464
M. Paul et al.
− 10.04 ∗ B D − 128.96 ∗ C D − 46.05 ∗ A
2
− 3.76 ∗ B
2
+ 114.62 ∗ C
2
− 35.94 ∗ D
2
3.2.3 Statistical Analysis
It is evident from the obtained statistical analysis that the cellulase activity model
of SCB9 strain was highly significant, as suggested by the model F-value and low
probability value. The model F-value of 230.17 as calculated from this system implies
that the model is significant. There is only a 0.01% chance that an F-value larger than
this could occur due to noise. The lack of fit F-value of 0.3782 implies that the lack
of fit is not significant relative to the pure error. There is an 88.03% chance that a lack
of fit F-value larger than this could occur due to noise. This nonsignificant lack of fit
as represented from the ANOVA table evidences the optimization of model system.
The coefficient of determination (R
2 ) was calculated as 0.9963 for enhanced cellulase
activity, indicating that the statistical model can explain adequate variability in the
response. Similarly, Doddapaneni et al. (2007) suggested that closer the value of R
2
to 1.0, stronger the model and better it predicts the response of tested enzyme activity
according to the designed experimental conditions. The predicted R
2 value of 0.9831
was in reasonable agreement with the adjusted R
2 value of 0.9920. This indicated a
good agreement between the experimental and predicted values for cellulase activity.
If there are many terms in the model and the sample size is not very large, the adjusted
R
2 value may be noticeably smaller than the R
2 . In the present study, in concur with
the above statement, adjusted R
2 0.9920 is also less than the R
2 value 0.9963.
Saravanan et al. (2012) studied the optimization of cellulase production using
Tricoderma reesei by RSM and comparison with genetic algorithm. The potential of
Trichoderma reesei for cellulase production using pineapple waste as substrate has
been investigated. A maximum cellulase activity of 569.23 U/mL is obtained under
the optimum experimental conditions; pH 5.5, temperature 37 °C, initial substrate
concentration 3%, inoculum concentration, and culture time. Box–Behnken design
(BBD) statistical tool and genetic algorithm are used to optimize the process parameters. The BBD study of linear and quadratic interactive effects of experimental
variables on the desired response of cellulase activity showed that the second-order
polynomial is significant. Therefore, it can be depicted from the optimization of
cellulase activity that both the current study and the study undertaken by Saravanan
et al. (2012) that BBD is a suitable technique and it properly determines as well as
validate the optimum condition for maximum enzyme activity.
M. Paul et al.
− 10.04 ∗ B D − 128.96 ∗ C D − 46.05 ∗ A
2
− 3.76 ∗ B
2
+ 114.62 ∗ C
2
− 35.94 ∗ D
2
3.2.3 Statistical Analysis
It is evident from the obtained statistical analysis that the cellulase activity model
of SCB9 strain was highly significant, as suggested by the model F-value and low
probability value. The model F-value of 230.17 as calculated from this system implies
that the model is significant. There is only a 0.01% chance that an F-value larger than
this could occur due to noise. The lack of fit F-value of 0.3782 implies that the lack
of fit is not significant relative to the pure error. There is an 88.03% chance that a lack
of fit F-value larger than this could occur due to noise. This nonsignificant lack of fit
as represented from the ANOVA table evidences the optimization of model system.
The coefficient of determination (R
2 ) was calculated as 0.9963 for enhanced cellulase
activity, indicating that the statistical model can explain adequate variability in the
response. Similarly, Doddapaneni et al. (2007) suggested that closer the value of R
2
to 1.0, stronger the model and better it predicts the response of tested enzyme activity
according to the designed experimental conditions. The predicted R
2 value of 0.9831
was in reasonable agreement with the adjusted R
2 value of 0.9920. This indicated a
good agreement between the experimental and predicted values for cellulase activity.
If there are many terms in the model and the sample size is not very large, the adjusted
R
2 value may be noticeably smaller than the R
2 . In the present study, in concur with
the above statement, adjusted R
2 0.9920 is also less than the R
2 value 0.9963.
Saravanan et al. (2012) studied the optimization of cellulase production using
Tricoderma reesei by RSM and comparison with genetic algorithm. The potential of
Trichoderma reesei for cellulase production using pineapple waste as substrate has
been investigated. A maximum cellulase activity of 569.23 U/mL is obtained under
the optimum experimental conditions; pH 5.5, temperature 37 °C, initial substrate
concentration 3%, inoculum concentration, and culture time. Box–Behnken design
(BBD) statistical tool and genetic algorithm are used to optimize the process parameters. The BBD study of linear and quadratic interactive effects of experimental
variables on the desired response of cellulase activity showed that the second-order
polynomial is significant. Therefore, it can be depicted from the optimization of
cellulase activity that both the current study and the study undertaken by Saravanan
et al. (2012) that BBD is a suitable technique and it properly determines as well as
validate the optimum condition for maximum enzyme activity.