Optimization Of Multienzyme Production Biology Essay

The production of petroleum cellulosic and hemicellulosic enzyme Endoglucanase, Xylanase, and Mannanase by Aspergillus Terreus K1 in solid province agitation on Palm kernel expeller ( PKE ) was optimized by the response surface methodological analysis ( RSM ) . The consequences shows that four factors had important consequence on the enzyme production ( P & lt ; 0.05 ) , that is the temperature, wet, inoculum concentration, and initial pH. Using PKE as solid substrate, maximal endoglucanase, mannanase, and xylanase was obtained ( 17.

37 U/g, 41.23 U/g, and 53.14 U/g severally ) at 29.

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3 oC, 68.8 % wet, pH 4.9, and 6 % inoculant ) .

These activities being close to the predicted ( 18.59 U/g, 42.40 U/g, and 52.79 U/g severally ) . Confirmation of single optimisation shows that a maximal production of 18.10 U/g endoglucanase, U/g Mannanase and U/g Xylanase is possible when PKE were fermented under optimal status.

Keywords: Solid province agitation, Aspergillus terreus, Palm Kernel Expeller, Responce surface methodological analysis


Feed resources represent a major constituent of economic animate being production in Asia as the usage of certain feed resources ( e.g. soya bean and cereal ) in carnal diets creates a competitory coni¬‚ict with human nutrition ( Vasta et al.

, 2008 ) . Therefore, the debut of agro-industrial byproducts as alternate with the purpose for a realistic possible degree of production and the saving of carnal wellness is a necessity in sustainable carnal production. PKE, the chief byproduct of the palm oil industry ( PKE ) shows great possible as Malaysia is the major thenar oil exporter ( MPOB, 2012 ) . PKE is a good beginning of energy and protein for ruminants but it is meagerly used in domestic fowl provenders ( up to 20 % by weight ) ( Chong et al. , 2003 ; Soltan, 2009 ) as it contains high degree NSPs, chiefly mannans, and little sum of cellulose, xylose and other polyoses ( Jaafar and Javis, 1992 ) . This suggests that at least three chief cellulolytic and hemicellulolytic enzymes are needed to better the alimentary value of PKE.

These enzymes are used to digest the internal glycosidic bonds of cellulose, mannan and xylan ensuing in a transition to mannose, glucose and xylose, severally. Previous survey by Ng et Al. ( 2002 ) and Saen et Al. ( 2011 ) had showed that commercial enzyme can be used to degrade these hempen compounds with an addition the monosaccharide content every bit good as metabolize energy. However, most of these enzyme used in farm animal production are imported and are normally design to aim specific mark ( Ibrahim 2008 )Bioprocessing and finds of more robust tropical enzyme-producing Fungi renders its industrial application more executable and economical.

Filamentous Fungis, being first-class decomposers of vegetational stuff, have been widely used to bring forth hydrolytic enzymes for industrial application. Those belong to the genus Aspergillus has been used throughout the universe for the production of cellulase ( Bakir et al. , 2001 ) , mannanase ( Kurakake and Komaki, 2001 ; Lin and Chen, 2004 ; Puchart et al. , 2004 ) , and xylanase ( Lu et al. 2003 ) .Solid province agitation ( SSF ) has gained a renewed involvement in recent old ages for the production of many enzymes due to lower operation costs and energy demands, and simpler works equipment as compared to submerged agitation ( SmF ) ( Mitchell and Losane, 1992 ; Pandey et Al.

2001 ) . Nevertheless, efficaciousness of such SSF is dependent of assorted parametric quantities such as initial pH, temperature, wet content, and inoculant size ( Lu et al. 2003 ; Baysal et al.

