"Genius is one per cent inspiration, ninety-nine per cent perspiration"

Thomas Edison

7 ADSORPTION OF COLORED POLLUTANTS FROM

DISTILLERY SPENT WASH BY NATIVE AND

TREATED FUNGUS: NEUROSPORA INTERMEDIA

7. Adsorption of colored pollutants from distiUery spent wash by native

and treated fungus: Neurospora intermedia

7 .1. Introduction

Distillery effluent, a foul smelling, dark colored by-product of distillery industries

is perceived as one of the serious pollution source of the countries producing alcohol

from fermentation and subsequent distillation of sugar cane molasses. It contains

extremely high COD, BOD, soluble solids, inorganic solids, color and low in pH (Saha et

al., 2005) besides other caramelized and recalcitrant wastes. The characteristic

recalcitrance to decolourization of distillery effluent is due to the presence of brown

melanoidin polymers that are formed in Maillard reactions between amino acids and

carbohydrates (Wedzicha and Kaputo, 1992). These Maillard compounds have

antioxidant properties that render them toxic to aquatic micro and macroorganisms (Kitts

et al., 1993). Various physico-chemical methods/ treatment technologies such as

incineration, composting and biological treatments have been studied for distillery waste

wasters by various researchers (Sheehan and Greenfield, 1980; Hayase et al., 1984;

Gupta et al., 1990; Pena et al., 1996; Nandy et al., 2002).

Biological treatment is practiced in most of the Indian distilleries resulting in

reduction of BOD and COD. The biological treatment system includes anaerobic

treatment with recovery of biogas, followed by aerobic treatment for removal of residual

BOD and COD. However, the success rate of most of the biological methods increases if

applied after physicochemical treatments. The major problem encountered with distillery

effluent treatment is the color which remain present even after biological treatment due to

the presence of recalcitrant compounds viz. caramel, melanoidins, variety of sugar

decomposition products, anthocyanins and tannins, and other xenobiotic compounds. It is

difficult to remove ·these constituents from the disti1lery effluent through conventional

biological processes.

Several workers have attempted to remove these recalcitrant compounds by

physico-chemical methods using diluted distillery wastewater and biologically treated

130

distillery effluent. Among the physico-chemical treatment methods, adsorption on

activated carbon (AC) is widely used for removal of color and specific organic pollutants

(Bernardo et al., 1997).

Activated carbon is a well-known adsorbent due to its extended surface area,

microporus structure, high adsorption capacity and high degree of surface reactivity.

Previous studies on decolourization of distillery spent wash include adsorption on

commercial as well as indigenously prepared activated carbons (Satyawali and

Balakrishanan, 2007) but the relatively high cost restricts its usage. Low cost adsorbents

such as pyorchar (activated carbon both in granular and powdered form, manufactured

from paper mill sludge) and bagasse flyash have also been studied for this application.

Since the bagasse flyash has high carbon content and the adsorbed organic material

further increases its heating value, it is not considered as good alternative. Yet another

adsorbent that has been evaluated is the natural carbohydrate polymer chitosan derived

from the exoskeleton of crustaceans. Lalov et al. (2000) studied the treatment of distillery

wastewater using chitosan as an anion exchanger.

Biomass of some natural microbial species, including bacteria, fungi and algae, is

capable of removing the different textile dyes by biosorption, biodegradation or

mineralization (Carliell et al., 1995). Ever increasing demand for new sources of low-cost

adsorbent undoubtedly make chitosan-containing biomass as one of the most attractive

'materials for colored wastewater treatment (Babel and Kurniawan, 2003). Various

researchers have carried the biosorption studies of various organic pollutants and color

from wastewaters (Tsezos and Bell, 1989; Fu and Viraraghavan, 2001). Partial

elimination of Maillard colored compounds was obtained by using microbes like

Geotrichum candidum (Borja et al., 1993). Rhizoctonia sp. D-90 (Sirianutapiboon et al.,

1995). Electron microscopy revealed the presence of melanoidin like pigment, in the

form of electron dense material in the cytoplasm that was adsorbed by the mycelia. Color

removal from molasses spent wash through adsorption was also studied by Miranda et al.

