Media Optimization for the Decolorization of Distillery...
Transcript of Media Optimization for the Decolorization of Distillery...
International Journal of Innovations in Engineering and Technology (IJIET)
Vol. 4 Issue 1 August 2014 8 ISSN: 2319 – 1058
Media Optimization for the Decolorization of
Distillery Spent Wash by Biological Treatment
using Pseudomonas Fluorescence
M.Ananda Boopathy
Department of Biotechnology
Mepco Schelnk Engineering College, Sivakasi, Tamilnadu
S.N.S.Senthilkumar
Department of Biotechnology
Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu
Abstract -The wastewater released from distilleries and fermentation industries are the major source of soil and aquatic
pollution due to presence of water-soluble recalcitrant colouring compounds called melanoidins. Biological
decolourisation of of these compounds found more advantages compared to chemical treatments. Hence in this study, the
bacterium Pseudomonas fluorescens showing higher decolorization efficiency on distillery spent wash was screened.
Physico-chemical properties like colour, pH, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), etc.,
were analyzed for the substrate. Effect of carbon and nitrogen supplementation on media was studied followed by media
optimization for different carbon, nitrogen and salt concentrations were carried out using Response Surface
Methodology. The central composite design (CCD), consisting of a three-factor-four-level pattern with 17 design points,
was then conducted in this optimum vicinity to locate the true optimum concentrations which are as follows: Glucose
(0.8%), Peptone (0.8%) and KH2Po4 (0.05%). Hence it is found that higher decolorization of distillery spent wash could
be achieved at low carbon and nitrogen concentrations. Thus this bacterium can be utilized for melanoidin decolorization
of distillery effluent at industrial scale.
Keywords: decolourization, Pseudomonas fluorescens, distillery spent wash, media optimization.
I. INTRODUCTION
Distilleries and fermentation industries produces dark brown color spent wash with a high Biological Oxygen
Demand (BOD), Chemical Oxygen Demand (COD), low pH and toxic substances such as phenols. The main
problem in treating Distillery Spent Wash (DSW) is its color, which contains nearly 2% (w/w) of a dark brown
recalcitrant pigment, melanoidin. Melanoidin is known as a natural browning polymer, produced by the “Maillard
reaction” between amino and carbonyl groups of organic matters and is closely related to humic substances in the
natural environment. Naturally melanoidins are widely distributed in food drinks and widely discharged in huge
amount by various agro-based industries especially from cane molasses based distilleries and fermentation industries
as environmental pollutants. The structure of melanoidins is still not completely understood but it is assumed that it
does not have a definite structure as its elemental composition and chemical structures largely depend on the
nature and molar concentration of parent reacting compounds and reaction conditions as pH, temperature,
heating time and solvent system used. Carbon isotope ratios support the stoichiometric ratios for the combination
of sugars with amino acids, which are based on the elemental composition data of melanoidins. Hence for its safe
disposal into the environment, pretreatment is required.
Degradation and decolourisation of these wastewaters by chemical methods, flocculation treatment and
physicochemical treatment such as ozonation and activated carbon adsorption have been accomplished, but these
methods are not economically feasible on large scale due to cost limitation whereas biological decolourisation by
using bacteria such as Pseudomonas fluorescens, Pseudomonas putida, Bacillus sp. , Alkaligenes sp., Lactobacillus
sp., have been successfully achieved and thus can be applied as bioremediation techniques. However, the biological
decolourisation of wastewaters containing melanoidins depends on pH, temperature, concentration of nutrients,
oxygen and inoculums size while the enzymatic system responsible for the degradation of melanoidins consists
mainly sugar oxidases and peroxidases as sarbos oxidase, glucose oxidase, manganese dependent and independent
peroxidases (MnP and MIP) (Watanabe et al., 1982; Ohmomo et al., 1985a; Aoshima et al., 1985).
International Journal of Innovations in Engineering and Technology (IJIET)
Vol. 4 Issue 1 August 2014 9 ISSN: 2319 – 1058
Biological methods present an incredible alternate for decolorizaiton/degradation and bioremediation of spent wash
due to their low cost,environmental friendly and publicly acceptable treatment and cost competitive alternative to
chemical decomposition processes.