2003 ) . Therefore, for development of efi¬?cient enzyme production system, some parametric quantities should be optimized due to their impact on the economic system and practicableness of the procedure. Response surface methodological analysis ( RSM ) is a aggregation of statistical techniques and a utile tools for optimization of marks metabolites as it eliminates the drawbacks of classical methods which takes into history one parametric quantity at a clip ( Liu and Wang 2007 ; Sayyad et Al. 2007 ; Deepak et Al. 2008 ) . Second-order theoretical accounts like cardinal composite design are widely used in RSM as they can take on a broad assortment of functional signifiers, and this flexibleness allows them to more closely come close the true response surface.

RMS has late used for the modeling and optimization of several bioprocess, including agitation, enzymatic reaction, merchandise recovery, and enzyme immobilization techniques ( Ismail, 2005, Levin et al 2008 ; Bonugli-Santos et Al 2010 ; Su et al. , 2011 ; Zhang et Al 2011 ) .The aim of the present survey was to use cardinal composite design ( CCD ) based Response Surface Methodology ( RSM ) to optimise the agitation parametric quantities for hemicellulase and cellulase production by A. terreus K1 in SSF utilizing PKE as exclusive C beginning.

Materials and methods


PKE were collected from two commercial meats oil extraction mills in Malaysia ; Klang and Kuantan.

The fresh sample were divided into two equal parts, where one part was instantly packed and stored at 4oC for the isolation of Fungi. The other part were grounded to uniform size of 2.5mm and stored at 4oC to be used in SSF subsequently.

Isolation and Preparation of spore suspension

For isolation of effectual fungous strains, consecutive dilution technique was used, where 0.1mL dilutant was pipetted onto murphy dextrose agar home bases, spread with a glass spreader and incubated at 30oC for 5 – 7 yearss for observation. Each settlement that was formed were transferred to a fresh PDA home bases, sub-cultured and maintained on PDA angle at 4oC with periodic ( 30-days ) sub-culturing.

Spore suspensions were prepared by adding Tween-80 ( 0.1 % ) to five-day-old civilizations grown on PDA angle at 30oC and gently brushing the mycelium with a unfertile wire cringle. Spores were counted by utilizing haemocytometer and the concentration of the spore suspension was adjusted to a i¬?nal spore count of 1.0 ten 107 spores/mL.

Screening and Identification of possible isolates

To screen for the best enzyme manufacturer, each isolates were grown in SSF at 30oC for 7-days, utilizing PKE as exclusive C beginning. The enzyme activity ( Endoglucanase, Mannanase, and Xylanase ) of each isolates were accessed.

The best enzyme manufacturer was identified by the analysis of the genomic ITS-region utilizing standard methodological analysis of White et Al. ( 1990 ) .

Optimization of Enzyme Production.

Response surface methodological analysis was used to optimise the Solid province agitation procedure for enhanced hemicellulose and cellulose production. The Design-ExpertA® Software ( Version 8.0 ) was used for the statistical design of experiments and for informations analysis. A cardinal composite design with four factors and five degrees, with six replicated Centre points, was employed.

The scope and centre point values of the four independent variables was presented in Table 1. The full experimental design with regard to the existent value of the independent variables and attained values for the response ( Cellulase, Mannanase and Xylanase activity ) , is presented in Table 2. The experiment was carried out in extra and the average enzyme activity was taken as response Y.Datas from the CCD ( Table 2 ) were analysed by the least squares method to suit the second-order multinomial theoretical account, harmonizing to the undermentioned equation:Y = Bo + B1X1 + B2X2 + B3X3 + B4X4 + B11X12 + B22X22 + B33X32 + B44X42 + B12X1X2 + B13X1X3 + B14X1X4 + B23X2X3 + B24X2X4 + B34X3X4where Y is the mensural response, B0 is the intercept term, B1, B2, B3, B4 are additive coefficient, B11, B22, B33, B14 are quadratic coefficient, B12, B13, B23, B24 are interaction coefficient and X1, X2 X3, X4 are coded independent variables.The statistical analysis of the theoretical account was performed in the signifier of Analysis of Variance ( ANOVA ) generated by Design-Expert package.

Solid province agitation

Growth medium composed grounded PKE ( 2.