(1996) using Aspergillus niger

In this study, the native, heat-, acid- and alkali-treated biomasses of Neurospora

intennedia were used for the adsorption of colored components of distillery effluent in

batch cultures. The effects of experimental conditions such as effluent concentration,

131

temperature and pH were also investigated to obtain information on adsorption properties

of the fungal biomass. The possible mechanisms involved in the adsorption are discussed

on the basis of the treatment of the fungal biomass followed by Electron Microscopic and

.FTIR spectroscopic studies. Finally, equilibrium biosorption capacities were also studies

by using adsorption isotherm techniques. The experimental data was fitted into the

Langmuir, Freundlich equations.

7 .2. Material and methods

7 .2.1. Sorbate

For studying the process of adsorption by fungal biomass, the effluent, collected

from Modi distilleries, Modinagar, Uttar Pradesh, India, was diluted to desired dilution

·using MSM (minimum salt media) for adsorption studies. The pH of the sample was

adjusted using O.lM HCl or O.lM NaOH as required.

7 .2.2. Cultivation of fungus

The fungus "Neurospora intennedia (MTCC-9655)" was selected for adsorption

studies. It was observed in chapter 3 that this fungus played significant role in

decolorizing the distillery spent wash through adsorption rather than using its enzymatic

system. Thus, it was assumed that the process of adsorption was dominantly taking place.

The strain was maintained on PDA plates, stored at 4°C with routine transfers in a cycle

of 2 months (Kapoor et al., 1999). It was cultivated in liquid medium in PDB using the

shake flask method. Once inoculated, flasks were incubated on an orbital shaker at 125

rpm for 7 days at 30°C. After incubation, the biomass was harvested from the medium

and washed with distilled water. The washed biomass (live biomass) was used

immediately thereafter.

7 .2.3. Physical and chemical treatment of fungal biomass

Untreated fungus was called native fungus. Native fungus was soaked in 0.1M

HCJ at room temperature, in the ratio 1:10 w/v for 1 hour at 125 rpm. The biomass was

then washed with buffer saline. This fungus was called acid treated fungus. Similarly,

base treated fungus was prepared by treating it with O.lM NaOH. For preparation of heat­

treated fungus, biomass was heated in water bath at 1 00°C in buffer saline for 10 min

(Bayramoglu et al., 2006).

132

7 .2.4. Adsorption studies

Batch adsorption studies were conducted by varying adsorbent (biomass),

adsorbate concentration (distillery spent wash), pH and temperature, to obtain rate and

equilibrium data. In each experiment, accurately weighed 10% fungal biomass (wet

weight) was added to 100 ml of distillery spent wash solution (MSM- effluent, 65oo·cu)

taken in a 250 ml conical flask along with necessary carbon (dextrose, 0.05%), nitrogen

(NaN03, 0.025%), for the fungus (chapter 3). The mixture was agitated at 125rpm in an

incubated shaker at constant temperature (30°C).

At the end of the equilibrium period, the contents of the flasks were analyzed for

residual concentration of adsorbate. The adsorption of the colored contaminants of

distillery spent wash on the native and heat-acid- and base-treated fungal biomass was

also investigated. The distillery spent wash having 65000 CU was served as stock

solution. Different concentrations were prepared from this stock solution. To determine

the effect of initial concentrations of the effluent on the adsorption rate and capacity on

the fungal preparations, the initial concentration of the effluent was varied between 1 000

CU to 6500CU in the bisorption medium. The effects of the medium pH on the

adsorption capacities of the fungal biomass preparations were later investigated in the

initial pH range 2.0-8.0 (which was adjusted with HCl or NaOH at the beginning of the

experiment) at 30°C. The effect of temperature was studied at varied temperature ranges

20- 40°C at pH 3.0.

