and their coded levels
|a: Temperature at low level (-1) of 25°C and high level
(+1) of 35°C, b: Moisture content at low level (-1) of 40 (w/v) and
high level (+1) of 60 (w/v), c: Inoculum size at low level (-1) of 5 (%
w/v) and high level (+1) of 15 (w/v)
Experimental design: The optimization of mannanase production by A.
terreus SUK-1 was carried out using Response Surface Methodology (RSM).
The variables used were temperature (a), moisture content (b) and inoculum size
(c) and the coded value of variables were -1,0,1 (low, basal low, high) (Table
2). Nineteen experiments were performed for each microorganism at three
levels including five replicates at the center points with three variables according
second order face-centered composite design (Table 3). Analyses
were carried out in duplicate. The experimental data were employed in statistical
package, software Design Expert 6.0 (StatEase Inc. Minneapolis, USA) to fit
a second order polynomial response surface methodology according to Eq.
where, Y is the mannanase activity IU mL-1, X0, X1,......, X23 represent the estimated regression coefficients, X1, X2, X3 represent the linear effect, X11, X22, X33 the quadratic effect and X12, X13, X23 cross product coefficient A, B and C represent variables (temperature, moisture content, inoculum size).
RESULTS AND DISCUSSION
The experimental design and result of experiment are presented in Table
3. The result of the second ordered response surface model for mannanase
production in the form of Analysis of Variance (ANOVA) was given in Table
4 and 5. The Analyzed of Variance (ANOVA) was carried
by Fishers F-test and F value is the ratio of the mean square due to regression
to the mean square due to error (Francis et al., 2003).
|| Experimental Central Composite Design (CCD) with experimental
value and predicted value on mannanase production by A. terreus SUK-1
||Analysis of Variance (ANOVA) for regression model to optimize
|SS: Sum of squares, DF: Degree of freedom, MS: Mean squares,
SV = 4.39 PRESS = 689.40
|| Regression coefficient for optimization of mannanase production
The model F-value of 10.82 implied that the model was significant and there
was only a 0.08% chance that a Model F-value this large could occur
due to noise. The pure error was very low (20.02), indicating good reproducibility
of the experimental data. The p value was used as a tool to check significant
of each coefficient which in turn may indicate the pattern of the interaction
between the variables (Bahceci and Acar, 2007). The
smaller the p-value, the more significant is the corresponding coefficient The
value probability >F less than 0.05 indicated the model term were significant.
||Standard Pareto chart of the important of effect of variables
(A: Temperature, B: Moisture content) for mannanase production by A.
The analyzed regression model as given in Table 5 suggested
that the linear coefficient (B) and quadratic terms coefficient (A2,
B2) were significant whereas the other terms coefficient included
cross product coefficient (C, C2, AB, AC, BC) were not significant.
The significance of quadratic term of temperature (A2) and moisture
content (B2) indicated that these factors can act as limiting factor
and even small changes in value can be the cause of the big influence on mannanase
production (Box et al., 1978).
The Importance of each effect can be determined by the size of the coefficient
which have been standardized (each effect is divided by its standard error)
(Fig. 1). The size of each coefficient gives a direct measurement
of the important of each effect (Psomas and Kyriakides,
2007). Figure 1 clearly showed that the moisture content
was the most influenced factor on mannanase production as the bar are displayed
on the top correspond to the most important effect (show only model term significant).
However, there is no report available in the literature about the importance
of effect moisture content on mannanase production by A. terreus SUK-1
but similar result was report by Latifian et al.
(2007) that the moisture content was strongly sensitive for cellulase production
by Trichoderma reesei mutant under SSF. The model second order polynomial
equation fitted by regression analysis was:
where, Y is the mannanase activity IU mL-1, A is the temperature (°C), B is the moisture content (% (w/v)) and C is inoculum size% (w/v)).
The goodness of fit of the model can be checked by Lack of fit-test, Coefficient
of determination R2, Coefficient of Variance (CV), Prediction Residual
Error Sum of Squares (PRESS) and adequate precession (Bahceci
and Acar, 2007). The proposed model is adequate to described data when the
lack of fit-test did not result in significant (p<0.05) (Table
3). The coefficient of determination, R2 give the information
how much of the variability in the observed data could be explained by the experiment
and their interaction (Kawaguti et al., 2006).
