Circumscribed Central Composite Design Research Articles

109 Evaluation of net energy, standardized ileal digestible lysine, and soybean meal content interaction in 13 to 25 kg pigs using a central composite design

Abstract Pigs [n = 4,683; 337 × 1050, PIC; initial body weight (BW) = 13.0 ± 0.01 kg] were used in a 21-d trial to investigate the interaction of net energy (NE), standardized ileal digestible lysine (SID Lys), and soybean meal (SBM) content used at five different levels on growth performance of nursey pigs. Pigs were housed in mixed sex pens with 35 pigs per pen and assigned in a randomized complete block design to 15 dietary treatments using a circumscribed central composite design (CCD). Factorial and axial points had 7 repetitions, and the central points had a total of 24. Eight diets were formulated to various levels of NE, SID Lys, and SBM and blended to create the 15 dietary treatments. The NE ranged from 2,334 to 2,762 kcal/kg, SID Lys from 1.08 to 1.52%, and SBM from 25.5 to 35.9%. Diets were corn-soybean meal based and soy hulls and soybean oil were added to reduce or increase NE content of the diet. Feed grade amino acids and SBM were used to adjust SBM and SID Lys content and to maintain SID Thr, Trp, Met, Val, and Ile ratios relative to SID Lys. For NE, a linear effect (P ≤ 0.052) was observed for average daily gain (ADG) and average daily feed intake (ADFI), and linear and quadratic effect was found (P ≤ 0.047) for gain to feed ratio (G:F) with a reduction in growth performance as NE increased due to reduction in SID Lys:calorie. When increasing SID Lys, ADG (P ≤ 0.044) and G:F (P ≤ 0.020) increased quadratically (Table). Increasing SBM content linearly improved ADG (P = 0.039) and G:F (P < 0.001), respectively. There was also a significant interaction between SID Lys and SBM for G:F (P = 0.082), where SID Lys positively impacted G:F as SBM increased in the diet. When including the significant terms, the resulting models can be used to predict the ADG (kg) response = [0.579392 + (-0.0063389 × NE) + (0.0260796 × Lys) + (0.0067428 × SBM%) + (-0.0065721 × Lys²) adjusted R2 = 0.36], and G:F (kg/kg) response = [0.7013215 + (0.0035198 × NE) + (0.0264389 × Lys) + (0.0060863 × SBM%) + (-0.0048012 × NE²) + (-0.0031838 × Lys²) + (-0.0034413 × Lys × SBM) adjusted R2 = 0.65]. In conclusion, using a CCD, increasing SID Lys resulted in a quadratic improvement in ADG and G:F, with this improvement being greater when SBM also increased. Overall, we observed few interactions between SID Lys, SBM, and NE.

A quality by design framework for developing nanocrystal bioenabling formulations

The present study aims to outline a rational framework for the design and development of a 1.0% (w/v) hydrocortisone nanocrystal-based formulation, resorting to a simple, efficient, and scalable nanonization methodology, based on the high-pressure homogenization (HPH) technique. Accordingly, the innovative product was comprehensively optimized following a Quality by Design (QbD) approach. The thorough selection of formulation composition was driven by a dual purpose: improving skin permeation and stability. In the early stage of development, a Failure Mode, Effects and Criticality Analysis (FMECA) diagram was employed to identify the most impactful variables for the critical quality attributes (CQAs). In this sense, a rotatable, three-factor and five-level circumscribed central composite design (CCCD) was applied to investigate how squalene concentration (x1), soluplus concentration (x2) and HPH-time (x3) influence physicochemical properties, performance and physical stability of the formulation. A robust Design Space (DS) was defined, establishing the optimal settings for the critical variables, whose combination meets the requirements set in the quality target product profile (QTPP). Morphological analysis revealed the cuboidal shape of hydrocortisone nanocrystals. In what concerns colloidal properties, the most promising formulation disclosed a small particle size (Dx(50) = 311.8 ± 1.5 nm), along with narrow size distribution (span value = 1.91 ± 0.17). Zeta potential results (−2.19 ± 0.15 mV–−12.1 ± 0.4 mV) suggested a steric hindrance stabilization. FTIR spectra showed no chemical interactions between drug and formulation components. XRD diffractograms confirmed loss of crystallinity during the downsizing process. In vitro studies revealed an improvement on drug release rate (316 ± 21–516 ± 35 μg/cm2/√t), compared to the coarse suspension and commercial products, and a straight dependence on the stabilizer concentration and HPH time. The permeation flux across the skin (0.16 ± 0.02–1.2 ± 0.5 μg/cm2/h) appeared to be dependent on the drug physicochemical properties, in particular saturation solubility. Further characterization of the experimental formulations pointed out the role of the stabilizing component to prevent against physical instability phenomena. This organic solvent-free, and therefore “green” nanocrystal production technology offers great potential for pharmaceutical R&D and drug delivery by enabling the development of new forms of conventional drugs with optimal physicochemical properties and performance.