5 millimeter ) , with changing pH and wet content harmonizing to the experimental design. All growing medium were sterilized by autoclaving anterior to intervention. SSF were carried out in 500 milliliters Erlenmeyer flask incorporating 30g of growing medium, inoculated with different concentration of inoculant and were incubated for 5 yearss at different temperature, harmonizing to the experimental design.

Enzyme extraction and Enzyme checks

Enzyme were extracted by agitating PKE in 50mM citrate buffer ( pH 5 ) ( 1:10 ) at 4oC for 24hr, centrifuged at 10,000 revolutions per minute for 10 min, and filtered through whatman No 1 filter paper. The filtrate used for the analysis of endoglucanase, xylanase and mannanase.Endoglucanase ( carboxymethylcellulase, endo-1,4-b-D-glucanase ; EC 3.

2.1.4 ) were determined harmonizing to the method of Grajek ( 1987 ) , whereas xylanase activity was estimatedA by method of Bailey et Al. ( 1992 ) . Concentration of free carboxymethyl glucose and xylose units which reacted with dinitrosalicylic acid reagent was estimated utilizing the DNS method ( Miller 1959 ) . Cellulase and Xylanase activity was expressed in international units ( IU ) where one IU is the sum of enzyme required to let go of 1Aµ mole glucose ( xylose in instance of xylanase assay ) equivalent in 1ml of enzyme solution in one min.I?-Mannanase check was determine based on industry protocol ( Megazyme, Ireland ) with little alteration.

About 0.2 milliliter of the antecedently prepared PKE filtrate was added to 0.2 milliliter of the substrate ( Azo-Carob Galactomannan ) solution and stirred for 5 s on a vortex scaremonger and incubated at 40A°C for 10 min. After that, 1 milliliter of ethyl alcohol ( ~95 % ) was added to the mixture and was stirred continuously for another 10 s on the whirl scaremonger. The mixture was allowed to equilibrate to room temperature for 10 min and so centrifuged at 3,000 revolutions per minute for 10 min.

The supernatant solution was poured straight from the extractor tubing into a cuvette and the optical density was measured utilizing spectrophotometer at 590 nanometer. Different concentrations of pure endo-1,4-I?-mannanase ( Megazyme, Ireland ) was used for the readying of standard curve following the same process as antecedently described.Enzyme activity assay were carried out in triplicate, where the mean enzyme activity obtained was used as the response.

Table 1. Coded values of variables used in cardinal composite design

Independent variablesDegree-2-1012Temperature ( oC )2530343742Moisture ( % )4050607080pH3.04.56.

07.59.0Inoculum ( % )3691215

Consequences and Discussion

Lignocellulosic-degrading enzyme represents enzymes that are of import in the debasement procedure of biomass cell wall.

Abilities of different Fungis for production these enzymes have been studied, and it clearly shows high fluctuation in production degree, depending on the type of C beginning used and micro-organism used ( ref ) . In this survey, easy available agricultural residues like PKE were used as the C beginning. Fungi were isolated from natural PKE obtain from commercial meat oil extraction mills by utilizing murphy dextroglucose agar. Ten Fungis were isolated in which Aspergillus terreus K1 was selected as the best lignocellulosic-degrading enzyme manufacturer.In order to obtain optimal production of lignocellulosic enzymes by Aspergillus terreus K1, four parametric quantities which affect the production of enzyme by were statistically optimized by utilizing RSM. These are temperature ( X1 ) , wet ( X2 ) , average pH ( X3 ) and inoculum concentration ( X4 ) . The maximal and minimal degrees of these parametric quantities for tests in CCD were shown in Table 1. To do the arrested development theoretical account accurate, centre point was replicated six times.

A sum of 30 experiments were performed harmonizing to the experimental design given in Table 2, together with the experimental consequences and predicted activities for each enzyme as estimated from the theoretical account equations. This attack was chosen in order to continue the significance of the interaction consequence, which would hold been lost if the authoritative methods of changing the degree of one parametric quantity at a clip, while repairing the other variable at changeless is choosen.