7 .2.5. Analysis

Before analysis of the remaining color concentration in the adsorbate, the sample

was centrifuged at 5000 rpm for 20 min. The supernatant was analyzed for estimation of

color by cobalt-platinate method (Chapter 3). Coloring unit of the effluent was

considered a measure of amount o:( chemicals present in the effluent. Such approach has

been followed in other studies also where COD as a measure of effluent concentration

was used (Srivastava et al., 2005, Devi et aL, 2008). The readings were taken in duplicate

for each individual solution to check repeatability and the average of the values were

taken.

133

Percentage color removal was calculated using the formula

%Color removal =(Co- C1 )/C0 x 100

C0=lnitial color of spent wash

C1 =Final color of spent wash at time t

The amount of biosorbed coloring material per unit fungal biomass (g wet biomass) was

obtained by using the following expression:

qe =(Co- Ce) ·VIM

qe is the amount adsorbed at equilibrium, Co is the initial concentration of the sorbate, Ce

is the equilibrium solution concentration, V the volume, and M the mass of adsorbent.

7 .2.6. Characterization of the fungal biomass

Changes in fungal biomass was studied before and after adsorption by SEM and

FT-IR. The changes in the fungal mycelium due to physico-chemical treatments (acid,

base and heat) were also studied by Ff-IR.

Scanning Electron Microscopy

The fungal mycelium before and after adsorption was analyzed by fixing and

soaking it overnight in O.lM phosphate buffer saline having 1% glutaraldehyde and 2%

paraformaldehyde at 4°C. Fixed mycelium was smeared over the coverslip coated with

poly-L-lysin for 30 min in wet condition. The specimen was washed with buffer,

dehydrated in a series of ethanol-water solution (30, 50, 70, and 90% ethanol, 5 min

each) and critical point dried under a C02 atmosphere for 20 min. Mounting was done on

aluminium studs provided with adhesive disk, a line of silver paint was applied on two

sides of each sample. A thin layer of gold was coated using Bio-rad Polaron Gold/Silver

Sputter coating unit for 30 min. Coated cells were viewed at 10 kV with scanning

electron microscopy (ZEISS Scanning Electron Microscope EVO 50). Working distance

was 10mm and SEl detector was used. Rate of scanning and magnification varied with

the sample (Srivastava and Thakur, 2006; Srivastava and Thakur, 2007).

Fourier Transform Infrared Spectroscopy (FT-IR)

The IR spectra of native, acid-, base- and heat-treated N. intennedia were

obtained by using a Ff-IR spectrophotometer. For FTIR spectra, fungal biomass (0.01 g

dry weight) was mixed with KBr (0.1 g) and pressed into a tablet form by pressing the

134

ground niixed material with the aid of a bench press. Scan was recorded from 450nm to

4000nm with Perkin-Elmer 1600 series Ff-IR spectrophotometer (Nujol, KBr disks).

7 .2. 7. Equilibrium models

To optimize the design of a sorption system to remove the sorbates, it is important

to establish the most appropriate correlation for the equilibrium curves. These

equilibrium sorption capacity curves can be obtained by measuring the sorption isotherm.

The experimental data of the amount of sorbate adsorbed on the sorbent are substituted

into an equilibrium isotherm model to determine the best-fit model for the sorption

system. Using this relationship, any variation in the concentration of sorbent with the

concentration of sorbate in solution is correlated. The Freundlich and Langmuir

adsorption isotherm models are widely used to analyse data for water and wastewater

treatment applications. Hence, in this study, the experimental data were fitted with the

Freundlich and Langmuir models.

Freundlich model

The Freundlich equation can be written as:

K C 1/n qe= F e

Where KF is a constant indicative of the relative adsorption capacity of the adsorbent

(mg1-0/n)L11ng-1) and n is the constant indicative of the intensity of adsorption. The

Freundlich expression is an exponential equation and therefore, assumes that as the

adsorbate concentration increases, the concentration of adsorbate on the adsorbent

surface also increases.

