Mycoremediation of Synthetic Dyes: An Insight into the Mechanism, Process Optimization and Reactor Design - Microbial Degradation of Synthetic Dyes in Wastewaters - page 14

experiment. Percentage dye removal, residual dye concentration and biomass
generated can be regarded as the response of a dye removal process. To obtain the
best response value of dye removal process, the independent variables need to be
optimized (Kaushik and Malik 2009 ). The optimization study using RSM can be
divided into three stages. In the

rst stage, the independent variables and their levels
are determined. Screening experiments are performed to determine the important
parameters that in uence the process of dye removal. Further, depending upon the

direction in which these parameters affect the process, their levels (ranging from -1
to +1) are determined. In the second stage, the experimental design is selected and
the model equation is predicted and veri

ed. Generally a full quadratic equation

(second order) is used in RSM.

X X XX

k
j ¼ 1 b j X j þ

k
j ¼ 1 b jj X j þ

y ¼ b 0 þ

j b ij X i X j i

\

In the third stage, responses of surface plot and contour plot are obtained and
their optimum points are determined (Bas and Boyaci 2007 ). Many researchers
have employed RSM to optimize the dye removal process by fungi in growing
mode in terms of initial dye concentration (Alam et al. 2009 ;G nen and Aksu

2009a ; Sharma et al. 2009 ; Srinivasan and Murthy 2009 ; Das et al. 2010 ), pH
(Sharma et al. 2009 ; Qu et al. 2010 ), temperature (Sharma et al. 2009 ; Qu et al.
2010 ) and nutritional conditions (G

ö

nen and Aksu 2009b ; Kaushik and Malik
2011 ; Aghaie-Khouzani et al. 2012 ; Papadopoulou et al. 2013 ). However, certain
factors must be considered while selecting RSM for biological processes. For
example, it is not necessary that all the systems, that show curved graph,

ö

tto
second order polynomial and thus require to be converted to other forms, such as
the log values or by changing the range of parameters (Bas and Boyaci 2007 ). This
limits its use in those biological processes which cannot be described by a second
order polynomial equation.

4.2 Taguchi Method

Taguchi method was initially developed as a tool for improving the quality
inengineering methodology and obtaining a robust design (Wang et al. 2002 ).
However, it has been also employed to optimize the condition ofdye removal
process (Engin et al. 2008 ; Yildiz 2008 ). Daneshvar et al. ( 2007 ) applied Taguchi
method in optimizing the process of biological degradation of Malachite Green with
respect to temperature, initial pH, type of algae, dye concentration and time of
reaction. Revankar and Lele ( 2007 ) optimized the fermentation medium for
Ganoderma sp. to obtain the maximum removal of amaranth dye using Taguchi
methodology.