Optimization of Endoglucanase production

The ANOVA sum-up for endoglucanase production is shown in Table 3. Model cogency was estimated as a map of its “ coefficients of finding ” ( R2 ) , which can provides a step of variableness in the ascertained response values that can be explained by the experimental factors and their interactions. In this experiment, a R2 value of 0.9739 indicates that the theoretical accounts were appropriate and could be used for quantitative anticipation of endoglucanase production.

In add-on, the theoretical account F-value implies that the theoretical account is important ( P & lt ; 0.01 ) , and the “ Lack of fit trial ” of 1.76 implies that it is non-significant comparative to pure mistake.Analysis of the P values is used to look into the signii¬?cance of each coei¬?cients. This analysis is required to understand the form of the common interactions between the best variables. The smaller the magnitude of the P, the more signii¬?cant is the corresponding coei¬?cient. In general, statistical analysis showed important consequence on single factor and their interaction, with exclusion to interaction between temperature and pH, wet and inoculant, every bit good as pH and inoculant ( P & lt ; 0.

05 ) . The contour secret plan of these interactions shows comparatively wide tableland part ( Figure 1 ) , intending to state that the endoglucanase activity changes a small when these factors varies.By using multiple arrested development analysis on the experimental information, a 2nd order multinomial equation was found to explicate the endoglucanase production regardless of the significance of coefficients ( Table 4 ) . The consequences predicated by the theoretical account equation showed that a combination of seting the agitation status to 30.

4oC, 60.5 % wet, pH 5.3 and 7.5 % inoculant would favor maximal endoglucanase output of 18.10 U/g, which is near to the experimental endoglucanase activity of 20.18 U/g. The larger coefficients for temperature ( X1 ) than the coefficients for other factor indicate that temperature has more important consequence on endoglucanase production.

Table 3: Analysis of discrepancy tabular array ( ANOVA ) for Endoglucanase production

BeginningSum ofSquaresdfMeanSquareF-ValueProb & gt ; FModel284.

921420.3539.97& lt ; 0.0001A-Temperature77.58177.58152.36& lt ; 0.





5110.511.010.3309Ad24.38124.3847.89& lt ; 0.0001BC9.

7819.7819.210.0005Bachelor of divinity0.2610.260.500.4894Cadmium0.

3010.300.590.4546Residual7.64150.51Lack of Fit5.

95100.591.760.2768Pure Mistake1.

6950.34Cor Sum292.5529Std. Dev.0.71R20.9739C.

V. %5.54Adjusted R20.9495Predicted R20.8556

Table 4: Predictive 2nd order multinomial equation depicting the relationship between enzyme activities of assorted enzymes

Endoglucanase16.88 – 2.

03 X1 – 0.51 X2 – 0.49 X3 – 0.72 X4 – 1.81 X12 – 1.17 X22 – 0.48 X32 – 1.

8 X42 – 0.67 X1X2 + 0.22 X1X3 + 1.49 X1X4 – 0.78 X2X3 + 0.13X2X4 + 0.

14 X3X4Mannanase36.62 – 3.39 X1 + 1.13 X2 + 1.

11 X3 – 0.75 X4 – 4.73 X12 – 5.22 X22 – 5.36 X32 + 2.80 X42 + 2.58 X1X2 – 0.28 X1X3 + 1.

79 X1X4 – 4.38 X2X3 – 2.22 X2X4 – 1.74 X3X4Xylanase49.00 – 4.40 X1 + 2.79 X2 – 6.

18 X3 – 4.76 X4 – 3.17 X12 – 0.70 X22 – 1.

20 X32 – 3.99 X42 + 10.74 X1X2 + 4.

53 X1X3 + 6.68 X1X4 – 4.09 X2X3 + 0.58 X2X4 – 3.24 X3X4where X1, X2, X3 and X4 are coded values of temperature, wet, pH and inoculant severally.a )B )degree Celsiuss )Figure 1: Contour secret plan demoing the consequence of a ) Temperature and pH ; B ) Moisture and Inoculum ; degree Celsius ) pH and Inoculum on the production of endoglucanase.