Langmuir model

The langmuir model assumes uniform energies of adsorption on to the surface and

no transmigration of adsorbate in the plane of the surface. The langmuir equation may be

written as:

qe = qmbCe

1+ bCe

where qe is the amount of solute adsorbed per unit weight of adsorbent at equilibrium (mg

g-1), Ce the equilibrium concentration of the solute in the bulk solution (mg L-1

),. qm· the

maximum adsorption capacity (mg g-1), and b is the constant related to the free energy of

the adsorption.

135

The linearized form of these models was used for calculations (Table 7.1).

Langmuir is converted into five different linear equations (Hamdaouia and Neffrechoux,

2007).

· Table 7.1. Isotherm model and their linear forms

Isotherm Equation Linear form

Freundlich q=KcYn 1 e F e lnqe = lnKF +-lnCe

n

Langmuir- I 1 1 1 1 -=----+-qe bqm ce qm

Langmuir-2 ·{; 1 1 _e =-C +--

Langmuir-3 qmbCe qe=l+bCe

Langmuir-4

Langmuir-5

7 .3. Results

7.3.1. Characteristics of fungal biomass

Scanning Electron Microoscopy (SEM)

qe qm e qmb

1 qe qe =bC+qm

e

!b._= -bq +bq C e ,m e

1 1 -=bq --b Ce m qe

Plot

lnqe vs. znce

1 1 vs.

qe C,

C, vs. ce

qe

qe vs. qe

C,

q, vs. q,

C,

1 1 VS.

ce q,

The surface morphology of the native fungus N. intennedia mycelia was

exemplified by the Scanning Electron micrograph in Figure 7 .1. As shown in the SEM

micrograph, the fungal mycelia have rough and porous surface. After adsorption the

mycelia looses its structure and wear and tear due to the particles present in the effluent is

evident. (Figure 7.1)

136

Figure 7.1. Scannaing electron microscopy of (a) native fungal mycelium N. intermedia

(top) (b) biosorbed fungal mycelium (Bisorption of distillery effluent) (bottom)

Fourier Transform Infrared Spectroscopy (FTIR).

In order to confirm the existence of functional bioadsorption groups (i .e., amino,

carboxyl and phosphate) on the fungal biomass and its different preparations, the FTIR

spectra of the finely powdered dried fungal biomasses were obtained. The spectra for

native fungal biomass is shown in Figure 7.2(A). The broad stretching adsorption band at

3356 cm- 1could be assigned hydroxyl groups stretching vibrations. The-NH stretching of

the protein and the acetamido group of chitin fraction stretching vibrations bands are

superimposed on the side of the hydroxyl group band at 3500-3200 cm- 1• The band at

1659 em - I is a consequence of CO stretching vibration conjugated to NH band. The peaks

at around 1411 and 1248 em - I are caused by the CO stretching band of carbonyl groups.

137

The moderately strong absorption bands at 1030 could be assigned to the -CN stretching

vibration of the chitin-chitosan and protein fractions. Strong absorption bands at 2925

cm-1 could be assigned to the -CH stretch. These data show the presence of C, H, N and

0 elements with their functional groups.

The FfiR spectra bands of bioadsorption studies by native fungi shows that the

broad overlapping peak shift to 3391cm-1 after adsorption of distillery spent wash, which

may be due to hydroxyl or amine groups present in the effluent itself. Additionally, the

peak at 1659 cm-1 assigned to the CO stretching shifted to 1634 cm-1 suggesting its role

in adsorption. However, the peak stretching at 1411 and 1248 shifted to 1434 and 1358

respectively, after adsorption indicating the presence of additional carboxyl groups in the

effluent (Figure 7.2 B).