II. MATERIALS AND METHODS
Microorganisms and Culture Medium
Fifteen strains were initially taken. The strains were identified on the basis of its decolorizing capacity. The screened
strain was maintained in LB broth at 4oC and was used for further studies
Preparation of seed culture
Seed culture was prepared by inoculating organisms in nutrient broth at 32oC and overnight night cultures were used
for inoculating the decolorization medium.
Distillery spentwash (DSW)
The spentwash was collected aseptically from Dharani sugars and Chemicals pvt.ltd, Tirunelveli, India. The
spentwash was centrifuged at 10,000 rpm for 15 min before use to remove the suspended solids and stored at 4°C.
The stored distillery spentwash was filtered through (Whatman No: 1) filter paper and was diluted with distilled
water. The analysis of different physico-chemical parameters like color, odor, pH, biological oxygen demand
(BOD), chemical oxygen demand (COD) were analyzed by employing standard methods.
Determination of BOD (Biological oxygen demand)
BOD was determined as follows; 0.1, 1.0, 2.0, 4.0, 6.0 ml of samples (Spent wash) were taken and made up to
300ml with distilled water. To this,15 drops of alkaline iodide solution was added followed by addition of
conc.H2SO4 of same volume. 15 drops of starch solution was added to 203ml of above solution which was titrated
against Sodium thiosulphate solution taken in burette. The endpoint is the disappearance of blue colour.
Determination of COD (chemical oxygen demand)
COD was determined as follows; 50 ml of diluted sample was taken. To this 1g of mercuric sulphate and 5 ml
of sulphuricacid-silver sulphate reagent was added followed by addition of 25ml of std. potassium dichromate
solution and 30ml of sulphuric acid-silver sulphate reagent and boiled for 2hours.After cooling , 2-5drops of
ferroin indicator was added and titrated against std. Ferrous ammonium sulphate.The endpoint is the color change
from yellowish green to reddish brown.
Decolorization assay
The strains were inoculated in the LB broth containing distillery spent wash. After incubation, the broth was
centrifuged at 10,000 rpm for 10 min. The supernatant was read at absorbance maximum (Amax) of the melanoidin
i.e. 475 nm.The decolorization yield percentage was expressed as the decrease in the absorbance at 475 nm against
initial absorbance at the same wavelength. Uninoculated medium was served as control. The entire assay was
performed in triplicates and compared with control. The decolorization efficiency of the isolate was expressed as per
following equation:
Decolorization (%) = I – F/I
Where, I = Initial absorbance (Control) and F = Absorbance of decolorized medium broth.
Biomass determination
Biomass is determined by using the standard formula 1OD = 0.37g/l of dry cellular weight.
III. SELECTION OF PHYSICO-CHEMICAL AND NUTRITIONAL PARAMETERS FOR MELANOIDIN DECOLORIZATION:
Effect of pH, temperature and time on the decolourisation activity
Optimum pH for the decolourisation activity was determined by inoculating the microbial culture in spent wash
medium in the pH range of 3.5-9.0 and incubated at room temperature. Effect of temperature on the decolourisation
activity was determined by inoculating the microbial culture in the same medium over a temperature range of 30-
80oC.Effect of time for efficient decolorisation was determined by incubating the medium for 24h,48h,72h and the
results were analyzed.
International Journal of Innovations in Engineering and Technology (IJIET)
Vol. 4 Issue 1 August 2014 10 ISSN: 2319 – 1058
Optimization of experimental conditions
The various process parameters influencing melanoidin decolorization and biomass production were optimized
individually and independently of the others, therefore, the optimized conditions were subsequently used in all the
experiments in sequential order. For optimization, the basal medium contained glucose0.5%; peptone 0.1 %;
KH2Po4 0.05% with 3.5 OD spentwash was used for inoculation with 2% (v/v) of bacterial culture. For the optimal
melanoidin decolorization and biomass production, the strains may require additional carbon and nitrogen sources
with varying concentrations in its growth media. Therefore, the growth medium was supplemented with the different
carbon sources viz. glucose, sucrose, cellulose and nitrogen sources viz. yeast extract, peptone, beef extract.
Thereafter, optimized carbon and nitrogen sources were further optimized at different concentration (0.2 to 1%,
w/v). The medium was sterilized at 121°Cfor 15 min and incubation was done at 30°C with all the other conditions
at the optimal levels.