MULTI-RESPONSE OPTIMIZATION OF METFORMIN -HYDROCHLORIDE DRUG VIA EXPERIMENTAL DESIGN TECHNIQUES APPLIED ON THE ADAPTIVE LOCAL LINEAR REGRESSION MODEL FOR RESPONSE SURFACE METHODOLOGY

The challenge encountered by industrial statisticians and engineers during statistical process control in other to build-up and formulates pharmaceutical optimization of drugs have prompted several choices of experimental design tool and regression models. The most commonly applied regression model is the second-order polynomial which may perform poorly due to model misspecification. In this paper, we present two experimental design methods namely; the Full Factorial Design (FFD) and the Circumscribed Central Composite Design (CCCD) applied to an existing Adaptive Local Linear Regression ( model to ameliorate the problem of boundary bias for a multi-response problem. The FFD do not make reference to the star points and as such could not address variability in the data, hence we also applied the CCCD to accommodate the star points in order to maintain rotatability and curvature in the data. In the application, we minimized Metformin Hydrochloride (Met-HCL) drug usage via FFD on and CCCD on and the results from the goodness-of-fit statistics, residual plots and optimization were obtained and analyzed. The that utilized CCCD outperformed that uses FFD in terms of the goodness-of-fit statistics, minimum residual plots as it relates to the zero residual line and optimization of Met-HCL for Response Surface Methodology (RSM) data.

Milling of pharmaceutical powder carrier excipients: Application of central composite design

Pharmaceutical powder carriers are often used to prevent agglomeration of a micronized drug in the co-milling process. Twenty-four pharmaceutical excipients were subjected to preliminary mild milling conditions in this work. Ten of them showed acceptable milling properties with alginic acid, calcium alginate, microcrystalline cellulose (Avicel® 200), carrageenan, and hypromellose having the best particle size reduction without any aggregation while maintaining a narrow span. For the latter five substances, circumscribed central composite design (CCD) evaluating the effect of the factors milling speed and timeon the responses (particle size, particle size distribution) for three milling ball sizes was used to establish optimal milling conditions. For all ten possible factor combinations and each ball size, a quadratic response surface model was used to predict the response variable. For three substances out of five, the best results were achieved using 5-mm balls. Thermal characteristics showed the good stability of excipients under optimized milling conditions.

Development of a Natural Preservative from Chestnut Flowers: Ultrasound-Assisted Extraction Optimization and Functionality Assessment

This study was carried out with the aim of optimizing the ultrasound-assisted extraction (UAE) of phenolic compounds from male chestnut flowers (C. sativa Mill) to develop a bioactive extract with potential to be used as a natural antioxidant preservative ingredient in the food industry. Time (t, 1–39 min), solvent concentration (S, 0–100%), and ultrasonic power (P, 5–500 W) were used as the independent variables for a 5-level experimental circumscribed central composite design (CCCD) coupled with response surface methodology (RSM) to optimize the extraction of phenolic compounds by UAE. Regarding the variables, the three showed a significant effect on the extraction of phenolic compounds. The content of phenolic compounds (including flavonoids and tannins) and the extraction yield (extract weight gravimetrically assessed) were the response criteria for the optimization. Based on the statistically validated predictive polynomial models, it was possible to reach a maximum content of phenolic compounds at the global optimal conditions of 24 ± 3 min, 259 ± 16 W, and 51 ± 7% ethanol. Additionally, pentagalloyl-glucoside and trigalloyl-hexahydroxydiphenoyl-glucoside were the major phenolic compounds identified. The optimized extract was then analyzed for their biological properties. The bioactive potential of the chestnut flower extract obtained under these optimized conditions was evaluated using in vitro assays for antioxidant, anti-inflammatory, and antimicrobial activity, as well as cytotoxicity and hepatotoxicity tests. The results revealed that the enriched extract has antioxidant, antitumoral, and anti-inflammatory activities without toxicity issues. Overall, this study allowed to define the optimal conditions for the extraction of phenolic compounds from chestnuts male flowers by UAE, to obtain an enriched extract with biological properties that could be further used as a natural antioxidant ingredient with applications on functional foods.