%T

3391.2

926.9 518.7

3356.4 1642.3

4000 3000 2000 1500 1000 450 cm-1

Figure 7.2. FfiR spectra of {A) dried unadsorbed (B) effluent adsorbed. N. intermedia

biomass

138

The FfiR spectra of these treated fungal biomasses shows that these treatments

have modified surface chemistry of the fungi. As shown in Table 7.2 there was loss of

some functional groups along with presence of some additional binding sites for the same

groups, while at the same time there was a change in the intensity for others (Figure 7.3).

(C)

3335.1

4000 3000

1606.8 1658.5 1456.7

1512.2

1645.6

2000 cm-l 1500

547.0

1000 450

Figure 7.3. FfiR spectra of (A) base (B) acid and (C) heat treated fungal biomass

preparations

139

Table 7.2. Comparative analysis of functional groups present in native, acid base and

heat treated mycelium

S. No. IR band Native Acid Base Heat

1 3500-3200 [(N-H) and 0-H] 3356 3319 3401 3335

2 2925, (C-H) 2924.4 2924.1 2925.1 2925.2

3 1659, [(N-H) amine and CO)] 1659.2 1651.8 1658.5 1645.6

4 1411, (C=O) 1411.4 - 1456.7 -

5 1248, (C=O) 1248.8 1250.8 1253.2 1252.7

6 1029, [(C-OH) and (P=O)] 1029.2 1039.5 1051.9 1034.2

7 518, (protein structure) 518 547 545.5 546.7

7.3.2. Effect of pH and temperature on adsorption

The effect of temperature on the equilibrium sorption capacity was investigated in

the temperature range of 20-40°C. The adsorption of distillery spent wash was enhanced

with raising the temperature up to 30°C and the time taken to reach the equilibrium

decreases with increasing temperature, however beyond that there was a decrease in the

further adsorption potential of the fungi with the increase in temperature (Figure 7.4a).

The pH of the aqueous solution is a controlling factor in the adsorption process. In

this study, the role of hydrogen ion concentration was examined at pH values ranging

between 2-9. The influence of pH on the bioadsorption potential of the fungi (N.

intennedia) is shown in Figure 7.4b. The most suitable pH for bioadsorption was 3 and

there was a decrease in the extent of bioadsorption potential with increase in the pH of

the solution. Hence fm1her studies were conducted at pH 3.

140

120

~ 100

> 0 E 80 Q) ... ... 0 60 0 (.)

tf. 40

20 15 20 25 30 35 40 45 2 3 4 5 6 7 8 9

Temperature pH (a) (b)

Figure 7.4. (a) Effect of temperature and (b) pH on adsorption potential of N. intennedia

7.3.3. Effect of contact time

It was found that the removal of colored pollutant from distillery spent wash

increases with increase in contact time to some extent. Further increase in contact time

does not increase the uptake due to deposition of colored pollutants on the available

adsorption sites of native fungal biomass. Preliminary investigations on the uptake of

pollutants on the adsorbent material at their optimum pH values and temperature values

indicated that the process was quite rapid. Typically, 80% of the total adsorption occurs

within the first four hours at the effluent concentration of 10% (v/v). This initial rapid

adsorption subsequently gives way to a very slow approach to equilibrium and saturation

was reached in 5-6h. For further optimization of other parameters, this contact time was

considered as the equilibrium time.

7.3.4. Biosorption isotherms

Equilibrium data, commonly known as adsorption isotherms, are the basic

requirement for the design of adsorption systems. The shape of the isotherms is the first

experimental tool to diagnose the nature of a specific adsorption phenomenon. The

amount of biosorbed coloring material onto the fungal biomass preparations was studied

and plotted as a function of the equilibrium concentration of colored material in the

biosorption medium. Several mathematical models can be used to describe experimental

data of adsorption isotherms. In this study, the equilibrium data were modeled with the

Langmuir (five linearized expressions) and Freundlich models.

