Optimization of medium composition for the production of elastase by Bacillus sp. EL31410 with response surface methodology

Chen, Q.H.; He, Guoqing; Ali, Mokhtar A.M.

doi:10.1016/s0141-0229(02)00028-5

Cited by 71 publications

(44 citation statements)

References 15 publications

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“…Then central composite design (CCD) was utilized to optimize the most important factors for the maximum AD yield and PS conversion rate. A 2 5−1 FFD which included 16 sets of trials with four replicates at center point was carried out in duplicate to screen the critical parameters influencing AD yield and PS conversion rate (Chen et al, 2002). The coded values of variables were determined by the following equation:…”

Section: Experimental Designmentioning

confidence: 99%

Optimization of biotransformation from phytosterol to androstenedione by a mutant Mycobacterium neoaurum ZJUVN-08

Zhang

Peng

et al. 2013

J. Zhejiang Univ. Sci. B

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Biotransformation of phytosterol (PS) by a newly isolated mutant Mycobacterium neoaurum ZJUVN-08 to produce androstenedione has been investigated in this paper. The parameters of the biotransformation process were optimized using fractional factorial design and response surface methodology. Androstenedione was the sole product in the fermentation broth catalyzed by the mutant M. neoaurum ZJUVN-08 strain. Results showed that molar ratio of hydroxypropyl-β-cyclodextrin (HP-β-CD) to PS and substrate concentrations were the two most significant factors affecting androstenedione production. By analyzing the statistical model of three-dimensional surface plot, the optimal process conditions were observed at 0.1 g/L inducer, pH 7.0, molar ratio of HP-β-CD to PS 1.92:1, 8.98 g/L PS, and at 120 h of incubation time. Under these conditions, the maximum androstenedione yield was 5.96 g/L and nearly the same with the non-optimized (5.99 g/L), while the maximum PS conversion rate was 94.69% which increased by 10.66% compared with the non-optimized (84.03%). The predicted optimum conditions from the mathematical model were in agreement with the verification experimental results. It is considered that response surface methodology was a powerful and efficient method to optimize the parameters of PS biotransformation process.

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Section: Experimental Designmentioning

confidence: 99%

Optimization of biotransformation from phytosterol to androstenedione by a mutant Mycobacterium neoaurum ZJUVN-08

Zhang

Peng

et al. 2013

J. Zhejiang Univ. Sci. B

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“…To optimize the hydrolysis reaction, a three-step design was used that included fractional factorial design (FFD), steepest ascent design, and central composite design (CCD). FFD was used for screening the most important factor of the hydrolysis reaction, steepest ascent design was used to determine the direction toward predicted higher responses, and CCD was used to optimize the important factor and maximize the ACE inhibitory activity (Chen et al, 2002). In the FFD, a set of 12 experiments was carried out.…”

Section: Experimental Design and Statistical Analysismentioning

confidence: 99%

Optimization of angiotensin I-converting enzyme (ACE) inhibition by rice dregs hydrolysates using response surface methodology

Xuan

Ruan

et al. 2005

J Zheijang Univ Sci B

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Angiotensin I-converting enzyme (ACE) inhibitory peptides have been shown to have antihypertensive effects and have been utilized for physiologically functional foods and pharmaceuticals. The ACE inhibitory ability of a hydrolysate is determined by its peptide composition. However, the peptide composition of a hydrolysate depends on proteolytic enzyme and the hydrolysis conditions. In this study, the effect of process conditions on the ACE inhibitory activity of rice dregs hydrolyzed with a trypsin was investigated systematically using response surface methodology. It was shown that the ACE inhibitory activity of rice dregs hydrolysates could be controlled by regulation of five process conditions. Hydrolysis conditions for optimal ACE inhibition were defined using the response surface model of fractional factorial design (FFD), steepest ascent design, and central composite design (CCD).

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“…Several statistical models are used in RSM to evaluate the effect of independent variables on the desired variable response [10]. The RSM has been applied as an experimental strategy for seeking the optimum conditions in a multivariable system [11]. The randomized experiments have to be performed in order to minimize the effects of unexplained variability in the actual responses due to extraneous factors [12].…”

Section: Introductionmentioning

confidence: 99%

Statistical Optimization of Production Conditions of Alkaline Pectin Lyase from Bacillus cereus using Response Surface Methodology

Reena¹,

Pooja²,

Nitish³

2016

J Food Ind Microbiol

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Pectin lyase finds applications in the degumming and retting of plant fibers where it degrades highly methylesterified pectin without prior action of any other pectinase. Response surface methodology (RSM) has been frequently utilized for the optimization of production process of industrially important enzymes from microbes. In the present work, fermentation conditions for the production of pectin lyase from Bacillus cereus were optimized using the factorial and central composite design of RSM. The cubic order polynomial regression model was found to be adequate and significant with a determination coefficient R 2 of 0.9505 (p<0.0001). The ANOVA analysis and three dimensional surface plots confirmed interaction among variables. The optimum values of variables were found to be pectin 4% (w/v), sodium carbonate 1% (w/v), manganese sulfate 0.055% (w/v) and magnesium sulfate 0.018% (w/v) at 150 rpm under response surface curves. After optimization, the experimental value of maximum activity of enzyme (3.37 U/ml) was found higher but close to the predicted value (2.68 U/ml) and the enzyme activity increased by 1.32 fold (32.16%).

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Optimization of medium composition for the production of elastase by Bacillus sp. EL31410 with response surface methodology

Cited by 71 publications

References 15 publications

Optimization of biotransformation from phytosterol to androstenedione by a mutant Mycobacterium neoaurum ZJUVN-08

Optimization of biotransformation from phytosterol to androstenedione by a mutant Mycobacterium neoaurum ZJUVN-08

Optimization of angiotensin I-converting enzyme (ACE) inhibition by rice dregs hydrolysates using response surface methodology

Statistical Optimization of Production Conditions of Alkaline Pectin Lyase from Bacillus cereus using Response Surface Methodology

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