Evaluation and Comparison of Three Classes of Central Composite Designs

Three classes of Central Composite Design: Central Composite Circumscribed Design (CCCD), Central Composite Inscribed Design (CCID) and Central Composite Face-Centered Design (CCFD) in Response Surface Methodology (RSM) were evaluated and compared using the A-, D-, and G-efficiencies for factors, k, ranging from 3 to 10, with 0-5 centre points, in other to determine the performances of the designs under consideration. The results show that the CCDs (CCCD, CCFD and CCID) are at their best when the G-efficiency is employed for all the factors considered while the CCID especially behaves poorly when using the A- and D-efficiencies.

Optimization of lipid content of Nannochloropsis gaditana via quadratic models using Matlab Simulink

Nowadays, population growth has gone up the energy demand and its consumption fast. Developing countries have trended to cleaner energy from green energy sources. Photosynthetic microalgae have taken attention for biodiesel production. To get a higher efficiency from microalgae, a number of criteria such as a strain with higher biomass and lipid amount and a cost effective theoretical methods to increase the lipid productivity are needed. In this research, changes on lipid content from Nannochloropsis gaditana in Johnsons’s medium with three effective assisted lipid extraction methods including Osmotic shock (0–20 KCI %), Ultrasound (0–50 kHz) and Lysozyme (0–20 U/mL) was examined by using response surface methodology (RSM) with circumscribed central composite design (CCD). According to the RSM predicted results, the maximum lipid percentage was gained in 10 KCI % of Osmotic shock, 30 kHz of Ultrasound and 10 U/mL of Lysozyme with the lipid content of 37% of biomass. The 3D response surface plot and related 2D contour plots specifies that the assisted factors play an active role to increase lipid content. In conclusion, Nannochloropsis gaditana could meet at these conditions with high lipid content for various goals in the industry.

Application of Response Surface Methodology for Determining Optimal Factors in Maximization of Maize Grain Yield and Total Microbial Count in Long Term Agricultural Experiment, Kenya

The Agriculture sector is the main stay of the Kenyan economic development contributing over 70% of the Gross Domestic Product (GDP). The sector is faced with numerous challenges leading to frequent and recurrent food shortages. Declining maize grain yield is one among the major challenges that call for urgent interventions to address the looming food crisis in the country. Maize play a big role in the Kenyan food security and in most case lack of the same is taken to mean food insecurity. It is due the importance attached to the crop that a Long Term Agricultural Experiments (LTAE) was set up specifically to research on the Maize grain yield. Many paper published on the LTAE in the country are only single factors analysis and lack the application of Response Surface Methodology (RSM) approaches in solving challenges facing the low and declining maize grain yield (y1), total microbe population (y2) a crucial component of Soil Organic Matter (SOM) and their optimization. The focus of this paper therefore is the application of RSM in maize grain yield and total microbial population optimization. Specifically, the paper determined the most significant factors for maize grain yield and total microbial population (bacteria, fungi, actinomycetes, rhizobia), (screening phase of the paper), constructed of an efficient and appropriate experimental design for evaluating the optimal settings of maize yield and total microbial population count and determined univariate optimal settings for maize grain yield and total microbial population. The primary data was summarized from LTAE in National Agricultural Research Laboratories (NARL) in Kabete under the Kenya Agriculture and Livestock Research Organization (KALRO) and secondary data imputed for experimental points falling outside the set field experimental design points. Two treatment factors were identified as the most significant treatment factors (Farm Yard Manure (FYM) and Nitrogen and Phosphorus (NP)) at their low levels and Circumscribed Central Composite Design (CCCD) with two star points as the most efficient design. CCCD passed most optimal criteria of DAET. Univariately, optimal setting for maize grain yield was realized at 3.8x103 kg/ha and that of the total microbial population at 3.6x106 count. The study confirmed that it was possible to optimize the input treatment factor that lead to the optimization of both maize grain yield and maintaining maximal total microbial population count at its optimal levels.