141

Validation of models

The experimental values of qe and Ce detennined in adsorption isotherms were

initially treated with linearized equations of Freundlich and Langmuir to find out the

model parameters. After detennining the best model, the values of qe were recalculated

using linear equation of the model. The reconstitute isothenns were compared with initial

isothenns to evaluate the error in the models. Linear correlation coefficients (r) showed

the fit between experimental data and linearized fonns of isothenn equations while the

average percentage errors (APE) calculated according to given equation indicated the fit

between the experimental and predicted values of adsorption capacity used for plotting

isothenn curves (Hamdaouia and Neffrechoux, 2007).

APE%= 4\-1 { (ge)experimental-(qe) predicted} I (ge) experimental X 100

N Where N is the number of experimental data.

Langmuir isotherm

The adsorption data obtained for colored pollutants in the distillery spent wash

was analyzed by regression analysis to fit the five linearized expressions of Langmuir

isothenn models. The details of these different fonns of linearized Langmuir equations

and the method to estimate the Langmuir constants qm and b from these plots are shown

in Table 7.3. The favorable nature of adsorption can be expressed in terms of

dimensionless equilibrium parameter of Hall (Hall et al., 1996).

RL= lfl+bC0

Where b is the Langmuir constant and C0 is the initial concentration of the adsorbate in

the solution. The values of RL indicates the type of isothenn to be irreversible (RL=O),

favorable (O<RL<l), linear (RL=l) or unfavorable (RL>l) ((Hamdaouia and Neffrechoux,

2007. The values for RL were 0.54, 0.81, 0.42 and 0.79 for native, acid, base and heat

respectively. RL values were less than 1 and greater than zero indicating favorable

adsorption.

In order to check the validity of the Langmuir model, it is interesting and essential

to recalculate the adsorbed amounts using the equilibrium concentration values and

Langmuir parameters detennined using the five linearized fonns of the equation. The best

142

' fitting model for native, acid and heat was Langmuir- I with r-values 0.8819, 0.9988 and

0.9298, respectively and Langmuir-2 was best fitting model for base treated fungi

(r=0.9777) The calculated average percentage errors for Langmuir 1,2 and 3 are shown in

Table 7.3. It is clear from the average percentage errors shown in Table 7.3 that inspite of

the lowest value of average percentage errorin Langmuir-2 for acid treated fungi, this·

model does not describe perfectly the equilibrium data because of the lower values of

coefficients of correlation. Thus, it is not appropriate to use the coefficient of correlation

of the linear regression method for comparing the best~fitting isotherms. The qm values

based on Langmuir 1 model shows that maximum adsorption was in the series native>

heat >acid, base (Table7 .3). The values of qe, Ce and graphs of initial isotherms and

reconstituted isotherms are given in appendix I.

Freundlich isotherm

The equilibrium data was further analyzed using the linearized form of Freundlich

equation using the same set experimental data, by plotting lnqe versus lnCe. The

calculated Freundlich isotherm constants and the corresponding coefficient of correlation

values were shown in Table 7.3. The fitness of Freundlich model for all the four types of

experimental data was in the order of acid> base> native> heat. The magnitude of the

exponent n gives an indication on the favorability of adsorption. The n values are > 1 for

all the tested fungal biomass preparations, indicating a favorable adsorption process.

However, heat treated fungal biomass preparation showed poor adsorption capacity as the

n value was less than one (0.98) along with lowest value of coefficient of correlation.

143

Table 7 .3. Summarized values of various isotherm parameters for adsorption of effluent

on Neurospora intennedia

~sotherm NATIVE ACID BASE HEAT !Freundlich ...