Optimization of Mannanase production

The R2 value of 0.9884 indicated that 98.84 % of the entire variableness in the response could be explained by the 2nd order multinomial equation ( Table 4 ) . The exemplary F-value of 85.18 indicates that the theoretical account were important and there was merely a 0.01 % opportunity that a “ theoretical account F-value ” this big could happen due to resound ( P & lt ; 0.

01 ) . Furthermore, the “ Lack of fit trial ” of 1.52 implies that it is non-significant comparative to pure mistake. The coefficient of fluctuation ( CV ) is the ratio of the standard mistake of estimation to the average value of the ascertained response, and as a general regulation a theoretical account can be considered moderately consistent if the CV is non greater than 10 % . Here, the low values of CV ( 5.

84 % ) indicated great dependabilities of the experiments performed. All these consequences ( Table 5 ) showed a good understanding between the experimental and predicted values and implied that the mathematical theoretical accounts were suited for the simulation of mannanase production in the present survey.Based on the statistical analysis, merely the interaction between temperature and pH had no important consequence ( P & lt ; 0.05 ) on mannanase production. The three dimensional response surface and contour secret plan ( Figure 2 ) were used to stand for the interaction between temperature and pH, in which it shows round contour secret plan of response surfaces bespeaking that the consequence of temperature on mannanase production is non dependent on initial pH, and frailty versa.

By work outing the opposite matrix, the optimum values for mannanase production of four variables in uncoded units were 31.2oC, 60.8 % wet, pH 6.4 and 6.00 % inoculant. Under the optimal status, the predicted maximal mannanase production was 42.03 U/g, which is near to the existent mannanase activity of 52.29 U/g.

Figure 2: Three dimensional Response surface secret plan demoing the consequence of temperature and pH, and their interaction consequence on production of mannanase.

Table 5: Analysis of discrepancy tabular array ( ANOVA ) for Mannanase production

BeginningSum ofSquaresdfMeanSquareF-ValueProb & gt ; FModel2967.3014211.9585.

18& lt ; 0.0001A-Temperature197.751197.7579.48& lt ; 0.





981322.98129.81& lt ; 0.0001Bachelor of divinity68.08168.0827.360.0001Cadmium41.


83142.49Lack of Fit13.6791.520.360.9139Pure Mistake21.

1754.23Cor Sum2967.3014211.9585.18& lt ; 0.0001Std.


9884C.V. %5.84Adjusted R20.9768Predicted R20.


Optimization of Xylanase production

The statistical signii¬?cance of the i¬?tted theoretical account was evaluated which is indispensable for finding forms of interaction between experimental variables ( Table 6 ) . As ascertained, the computed theoretical account ‘s F-value of 44.58 with a chance value P & lt ; 0.01 indicated that the selected quadratic arrested development theoretical account i¬?tted good to the experimental information. The deficiency of i¬?t F-value ( 3.83 ) implied that the deficiency of i¬?t was insignii¬?cant and therefore the theoretical account provided a good i¬?t to the informations.Table 2 shows the outputs of xylanase produced by Aspergillus terreus K1.

As can be seen, highest xylanase ( 67.67 U/g ) was produced when it was grown at 30 oC, initial wet of 70 % , pH 4.5 and inoculum size of 6 % ( Run 11 ) whereas, the minimal xylanase activity ( 22.53 U/g ) was produced when the agitation procedure was conducted at incubation temperature, wet, pH and inoculant of 25oC, 60 % , pH 6 and 9 % , severally ( Run 8 ) .

By using multiple arrested development analysis to the trial consequences, the second-order multinomial equation stand foring xylanase production was obtained ( Table 4 ) . Using the design Expert package, the optimum status for xylanase production were predicted to be at 29.3oC, 69.6 % wet, pH 4.6 and 7.

