2009
DOI: 10.1016/j.micres.2006.10.006
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Optimization of laccase production from a novel strain—Streptomyces psammoticus using response surface methodology

Abstract: Response surface methodology was employed for the optimization of different nutritional and physical parameters for the production of laccase by the filamentous bacteria Streptomyces psammoticus MTCC 7334 in submerged fermentation. Initial screening of production parameters was performed using a Plackett - Burman design and the variables with statistically significant effects on laccase production were identified. Incubation temperature, incubation period, agitation rate, concentrations of yeast extract, MgSO(… Show more

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Cited by 100 publications
(50 citation statements)
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“…The significance of each coefficient in the experimental model was also determined by T value and P value. A high T test value and a low P value indicate a high significance [75,76]. Student's t test of each coefficient of the model showed that the linear coefficient (X 2 ), the quadratic term (X 1 2 , X 2 2 , X 3 2 ) and the cross product (X 1 X 2 ) have significant effects (P > |T| < 0.05) on T. peruviana biodiesel (Y).…”
Section: Gas Chromatographic Analysis Of T Peruviana Seed Oilmentioning
confidence: 99%
“…The significance of each coefficient in the experimental model was also determined by T value and P value. A high T test value and a low P value indicate a high significance [75,76]. Student's t test of each coefficient of the model showed that the linear coefficient (X 2 ), the quadratic term (X 1 2 , X 2 2 , X 3 2 ) and the cross product (X 1 X 2 ) have significant effects (P > |T| < 0.05) on T. peruviana biodiesel (Y).…”
Section: Gas Chromatographic Analysis Of T Peruviana Seed Oilmentioning
confidence: 99%
“…They achieved a laccase yield of 55.4 U/g using an RSM approach. In our study, the maximum laccase yield of 607.2 U/mL was much higher than that obtained in other recent studies (Niladevi et al, 2009;Li et al, 2013). The rate of wheat straw degradation obtained in this study was also higher than that reported elsewhere.…”
Section: Optimization Of Fermentation Conditions (Rsm Ii)contrasting
confidence: 73%
“…The R-squared of 0.8875 revealed that the model could explain 88.75% of the variability in the response (Table 2). For a good statistical model, the R 2 should be in the range of 0.75-1.0 which indicates a good fit of the model [19]. The relatively high value of R 2 indicated that the quadratic equation could be used instead of an experimental system under the given conditions.…”
Section: Statistical Analysis and The Diagnostic Checking Of The Fittmentioning
confidence: 99%