Microbial Degradation of Basic Dyes in Wastewaters - Microbial Degradation of Synthetic Dyes in Wastewaters - page 92

decreased rate of enzyme synthesis. On the contrary; it was observed in a study that
under both stationary and shaking culture conditions, Phanerochaete chrysospo-
rium effected equal and ef

cient degradation of Malachite green. However, the
degradation of Crystal violet by the same culture was cient

under shaking conditions as compared to the stationary culture (Sani et al. 1998 ).
Therefore, various types of bioreactors with static and agitated con

ve times more ef

gurations were

developed to provide suf cient oxygen. The choice of the reactor depends on the

particular requirement, although lower agitation rate ranging between 100 and
150 rpm is found bene

cial in achieving better decolorization results with fungi as
compared to static conditions (Fu and Viraraghavan 2001 ; Parshetti et al. 2007 ).

3.8 Initial Dye Concentration

Dyes at higher concentrations are usually toxic to microorganisms, but toxicity also
depends on the nature of dye. In general, most of the research studies have indicated
a range of initial dye concentration between 50 1,000 mg l − 1 . Hence, it is important

to optimize the initial dye concentration for color removal, which depends on both
the microbial strain and the type of dye used.

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3.9 Statistical Design-Based Optimization

Many dye decolorization studies, as reported in the literature, practiced the classical
optimization method which involved the alteration of ”

(OFAT), while keeping all other factors at a predetermined level. In this approach, a
series of experiments are carried out using a large number of variables which need
to be tested to determine the optimum level. This process is very time-consuming,
labour-intensive, open-ended, expensive and the interaction between the variables is
ignored (Haaland 1989 ). On the other hand, for improving the decolorization
ef

“ one factor at a time

ciency, an experimental design approach may be followed which requires both a
design and an optimization method. The design speci es the variables to test within

the experiment, including the number of replicates and the arrangement of tests into
homogenous

. Further, a mathematical model is employed to predict the
optimized conditions of the process, based on which minimum experiments are
conducted to validate the predicted optimized conditions. The statistical approaches
are preferred in process optimization, because it is economical, considers interac-
tions between medium components and allows rapid optimization of the process
(Mason et al. 1989 ). An arti

' blocks '

cial neural network model was developed to predict
the biosorptive decolorization of Basic green 4 solution by microalga Chlamydo-
monas sp. With the optimum conditions of initial pH 9, 45 ° C, dye concentration of

10 mg l − 1

ciency was
observed (Khataee et al. 2009 ). In one study, a central composite design, based on

and reaction time of 180 min, 80 % decolorization ef