The Coefficient of determination, R2 (0.9154) suggested that about
91.5% variability in the model could be explained and about 8.5% of the total
variation cannot be explained by the model. The closer R2 value to
1.0, the stronger the model to make a prediction to the response (Haaland,
1989). The good model exhibit low standard deviation, high value of R2
and a low PRESS (Table 3). Adequate precision measures
signal to noise ratio where it can compares the ranges of the predicted values
at the design point to average prediction error. A ratio greater than 4 is desirable
as it indicates adequate model discrimination. On this particular case, the
value of 11.372 is well above 4 and the model can be used to navigate the design
Figure 2 shows the effect of temperature and moisture content
at fixed inoculum size of 10% (w/v). An increased in production of mannanase
was observed at the range moisture content of 40-50% and a temperature range
of 31-28°C. Comparable results were obtained that at the 50% of moisture
content, the maximum mannanase production was achieved optimization experiment
by Aspergillus niger using PKC as a sole carbon sources (Ong
et al., 2004). In contrast, Abdeshahian et
al. (2010) have shown that the cultivation of A. niger using
PKC as the sole carbon sources under SSF leads to the production of maximum
levels of mannanase when moisture level increased from 40 to 60% and the level
of mannanase production began to reduce when the higher level of moisture content
||The effects of temperature and moisture content on mannanase
production by A. terreus SUK 1
||The effects of inoculum size and temperature on mannanase
production by A. terreus SUK-1
Increasing the moisture content can leads to decrease the porosity of substrate
thus limiting the oxygen transfer into the substrate all of which, in turn,
result in decreases fungi growth and product formation. Meanwhile, a lower of
moisture content can reduced the solubility of the nutrient of the substrate,
lower degree of swelling and a higher water tension (Kheng
and Omar, 2005).
Figure 3 shows the effects of inoculum size and temperature
and at fixed moisture content of 50% (w/v) on mannanase production. The maximum
mannanase production was obtained at the range of 29-31°C and out of from
this range brings the negative effect on mannanase production. As it was reported
the optimum of mannanase production under SSF was obtained at temperature of
30°C (Feng et al., 2003). The author reported
that the mRNA of this enzyme is not stable and within a certain temperature
range, an appropriate decrease in temperature would enhance the stability of
the mRNA and prolong the duration of enzyme production.
||The effects of inoculum size and moisture content on mannanase
production by A. terreus SUK-1
||Profiles of mannanase production under SSF before (30°C,
50% moisture content (w/v) and 10% inoculum size (w/v)) and after optimization
((31°C, 42.86% moisture content (w/v) and 5.5% inoculum size (w/v))
of cultural condition by RSM
This statement may be able to explain the phenomenon of inactivation mannanase
enzyme out of temperature range in this study. The result of this study were
consistent with the findings obtained by Abdeshahian
et al. (2010) and Lin and Chen (2004) who reported
that at 30°C leads to the production of maximum level of mannanase.
Figure 4 shows the effect of inoculum size and moisture content
at fixed the temperature of 30°C on mannanase production. As shown in the
Fig, the factor of moisture content had a great influenced on mannanase production
than inoculum size which was not varies much can be observed on mannanase production
whether increasing or decreasing the inoculum size. It can be concluded that
the inoculum volume (5-15% (w/v)) of 107 spore mL-1 did
not bring much significant increase in mannanase production. However, changing
the inoculum concentration ranging from 1x104-1x108 spore
mL-1 significantly influenced of mannanase production (Abd-Aziz
et al., 2003). Rashid et al. (2011)
reported that the inoculum size of 1x107 spore mL-1 leads
to the maximum mannanase yields by A. niger using PKC as the substrate
under SSF. Different observation in the study of Abd-Aziz
et al. (2003), who reported that the inoculum size of 1x104
was enough to enhance mannanase enzyme activity by A. niger under
submerged fermentation. Therefore, a balance correlation between proliferating
biomass and available materials are important in order to achieve maximum enzyme
production (Rauf et al., 2010). In the Fig.
2 and 3, even small changes value of moisture content
triggers the maximum production of mannanase. The maximum of activity mannanase
predicted from the model was 45.50 IU mL-1 under the optimal condition
(31°C, 42.86% moisture content (w/v) and 5.5% inoculum size (w/v)).
To verify the predicted optimum of mannanase production, the experiment was repeated in triplicate for 96 h. The results showed that the mannanase activity was closed to the predicted value (45.50 IU mL-1) to 44.80 IU mL-1 thus confirming the model validity. Figure 5 shows the profiles mannanase production by A. terreus SUK-1 before optimization and after optimization of condition by RSM. This Figure clearly shows that the optimization experiment by RSM method can improved the mannanase production by A. terreus SUK-1. Under the optimized condition, the highest activity mannanase enzyme was about 45.12 IU mL-1 than before under optimized was only about 34.42 IU mL-1.
Using Response Surface Methodology (RSM), it was possible to know that the moisture content was the most influenced factor on mannanase production among the variables tested in this study. Furthermore, the optimal condition for mannanase production can be predicted by this method. By this method, the optimum of mannanase production was achieved about 44.80 IU mL-1 at the condition of, 31°C, 42.86% (w/v) moisture content and 5.5% (w/v) inoculum size thus confirming the model validity where the experiment data agreed fittingly at the predicted optimal condition. Under optimized condition, the maximum mannanase production was produced of 45.12 IU mL-1 than before optimized condition was 34 42 IU mL-1.
This study is supported by Ministry of Science, Malaysia (MOSTI) (01-03-03-003 BTK/ER/008). The authors also thank the Malaysian Agriculture Research and Development Institute (MARDI) for providing equipment and facilities during the experimental work.
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