Statistical analysis
All experiments were carried out in triplicates and the results are presented as the mean of three independent
observations. Standard deviation for each experimental result was calculated using MS Excel. All the graphs were
plotted using Origin pro.
IV. RESULTS AND DISCUSSION
Physico-chemical analysis of the effluent was carried out. The colour of spent wash was found dark brown. The
colour of spent wash is suspected due to presence of a derivative of caramelized sugar formed during the distillation,
termed melanoidin (9).Odour of the distillery effluent was offensive. Odourous compounds from distillery waste
water mainly consist of volatile fatty acids such as butyric and valeric acids that have a high odour index. Distillery
has distinct organic compositions. Various anaerobic bacteria ferment these compounds and generate products such
as volatile fatty acids for example glycerol is fermented into butyric acid by clostridium butyricum (17).The pH of
the spent wash was acidic in nature i.e. 4.1 (the raw spent wash is acidic in nature and the pH values of distillery
wastewaters range from 3.5 to 5.0) (18, 19). BOD and COD were found to be 38130 mg/l and 95564 mg/l
respectively. For assay determination, wavelength scan of distillery spent wash was done (Fig.1). The sample
showed maximum absorbance at 475nm.
Out of fifteen species screened, Pseudomonas fluorescens showed maximum efficiency of decolorization and hence
this bacterium is used further for media optimization studies.
Maximum decolourisation effect was found within the pH range of 6.5 to 7.0, the preferred range for the growth of
isolate. Temperature range of 30-35 oC was found to be suitable for the activity. Under optimum pH and
temperature, decolourisation efficiency was notable at 72h for the screened species.
The effect of various sugars and nitrogen as externally added carbon and nitrogen sources in the spent wash
medium, on decolourisation activity was studied. Maximum melanoidin decolorization was observed in glucose as
well as sucrose as carbon source at the level of 0.8%.This effect can be explained that during initial phase of growth,
organism utilizes easily available carbon sources added to the medium and then starts to degrade spentwash that is
complex carbon source(Kumar et al., 1997). Ohmomo et al. (1987) reported that glucose was the best carbon source,
which utilized by Aspergillus fumigates G-2-6 for maximum degradation of melanoidins and further increase in
glucose concentration, increased the mycelial biomass but no change in decolorization level. Watanabe et al.
(1982)have reported that the enzymatic degradation of melanoidin by Coriolus sp. No. 20 having an intracellular
enzyme, which required active oxygen molecules and sugars (sorbose as well as glucose) in the reaction mixture,
was later identified as sorbose oxidase which oxidize glucose into gluconic acid (Miyata et al.,2000; D’souza
et al., 2006). The decline in melanoidin decolorization encountered with high sugar concentration in the medium is
probably due to inhibition effect to the enzyme like lignolytic activity of laccase enzyme and oxidation activity of
the peroxidase (Raghukumar and Rivonkar, 2001;Guimaraes et al.,2005; Pant et al., 2008; Jiranuntipon et al., 2008;
Zhao et al.,2010; Ravikumar et al., 2011). Different nitrogen sources were optimized for melanoidin decolorization.
Among different nitrogen sources (organic and inorganic), the highest melanoidin decolorization was reported with
peptone at the level of 0.8%. Similarly various nitrogen sources were optimized by different workers for melanoidin
decolorization, but peptone was the most effective for color removal (Ohmomo et al., 1988; Miyata et al.,2000;
Sirianuntapiboon et al.,2004a; 2004b; Ravikumar et al., 2011). Kirk et al. (1978) reported that enzymatic systems
catalyse degradation of lignin and lignin-like compound during the secondary phase of the metabolic growth in the
presence of peptone. Synthesis and secretion of lignin peroxidase or ligninase (LiP) and manganese-dependent
peroxidase (MnP) are triggered by nutrient limitations such as carbon and nitrogen sources. At high concentration,
there was no significant decolorization due to surplus supplementation of nitrogen which inhibited the growth.
International Journal of Innovations in Engineering and Technology (IJIET)
Vol. 4 Issue 1 August 2014 11 ISSN: 2319 – 1058
Similar effect was observed when low concentration of peptone was used as nitrogen source for decolorization of
melanoidin pigment present in the spent wash.