Implementation of design of experiments approach for the micronization of a drug with a high brittle–ductile transition particle diameter

Objective: To optimize air-jet milling conditions of ibuprofen (IBU) using design of experiment (DoE) method, and to test the generalizability of the optimized conditions for the processing of another non-steroidal anti-inflammatory drug (NSAID).Methods: Bulk IBU was micronized using an Aljet mill according to a circumscribed central composite (CCC) design with grinding and pushing nozzle pressures (GrindP, PushP) varying from 20 to 110 psi. Output variables included yield and particle diameters at the 50th and 90th percentile (D50, D90). Following data analysis, the optimized conditions were identified and tested to produce IBU particles with a minimum size and an acceptable yield. Finally, indomethacin (IND) was milled using the optimized conditions as well as the control.Results: CCC design included eight successful runs for milling IBU from the ten total runs due to powder “blowback” from the feed hopper. DoE analysis allowed the optimization of the GrindP and PushP at 75 and 65 psi. In subsequent validation experiments using the optimized conditions, the experimental D50 and D90 values (1.9 and 3.6 μm) corresponded closely with the DoE modeling predicted values. Additionally, the optimized conditions were superior over the control conditions for the micronization of IND where smaller D50 and D90 values (1.2 and 2.7 μm vs. 1.8 and 4.4 μm) were produced.Conclusion: The optimization of a single-step air-jet milling of IBU using the DoE approach elucidated the optimal milling conditions, which were used to micronize IND using the optimized milling conditions.

Purification optimization for a recombinant single-chain variable fragment against type 1 insulin-like growth factor receptor (IGF-1R) by using design of experiment (DoE)

Design of experiment (DoE) is a statistics-based technique for experimental design that could overcome the shortcomings of traditional one-factor-at-a-time (OFAT) approach for protein purification optimization. In this study, a DoE approach was applied for optimizing purification of a recombinant single-chain variable fragment (scFv) against type 1 insulin-like growth factor receptor (IGF-1R) expressed in Escherichia coli. In first capture step using Capto L, a 2-level fractional factorial analysis and successively a central composite circumscribed (CCC) design were used to identify the optimal elution conditions. Two main effects, pH and trehalose, were identified, and high recovery (above 95%) and low aggregates ratio (below 10%) were achieved at the pH range from 2.9 to 3.0 with 32–35% (w/v) trehalose added. In the second step using cation exchange chromatography, an initial screening of media and elution pH and a following CCC design were performed, whereby the optimal selectivity of the scFv was obtained on Capto S at pH near 6.0, and the optimal conditions for fulfilling high DBC and purity were identified as pH range of 5.9–6.1 and loading conductivity range of 5–12.5mS/cm. Upon a further gel filtration, the final purified scFv with a purity of 98% was obtained. Finally, the optimized conditions were verified by a 20-fold scale-up experiment. The purities and yields of intermediate and final products all fell within the regions predicted by DoE approach, suggesting the robustness of the optimized conditions. We proposed that the DoE approach described here is also applicable in production of other recombinant antibody constructs.

Effects of water quality parameters on agglomeration and dissolution of copper oxide nanoparticles (CuO-NPs) using a central composite circumscribed design

Once released into the aquatic environment, nanoparticles (NPs) are expected to interact (e.g., dissolve, agglomerate, settle), with important consequences for particle fate and toxicity. However, a clear understanding of how environmental factors influence the toxicity and fate of NPs in the environment is still in its infancy. In this study, a second order central composite circumscribed design (CCCD) was employed to systematically explore how different combinations of pH, hardness, and natural organic matter (NOM) in receiving water affect the hydrodynamic diameter, surface charge (zeta potential), and release of free Cu2+ from CuO-NPs under a range of environmentally realistic conditions. The results clearly showed that all three CuO-NP properties varied markedly as functions of pH, hardness and dissolved NOM, confirming that agglomeration and the extent of release of free Cu2+ largely depend on the surrounding environmental conditions. The response of hydrodynamic diameter, but not zeta potential, to water quality parameters was highly time dependent, showing very different patterns on day 2 and day 10. The approach used in this study can contribute to improving understanding of how, and to what extent, environmental factors affect the physicochemical properties of CuO-NPs once they enter aquatic environments. This understanding can help to predict the conditions under which CuO-NPs are likely to become problematic, which can inform management and mitigation actions.