0.8766 0.9898 0.9434 0.8678 V\PE% 15.17121 4.542265 12.02121 13.572929 !KF(CU 1-ltnLIIng-1) 1.743 1.142 11.279 2.233

~ 1.141422 1.214477 1.550628 0.9801039 !Langmuir 1

0.8819 0.9988 0.9636 0.9298 APE% 15.77206 4.723965 7.327218 16.462239 Qm(CU g-1

) 33300 5000 5000 10000 b(LCU-1

) 0.00016 0.000067 0.0002 0.000049 Langmuir2

0.2625 0.9053 0.9777 0.006 APE% 28.33244 3.505215 6.237372 13.40558 qm(CU g-1) 16700 5000 5000 100000 b(LCU-1

) 0.000034 0.000067 0.0002 0.0000044 1Langmuir3 lr 0.0282 0.849 0.8562 0.1438 V\PE% 42.83899 17.94081 9.241919 41.200438 lqm(CU g-1

) 4008.9 5165.4 5330 220.78 lb(LCU-1

) 0.00018 0.000064 0.00018 -0.00052 Langmuir4

0.0282 0.849 0.8562 0.1438 qm(CU g-1

) 27500 4700 1594.35 -17900 b(LCU-1

) 0.00002 0.00006 0.0002 -0.00003 Langmuir5

0.8819 0.9988 0.9696 0.9298 lqm(CU g-•) 12000 5720 1594.35 7760 lb(LCU-1) 0.00004 0.00005 0.0002 0.00005

7 .4. Discussion

Various workers have investigated the biosorption of various organic pollutants

and color from wastewaters (Tsezos and Bell, 1989; Fu and Viraraghavan, 2001).

Biosorption of heavy metals in aqueous solutions has received increasing attention in

recent years (Kac,ar et al., 2002; Bai and Abraham, 2003; Abu Al-Rub et al., 2004). As

an efficient, cost-effective and environmentally friendly technique, biosorption for heavy

metals and various organic pollutants has emerged as a potential alternative to the

144

conventional techniques. Phanerochaete chrysosporium is a well-known white-rot fungus

and it has a strong ability to biosorb various xenobiotics (Benoit et al., 1998). A few

studies have been carried out with P. chrysosporium for detoxifying chlorophenol­

bearing effluents (Aksu and Yener, 1998; Benoit et al., 1998). Most studies about

biosorption have focused on the use of dead biomass in powdered fonil. Microbial

biomass is inexpensive and many fungal and bacterial species have been shown as

potential biosorbents. Certain basidiomycetes, Phanerochaete chrysosporium, Bacillus

cereus, Plasiomonas achromobacter, Rhodococcus sp. were tested as dye degrading

microorganisms. Other biomasses such as Aeromonas sp. and Fomitopsis carnea have

been used to successfully adsorb reactive and cationic dyes respectively (Hu, 1992; .

Mittal and Gupta 1996).

The scanning electron microscopy of untreated fungi shows extremely rough and

porous morphology of the fungi. This surface property increases the total surface area and

thus improves adsorption capability of the fungus (Bayramoglu et al., 2006). The effluent

adsorbs on the surface of the mycelium ultimately destroyed the surface properties. The

suspended solids present in the effluent collide with the mycelium and wear and tear of

the mycelium takes place (Figure 7.1 ).

The biosorption potential of the fungi Neurospora intermedia has been identified

in chapter three. From the results of FT-IR it is clear that it contains chitin and chitosan

(Figure 7.2). These chemical compounds are involved in biosorption (Saiano et al.,

2005). Similar studies has been shown by using Rhizopus sp. (Volesky and May-Philips,

1995). FTIR studies also showed that the bands associated with colorants/ compounds in

distillery effluent were also observed in the effluent treated mycelium (Pandey, 1999;

Hoareau et al., 2004). Both native and physically (heat)- chemically (acid, base) treated.

fungal biomasses have been used to remove colored pollutant from aqueous medium

(Vandeviverae et al., 1998; Ozer et al., 2005). In our study of FT-IR, data revealed that

the chemical moieties associated with the fungal mycelium underwent changes when

mycelium was given acid, base and heat treatment (Figure 7.3, Table 7 .2). This change

was positive or negative. Treatment of mycelium led to loss of some functional groups.

