Application of Plackett‐Burman design and response surface methodology to achieve exponential growth for aggregated shipworm bacterium

Ahuja, Sanjeev; Ferreira, Gisela; Moreira, A.

doi:10.1002/bit.10880

Cited by 93 publications

(50 citation statements)

References 32 publications

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“…After 12 h of cultivation, the inoculants were ready to use. T. turnirae suspension was stored at -80°C in Eppendorf tubes [14]. The tubes were allowed to melt down at ambient temperature and then used as inoculants in an appropriate level.…”

Section: Inoculum Preparationmentioning

confidence: 99%

Cocultivation of Lactococcus lactis and Teredinobacter turnirae for biological chitin extraction from prawn waste

Aytekin

Elibol

2009

Bioprocess Biosyst Eng

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In this study, mainly biological treatment of prawn waste for chitin production was investigated. Lactic acid and protease fermentations were applied to extract chitin from prawn waste in the presence of various glucose concentrations. The results obtained were also compared with those of chemical method which was consisted of first mineral removal and then protein removal sequence. Different strategies were applied using lactic acid producing bacterium, Lactococcus lactis, and a protease producer, marine bacterium Teredinobacter turnirae. Both bacteria were first cultivated individually and then cofermented. In their individual cultivation, L. lactis removed the inorganic materials efficiently, while T. turnirae performed better in deproteinization process. Cofermentation of both bacteria was also conducted using three different protocols. The highest process yield (95.5%) was obtained when T. turnirae was first inoculated. Although the extraction of chitin by biological treatment was incomplete compared to the chemical method, the biological treatment employed here could still be considered as an alternative method in a more environmentally benign approach.

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Section: Inoculum Preparationmentioning

confidence: 99%

Cocultivation of Lactococcus lactis and Teredinobacter turnirae for biological chitin extraction from prawn waste

Aytekin

Elibol

2009

Bioprocess Biosyst Eng

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“…Table III shows the Plackett-Burman design and analysis. The SD, which was calculated using dummy variables, was not equal to 0 (Table III), suggesting the existence of interactions amongst factors in the fermentation (Ahuja et al, 2004). P-values less than 0.05 indicate factors which are significant at the probability level of 95%.…”

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confidence: 99%

Medium factor optimization and fermentation kinetics for phenazine‐1‐carboxylic acid production by Pseudomonas sp. M18G

Zhang

2007

Biotech & Bioengineering

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We investigated the production of biofungicide phenazine-1-carboxlic (PCA) by Pseudomonas sp. M18G, a gacA-deficient mutant of M18 for PCA high-production. Glucose was chosen as the optimal carbon source and soy peptone as the nitrogen source. A Plackett-Burman design revealed that glucose, soy peptone and NaCl were the most significant factors in PCA fermentation. Response surface methodology (RSM) and artificial neural network (ANN) models involving the significant factors were developed using common data. The prediction accuracy of ANN was slightly higher compared to RSM. The genetic algorithm (GA) was used to search the optimal input space of the trained ANN model and find the corresponding PCA yield. The optimum composition was found to be: glucose 34.3 g L(-1), soy peptone 43.2 g L(-1), NaCl 5.7 g L(-1), and the predictive maximum PCA yield reached 980.1 microg mL(-1). The optimized medium allowed PCA yield to be increased from 673.3 to 966.7 microg mL(-1) after verification experiment tests. Additionally, PCA fermentation kinetics was investigated. Kinetic models based on the modified Logistic and Luedeking-Piret equations were developed, providing a good description of temporal variations of biomass (X), product (P), and substrate (S) in PCA fermentation.

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“…Statistical methods have been applied for optimization of microbial enzyme production in various studies [34][35][36][37]. The use of a good reliable statistical model is essential to develop better strategies for the optimization of the fermentation process [38].…”

Section: Discussionmentioning

confidence: 99%

Optimization of Process Parameters by Statistical Experimental Designs for the Production of Naringinase Enzyme by Marine Fungi

Shehata

Aty

2014

International Journal of Chemical Engineering

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Naringinase has attracted a great deal of attention in recent years due to its hydrolytic activities which include the production of rhamnose and prunin and debittering of citrus fruit juices. Screening of fifteen marine-derived fungi, locally isolated from Ismalia, Egypt, for naringinase enzyme production, indicated that Aspergillus niger was the most promising. In solid state fermentation (SSF) of the agroindustrial waste, orange rind was used as a substrate containing naringin. Sequential optimization strategy, based on statistical experimental designs, was employed to enhance the production of the debittering naringinase enzyme. Effects of 19 variables were examined for their significance on naringinase production using Plackett-Burman factorial design. Significant parameters were further investigated using Taguchi's (L16 4 5 ) orthogonal array design. Based on statistical analysis (ANOVA), the optimal combinations of the major constituents of media for maximal naringinase production were evaluated as follows: 15 g orange rind waste, 30 mL moisture content, 1% grape fruit, 1% NaNO 3 , 0.5% KH 2 PO 4 , 5 mM MgSO 4 , 5 mM FeSO 4 , and the initial pH 7.5. The activity obtained was more than 3.14-fold the basal production medium.

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Application of Plackett‐Burman design and response surface methodology to achieve exponential growth for aggregated shipworm bacterium

Cited by 93 publications

References 32 publications

Cocultivation of Lactococcus lactis and Teredinobacter turnirae for biological chitin extraction from prawn waste

Cocultivation of Lactococcus lactis and Teredinobacter turnirae for biological chitin extraction from prawn waste

Medium factor optimization and fermentation kinetics for phenazine‐1‐carboxylic acid production by Pseudomonas sp. M18G

Optimization of Process Parameters by Statistical Experimental Designs for the Production of Naringinase Enzyme by Marine Fungi

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