Dispersive liquid–liquid microextraction combined with laser-induced breakdown spectrometry and inductively coupled plasma optical emission spectrometry to elemental analysis

In this paper, two analytical methodologies based on the combination of dispersive liquid–liquid microextraction with inductively coupled plasma optical emission spectrometry and laser-induced breakdown spectrometry, respectively, were evaluated for simultaneous preconcentration and detection of Cd, Co, Ni, Pb and Zn. The microextraction procedure was based on the injection of appropriate quantities of 1-undecanol and methanol into the sample solution containing the complexes formed between metal ions and 1-(2-pyridylazo) 2-naphtol (PAN). The main experimental factors affecting the complexation and the extraction of metals (pH, PAN concentration, salt addition and extractant solvent and disperser solvent volume) were optimized using a multivariate analysis consisting of two steps: a Plackett-Burman design followed by a Circumscribed Central Composite Design (CCCD). Under optimum microextraction conditions, the analytical features of the proposed methodologies were assessed. Accuracy was evaluated by analyzing two certified reference materials, yielding results in agreement with the certified values. Both methodologies were applied to the analysis of a number of beverage samples.

Optimization of Countercurrent Supercritical Fluid Extraction of Minor Components from Olive Oil

A process based on the use of a semi-continuous countercurrent supercritical fluid extraction (CC-SFE) has been optimized to concentrate minor components, with functional properties, from olive oil. The optimization of the main variables involved in the supercritical extraction process (extraction pressure, temperature and sample flow rate) was performed using a surface response methodology (RSM). A central composite circumscribed design (CCCD) was employed to study the responses selected to describe the process, such as the extraction yield, the concentration of the different minor compounds (squalene, sterols and tocopherols) in the CO2-rich upper current stream, and the recovery of these compounds from the olive oil. Parameters of the model, for each response variable, were simultaneously estimated by Partial Least Squares (PLS) regression. The statistical analysis of the results allowed obtaining mathematical models able to predict the behavior of the different responses selected as a function of the main variables involved in the process. The optimum conditions obtained, that maximized all the responses as a whole, were: extraction pressure, 234 bar; extraction temperature, 35°C and sample flow rate, 82 mL/h, working with a solvent flow rate equal to 2000 mL/h (S/F equal to 28.4 kg CO2/kg oil). The optimum of the model was experimentally confirmed allowing around 90% recovery of squalene without significant changes on the nutritional and physicochemical properties of the oil.

Effect of Arabic gum, xanthan gum and orange oil on flavor release from diluted orange beverage emulsion

The influence of main emulsion components namely Arabic gum (13–20% w/w), xanthan gum (0.3–0.20% w/w) and orange oil (10–14% w/w) on semi-quantitative headspace analysis of target volatile flavor compounds released from a model orange beverage (diluted orange beverage emulsion) was evaluated by using a three-factor circumscribed central composite design (CCCD). For optimization procedure, the peak area of 13 volatile flavor compounds (i.e. ethyl acetate, α-pinene, ethyl butyrate, β-pinene, 3-carene, myrcene, limonene, γ-terpinene, octanal, decanal, linalool, neral and geranial) were considered as response variables. The response surface analysis exhibited that the significant ( p < 0.05) second-order polynomial regression equations were successfully fitted for all response variables except for ethyl butyrate. A satisfactory coefficient of determination ( R 2) ranged from 0.831 to 0.969 (>0.8) was obtained for the response variables studied. No significant ( p > 0.05) lack of fit was indicated for the reduced models except for the models fitted for limonene and linalool. This observation confirmed an accurate fitness of the reduced response surface models to the experimental data. The multiple response optimizations indicated that an orange beverage emulsion containing 15.87% (w/w) Arabic gum, 0.5% (w/w) xanthan gum and 10% (w/w) orange oil was predicted to provide the minimum overall flavor release.

Enrichment of vitamin E from Spirulina platensis microalga by SFE

A process based on supercritical fluid extraction (SFE) at pilot scale plant has been optimized to obtain fractions highly enriched in vitamin E from microalga Spirulina platensis. The optimization of the main variables involved in the process (extraction pressure and temperature and extraction solvent) has been performed using a surface response methodology. A central composite circumscribed design (CCCD) was employed to study the vitamin E enrichment (in mg/g extract). The parameters of the model were estimated by multiple linear regression (MLR) providing a mathematical model able to predict the concentration of vitamin E as a function of extraction pressure and temperature when neat CO 2 was used as extractant. The estimated model demonstrated that the extraction temperature, the quadratic term of temperature, the extracting pressure and the interaction pressure × temperature had a significant effect on the final concentration of vitamin E in the extracts. The optimal conditions for the extraction of vitamin E from Spirulina platensis were achieved working at maximum temperatures being the optimum value predicted 29.4 mg/g extract which implies a tocopherol enrichment of more than 12 times the initial concentration of tocopherol in the raw material.