Due to the complex nature of the process of adsorption it is not possible to predict the

adsorption capability accurately depending on the chemistry of the mycelium

145

(Bayramoglu et al., 2006). The results of this study clearly showed that physical and

chemical surface modification methods can be used to maximize the color removal

efficiency of different preparations of fungal biomass Thus, further studies involved the

equilibrium isotherm study of all four types of mycelium preparations.

·· ·It was found that best performance was by base treated mycelium followed by -

acid, then native and finally heat. However, the band intensities showed different patterns

with different treatments. Variability in the response of fungi after acid, base and heat

treatment has been reported in case of Phanerocheate chrysosporium (Bayramoglu et al.,

2006). For the linear models, the coefficient of determination (r2) is widely used in

assessment of isotherm accuracies and is commonly determined by the least squares

method (Dagnelie, 1998). Among the tested isotherm models Langmuir models were

more applicable to the type of biosorption achieved by fungal biomass preparations.

These results suggested that different preparation of N. intennedia biomasses have

potential applications in biotreatment systems for color removal from different industrial

effluents. The value of constant n was greater than 1 hence, all the adsorption process

were favorable. From the model we can say that adsorption has uniform energies on the

surface and there is no transmigration of adsorbate in the plane of the surface. Moreover,

. as the adsorbate concentration increases, the concentration of adsorbate on the adsorbent

surface also increases.

Research indicates that there are many factors of the adsorbent and the adsorbate

that can affect the extent and rate of adsorption process. Surface chemistry and the

distribution of adsorption sites on the surface of the adsorbent play a significant role in

the adsorption process. Distillery spent wash contains complex polymeric organic

compounds having different aromatic rings and functional groups and thus have varying

ionization potentials at different pH ultimately showing varying biosorption potential at

different pH values. The fungal cell wall is composed of polysaccharides (i.e. chitin and

chitosan), proteins, lipids and melanin with several functional groups (such as amino,

carboxyl, thiol and phosphate groups) capable of binding various organic molecules

(Yesilada et al., 2003). The ionic forms of these organic compounds in solution and the

surface electrical charge of the biomass depend on the solution pH. Therefore, the

interaction between an adsorbate and biosorbent is mainly affected by ionization states of

146

the functional groups on both the molecule and biosorbent surface (Maurya et al., 2006).

Low pH has been found to favor adsorption of dyes (Aksu and Donmez, 2002) and heavy

metals (Bai and Abraham, 2003) by the biomass of yeast and fungi and also by other

adsorbents such as eucalyptus bark (Morais et al., 1999). Our studies also showed that

· lower pH values were favorable for adsorption process. Similar results were alsn found

by Hu (1992) and Mahony et al. (2002) while carrying out adsorption studies of different

reactive dyes.

The biosorption of the colored pollutants increased with increasing temperature

till 30°C due to increased surface activity and increased kinetic energy of the dye

molecules. Similar observations were reported in the literature (Arica and Bayramoglu,

2005). Aksu and Cagatay reported that the adsorption capacity of.-Chlorella vulgaris for

Ramazol Black B dye was increased as the temperature increased (Aksu and Cagatay,

2006). However, beyond 30°C there was decrease in the percentage biosorption.

In our study the equilibrium for adsorption was reached very early in which 80%

biosorption was completed within first 4 hours. Similar studies were observed by Kiff

and Little ( 1986) while studying biosorption where A. oryzae was used and it reached

equilibrium in 1 hour with 90% biosorption taking place in the initial 10 min at pH 6.0.

On the contrary, biosorption of metal ions i.e. lead, cadmium, copper and nickel by A.

niger took a longer time to reach equilibrium at a pH of 4-6 (Kapoor et al., 1999). This

surface binding involves specific chemical sites or functional groups on the cell wall,

performance of which is affected by pH and other ions.

147