Response surface methodology uses statistical models. In practice, both the models and the parameter values are
unknown, and subject to uncertainty on top of ignorance. Of course, an estimated optimum point need not be
optimum in reality, because of the errors of the estimates and of the inadequacies of the model.
In our study, Response Surface Methodology (RSM) was used to study the effects of carbon, nitrogen, salts, on
Decolorization. Interactions between each variable were calculated by experimental designs. The factorial design
was performed to study the decolorization and the effects of glucose concentration, Sucrose, cellulose, peptone,
yeast extract,beef extract, Potassium di hydrogen Phosphate (KH2PO4-- ).
The Model F-value of 11.34 implies the model is significant. There is only a
0.04% chance that a "Model F-Value" this large could occur due to noise.Values of "Prob > F" less than 0.0500
indicate model terms are significant. In this case C, BC, A2, B2, C2 are significant model terms.Values greater than
0.1000 indicate the model terms are not significant.
The "Lack of Fit F-value" of 3.33 implies the Lack of Fit is not significant relative to the pureerror. There is a
10.66% chance that a "Lack of Fit F-value" this large could occur due to noise. Non-significant lack of fit is good.
"Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 10.037
indicates an adequate signal. This model can be used to navigate the design space.
From this study, it was found that Melanoidin present in distillery spent wash can be degraded and hence the spent
wash can be decolorized by using the bacteria Pseudomonas fluorescens. Thus this bacterium can be used in
biological treatment of spent wash and this method could be used to treat distillery spent wash and hence can
prevent environmental pollution.
V. DETERMINATION OF CENTRAL LEVELS:
Effect of Different Carbon sources on Decolorisation
Figure 1: Effect of cellulose on decolorisation and biomass
Figure 2: Effect of glucose on decolorisation and biomass
International Journal of Innovations in Engineering and Technology (IJIET)
Vol. 4 Issue 1 August 2014 12 ISSN: 2319 – 1058
Figure 3: Effect of sucrose on decolorization and biomass
Effect of Different Nitrogen Sources on decolorization and biomass
Figure 4: Effect of Yeast extract on decolorization and biomas
Figure 5: Effect of Peptone on decolorization and biomass
International Journal of Innovations in Engineering and Technology (IJIET)
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Figure 6: Effect of Beef extract on decolorization and biomass
Experimental run from Design expert
Table 1: Experimental runs
Factor 1 Factor 2 Factor 3 Response 1
Std Run A:Glucose B:Peptone C:KH2Po4 Decolorization
14 1 0.8 0.8 0.075 74
15 2 0.8 0.8
0.075 74
2 3 1 0.6 0.075 61
3 4 0.6 1 0.075 70
12 5 0.8 1 0.1 60
13 6 0.8 0.8 0.075 74
8 7 1 0.8 0.1 65
6 8 1 0.8 0.05 69
5 9 0.6 0.8 0.05 67
16 10 0.8 0.8 0.075 74
10 11 0.8 1 0.05 71
17 12 0.8 0.8 0.075 74
11 13 0.8 0.6 0.1 75
4 14 1 1 0.075 68
7 15 0.6 0.8 0.1 62
1 16 0.6 0.6 0.075 66
9 17 0.8 0.6 0.05 64
VI. ANOVA RESPONSE AND
VALUES
International Journal of Innovations in Engineering and Technology (IJIET)
Vol. 4 Issue 1 August 2014 14 ISSN: 2319 – 1058
Std DEV Mean C.V
%
PRESS R-
Squared
Adj R-
squared
Pred R
squared
Adeq
Recession
372.96 4925.65 7.57 8.775E+006 0.9108 0.8304 0.4370 10.037
Effect of Interaction between nutrients
Glucose and Peptone Glucose and KH2Po4
Interaction between Peptone and KH2PO4
The advantage of using RSM is that the prediction of limiting nutrient which is given by the perturbation graph.
Here “A” i.e. glucose is the limiting nutrient
International Journal of Innovations in Engineering and Technology (IJIET)
Vol. 4 Issue 1 August 2014 15 ISSN: 2319 – 1058
Perturbation graph for prediction of limiting nutrient
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