Recrystallization of waxy maize starch during manufacturing of starch microspheres for drug delivery: Influence of excipients

The formation of ordered structure, such as crystallites, in starch was studied by means of differential scanning calorimetry (DSC). The influence of time/temperature treatment and additives such as polyethylene glycol (PEG), bovine serum albumin (BSA) and a carbonate buffer on the formation was investigated. The experiments were planned with a CCC (Central Composite Circumscribed) design. For all three investigated systems it could be concluded that the incubation time at 6 °C was the decisive factor for the amount of ordered structure obtained during the incubation, while the incubation time at 37 °C was the decisive factor for the thermal stability of the crystallites as expressed by T on, T m and T c. The additives seemed to mainly affect the nucleation phase of crystallization process. The additives decreased the time required in order to obtain a certain level of ordering in the incubated starch samples. The carbonate buffer decreased the amount of ordered structure in starch as judged by DSC enthalpy values, while increasing the melting temperature of these structures. The additives PEG and BSA lowered the melting temperatures of the starch in the systems but increased the enthalpy values. By optimization procedure a specific amount of ordered structure with desired thermal characteristics could be predicted.

A new approach for determination of enzyme kinetic constants using response surface methodology

A statistical approach called response surface methodology (RSM) is used for the prediction of the kinetic constants of glucose oxidase (GOx) as a function of reaction temperature and pH. Lineweaver–Burk transformation of the Michaelis–Menten equation was utilized as the integral part of the RSM algorithm. The effects of variables, namely reciprocal of substrate concentration (0.033–0.5 mM −1), reaction temperature (14.9–40.1 °C) and reaction pH (pH 4.4–8.5) on the reciprocal of initial reaction rate were evaluated and a second order polynomial model was fitted by a central composite circumscribed design (CCCD). It was observed that optimum reaction temperature and pH for the GOx reaction depended on the substrate concentration and varied between 27.8 °C and 6.4 pH and 32.7 °C and 6.1 pH in the investigated range of substrate concentration. The maximum reaction rate ( V max) and Michaelis–Menten constant ( K m) of GOx were obtained for each reaction parameter by using the model equation. The maximum reaction rate varied between 3.5 μmol/min mg enzyme and 29.8 μmol/min mg enzyme. Michaelis–Menten constant was determined between 1.9 mM and 16.8 mM in the tested reaction parameters. The kinetic constants of GOx were also determined with the conventional method at six reaction parameters and compared with the results of the proposed method. The correlation coefficients ( R 2) between the results of two methods were determined as 0.940 and 0.869 for V max and K m, respectively.

Kinetic constants determination for an alkaline protease from Bacillus mojavensis using response surface methodology.

The kinetic constants for an alkaline protease from Bacillus mojavensis were determined using a central composite circumscribed design (CCCD) where concentration of substrate (casein) and the assay temperature were varied around their center point. The K(m),V(max), K(cat), activation energy (E(a)) and temperature coefficient (q(10)) were determined and the values of these kinetic constants obtained were found comparable to that obtained with conventional methods. The Michaelis-Menten constant (K(m)) for casein decreased with corresponding increase in V(max), as reaction temperature was raised from 45-60 degrees C. The protease exhibited K(m) of 0.0357 mg/ml, 0.0270 mg/ml, 0.0259 mg/ml, and 0.0250 mg/ml at 45, 50, 55, and 60 degrees C, respectively, whereas V(max) values at these temperatures were 74.07, 99.01, 116.28, and 120.48 microg/ml/min, respectively, as determined by response surface methodology. The Arrhenius plot suggested that the enzyme undergoes thermal activation above 45 degrees C until 60-65 degrees C followed by thermal inactivation. Likewise, the energy of activation (E(a)) was more between 45-55 degrees C (9747 cal/mol) compared to E(a) between 50-60 degrees C (4162 cal/mol).