7 % inoculant, with output of 69.04 U/g Xylanase, which is near to the existent mannanase activity of 63.73 U/g.

By analyzing the consequence of temperature ( repairing the other variable at zero degree ) , it can be seen that the optimal temperature for xylanase production would hold been at 36.5oC ( Figure 5 ) . In order to convey the incubation temperature to approach ambient without impacting the enzyme production, we can modified the other variable, in this instance, little alteration in pH ( seting pH 4.5 to pH 4.

6 ) can greatly cut down the incubation temperature ( from 36.5oC to 31.9oC ) .

Table 6: Analysis of discrepancy tabular array ( ANOVA ) for Xylanase production

BeginningSum ofSquaresdfMeanSquareF-ValueProb & gt ; FModel3054.8714218.

2044.85& lt ; 0.0001A-Temprature166.201166.2034.16& lt ; 0.0001B-Moisture142.


51& lt ; 0.0001D-Inoculum439.571439.5790.35& lt ; 0.0001AB875.

381875.38179.92& lt ; 0.0001Actinium156.131156.1332.090.

0001Ad367.191367.1975.47& lt ; 0.0001BC205.561205.5642.25& lt ; 0.

0001Bachelor of divinity3.8013.800.780.3943Cadmium120.

071120.0724.680.0003Residual58.38124.87Lack of Fit26.8373.

830.610.7354Pure Mistake31.5556.31Cor Sum3113.2526Std. Dev.2.

21R20.9812C.V. %5.03Adjusted R20.9594Predicted R20.


Optimization of multienzyme production

The co-production of endoglucanase, mannanase and xylanase can be found in many enzyme production systems when turning micro-organism in agrobio-waste. Nevertheless, the efficient production of this enzyme mixture is dependent on assorted factors. As shows by current determination in this paper, it is noted that each single enzyme typically being produced under different set of status. In order to happen the best environment for the coproduction of these enzyme ( with emphasize of mannanse production ) , optimisation were done by utilizing Design-Expert package with the activity of all three enzyme were used as response. It is predicted that by incubating of PKE at 30.5 oC, 62.7 % wet, pH 5.8, and 6 % of A.

terreus K1 spore ( 1.0 x 10-7 spores/ml ) , a maximal endoglucanase, mannanase, and xylanase can be obtained ( 17.37 U/g, 41.23 U/g, and 53.14 U/g severally ) .

Confirmation of this predicted status were conducted as triplicate and the enzyme activity obtain ( 18.59 A± 1.39 U/g, 42.40 A± 4.89 U/g, and 52.

79 A± 4.80 U/g severally ) is close to the predicted value.It is said that enzyme production are subjected to initiation or katabolic repression. Since PKE constitute chiefly mannan polymer, it is expected that mannanase will be the major enzyme produced harmonizing to the survey by Lee ( 2007 ) . However, consequences of this survey shows otherwise. The higher xylanase activity could be due to the initiation by both xylan and cellulose nowadays in PKE itself ( Biely et al. , 1985 ; Royer and Nakas 1989 ; Tuohy et al. , 1992 ) or throught the initiation by end-product of mannanase action ( Sachslehner et al.

1997 ) . Another point of position is that the production of mannanse is growth-dependent and is an induced enzyme ( Feng et al. 2003 ) . When proper induceer is present, mannanase will be produced, but one time depleted or when the cell are in stationary stage, the production will discontinue instantly.Temperature represents one of the chief factors impacting the growing of Fungi.

Fungus kingdoms have been shown to be able to digest broad scope of temperature, typically from 30-40oC, with some are able to last in utmost temperature ( Vandamme et al. , 2007 ; Chellapandi and Jani, 2009 ; Sohail et al. , 2009 ; Facchini et al. , 2010 ; Tao et al. , 2010 ; Wang et Al.

