By the response surface methodology, best conditions of enzymatic

By the response surface methodology, best conditions of enzymatic active were determined for intervals of utilised experimental conditions. All statistical analysis was conducted using Statistical Analysis System® 9.0 version, RSREG procedure (SAS Institute Inc., Cary, NC, USA). According to Granato et al. (2010), to validate the adjusted model, the optimised values of the independent variables (X1 and X2) should be used in the same initial experimental procedure, in order to verify the prediction power of the developed models by comparing theoretical predicted data to the experimental ones. In this work, triplicate of biotransformation

using the optimised variables were prepared and analysed. In order to evaluate which factors had Volasertib cell line significant effect on the enzymatic active of CMCase, FPase, and xylanase, an ANOVA (Table 2) and parameters estimative analysis were conducted for the 23−1 fractional factorial. The analysis of variance (ANOVA) for the models was performed and the model significance was examined using Fisher’s statistical test (F-test) applied to significant differences between sources of variation in experimental results, i.e., the significance of the regression (SOR), the lack of fit (LOF), and the coefficient of multiple determination (R2). Since the full second-order models

(models containing both find more parameter interactions) were not accepted by the mentioned tests, they were improved by the elimination of the model terms until the determined conditions were fulfilled. All factors that were not significant at 10% were then pooled into the error term and a new reduced model was obtained for response variables by regression analysis using only the significant

factor previously listed. The outcome of the ANOVA can be visualised in a Pareto chart (Fig. Teicoplanin 1), in which the absolute value of the magnitude of the standardised estimated effect (the estimate effect divided by the standard error) of each factor is plotted in decreasing order and compared to the minimum magnitude of a statistically significant factor with 90% of confidence (p = 0.10), represented by the vertical dashed line. From this figure it can be observed that all variables were significant in the enzymatic active for CMCase and xylanase. On the other hand, the Pareto chart regarding the FPase active shows that time and temperature have a significant effect for this response variable. For all cases, the interactions with the variables time, temperature, and water content were not significant to the enzymatic activity. The reduced models can be described by Eqs. (2), (3) and (4), in terms of uncoded values. equation(2) AC1=25.61154+3.41369X1+1.50245X2-1.11489X3-7.45472X12-5.06567X22-5.19840X32 equation(3) AC2=16.

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