, 2006 ; Lin and Chen, 2004 ; Kurakake and Komaki, 2001 ) . Despite the broad temperature tolerance, the optimal temperature predicted to be 30oC in this survey, a temperature which is near to the natural home ground this Fungi were isolated. Similar to the production of endoglucanase, the production of mannanase are much more affected by alterations in temperature, where temperature above 32oC grade a lessening in mannanase productiveness. It is proposed that the messenger RNA involve in the synthesis mannanase are merely stable within a certain temperature scope, whereby lessening in temperature will bit by bit stabalize and protract the production of this enzyme, but below the scope will discontinue mannanase production due to diminish in biochemical procedure ( Feng et al. 2003 ) . This is non the instance for xylanase production,Unlike the mannanase and endoglucanase production, xylanase production seems to be more significantly affected by alterations in pH ( as shown by the larger value of coeeficient estimination, X4 ) .

Based on the clip class of enzyme production survey by Lee ( 2007 ) , it is observed that the production of mannanse occur during growing of fungal, whereas the optimal production of endocglucanase and xylanase occurs subsequently. During the growing of fungal, pH will diminish ab initio and so somewhat increase with incubation clip due to the accretion of soluble cut downing sugar ( Kurakake and Komaki, 2001 ) . Therefore, excessively low initial pH will impact the production of mannanase, but excessively high of initial pH will take to excessively alkaline environment which might discontinue the subsequent endoglucanase or xylanase production.


In this present survey, multienzyme ( cellulose, mannanase and xylanase ) production by the fungous Aspergillus terreus K1 by utilizing an agrobio-waste merchandise was successfully optimized utilizing the cardinal composite design. The application of inexpensive petroleum enzyme mixture as carnal provender additive may, in some instances to be more efficient than the usage of pure enzyme in term of production cost and other constituents present in the petroleum enzyme may stabilise the enzymes.

Furthermore, the pertinence of the statistical attack were proven to be a powerful attack as it can foretell the overall co-production of enzyme with minimum figure of experimental points. Therefore, this fungus isolated could be an attractive alternate beginning of cellulosic and hemicellulosic enzyme manufacturer, which have gained an involvement in recent old ages for the efficient use of PKE as carnal provender.

Table 2. Central composite design matrix with experimental and predicted values of endoxylanase production by Aspergillus terreus

Trial NumberVariableCellulaseXylanaseMannanaseX1X2X3X4ExperimentalPredictedExperimentalPredictedExperimentalPredicted1-200010.8311.3850.5752.4017.7918.572-1-1-1-117.2116.6248.5349.4733.9236.163-11-1-111.1811.5555.2455.3523.7424.094-1-11-115.8915.9339.5539.1222.1221.525-111-113.3213.4246.3356.5329.4128.226-1-1-1110.4511.0748.6549.6430.3030.317-11-119.8910.5141.3641.4547.6848.438-1-11112.8313.7018.9327.5322.9824.499-111114.1214.1649.4647.8931.6230.1210000-29.088.3327.0025.5745.7646.291100-2018.0317.3467.6769.4128.0433.61120-2006.555.6046.0345.1411.6110.9513000016.8215.8833.7133.9637.7737.3414000017.0816.6250.5949.4738.0236.1615000010.7210.8946.4045.5810.249.211600007.747.6132.3933.9225.9325.3817000011.8111.5124.3723.9324.9924.9918000016.7216.6248.3249.4738.2336.1619020015.9216.6251.0149.4733.7936.1620002011.6212.0014.065.7934.6733.8621000210.6410.7551.8549.7116.8318.16221-1-1-116.9216.6245.8249.4737.4736.162311-1-112.2112.5949.9649.2026.9426.50241-11-115.8816.6253.0049.4735.1136.1625111-115.8415.6556.9155.9812.6812.56261-1-119.9910.0740.1540.5029.8429.812711-1111.3410.7820.3022.0318.1217.78281-1118.6519.1529.2230.0819.2618.9329111113.3413.1042.8143.6012.4912.4330200013.7113.7833.7933.3915.4716.86


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