ISOLATION OF NOVEL AEROBIC DENITRIFIER AND OPTIMIZATION OF PROCESS PARAMETERS FOR BIOLOGICAL DENITRIFICATION USING RSM
AUTHORSKeshava Joshi, Lokeshwari N., Vinayaka B. Shet, Srinikethan G., Ashwini, Sneha, Anusha, Aparna A.
The study was aimed to isolate and characterize a high efficiency novel denitrifier bacterium for reducing nitrate in wastewater and the optimization of the process parameters for biological denitrification. One of the bacteria among four chosen for study displayed maximum of 98% reduction of nitrate. The strain was identified as Enterobacter sp. NCCP-29 by biochemical tests and further identified based on similarity of PCR-16S rRNA using universal primers. The parameter (pH, temperature, agitation speed, C:N ratio) which affect the denitrification were screened using one factor at a time approach. The pH, temperature and C:N ratio exhibited significant affect on the denitrification using Enterobacter sp. NCCP-29. The levels of these parameters were optimized using a central composite design (CCD). The denitrification of 98% was achieved at optimized conditions (pH 6.5, temperature 30°C and C: N ratio of 3:1). The second order model was generated and found to have good fit with R2 value of 0.93.The investigation revealed the ability of Enterobacter sp. NCCP-29 to remove nitrate under aerobic conditions.
KEYWORDSC:N ratio, Enterobacter sp. NCCP-29., pH, Polymerase Chain Reaction, RSM, Temperature
Nitrates cause the most serious problems when dispersed in water since they cause the depletion of aquifers and the eutrophication of rivers. Sources of nitrate comprise natural cycle and human activities, mainly from uncontrolled land discharges of treated or raw domestic and industrial waste waters, landfills, and animal wastes predominantly from animal farms (Vitousek et al., 1997 and Galloway et al., 2008). Therefore, several studies focused on the nitrate removal from wastewater in order to achieve an acceptable concentration in treated waters to be discharged into the environment. Denitrifying microorganisms are ubiquitous in nature and they have been isolated from different ecological sources. Nitrogen containing ions such as nitrate and nitrite occur widely in a variety of process streams, such as those coming from the extensive use of fertilizers. These species can have serious consequences when released in the environment, due to the possible health effects for many organisms including humans (Matsuzaka et al., 2003). Various researchers have isolated denitrifying bacteria from diverse environments such as agricultural soils, deep sea sediments, wastewater treatment plants, biofilms of long term aerobic/anoxic denitrifying reactor and have isolated potential denitrifiers from various nitrate enriched regions such as petrochemical industry effluent, greenhouse soil of agricultural land (Zumfit, 1997; Rezaee et al., 2010; Wang et al., 2013; Zhou et al., 2014, Kong et al., 2018). In this study, the isolated denitrifying bacteria from municipal waste water with high denitrification potential were identified and characterized, using their morphological and biochemical properties, and 16S rRNA analyses. 16s rDNA gene sequence was used for the identification of isolated strain. The effect of isolate on nitrate reduction with different process parameters was studied. The study also analyzed with general factorial design and model variation trends for three parameters of pH, Temperature and C: N ratio. Response surface methodology (RSM) has an important application in the process design and optimization as well as the improvement of existing design (Box and Draper, 1987). This methodology is more practical than other methods of approaches arise from an experimental methodology which includes interactive effects among the variables and, eventually, it depicts the overall effects of the parameters on the process (Bas and Boyaci, 2007). In the last few years, RSM has been applied to optimize and evaluate the interactive effects of independent factors in numerous chemical and biochemical processes (Yang and Hwang, 2003; Ahmadi et al., 2005; Aghamohammadi et al., 2007; Zinatizadeh et al., 2009).
MATERIAL AND METHODS
Composition of Nitrate rich (NR) medium was NH4Cl-0.3g/L, KH2PO4-1.5g/L, Na2HPO4.7H2O- 7.9g/L, KNO3-2 g/L, disodium succinate-27g/L, MgSO4.7H2O-5 mL/L (20g/L).
Composition of trace element solution : 5 mL/L (composition – EDTA, 50.0 g/L; ZnSO4, 2.2 g/L; CaCl2, 5.5 g/L; MnCl2.4H2O, 5.06 g/L; FeSO4.7H2O, 5.0 g/L; (NH4)6Mo7O24.4H2O, 1.1 g/L; CuSO4.5H2O, 1.57 g/L; and CoCl2.6H2O, 1.61 g/L; pH 7.2) and Na2SO3– 100 mg/L .
Composition of bromothymol blue (BTB) medium: L-asparagine, 1 g/L; KNO3,1g/L; KH2PO4, 1 g/L; FeCl2, 0.05 g/L; CaCl2, 0.2 g/L; MgSO4.7H2O, 1 g/L; BTB reagent, 1 mL/L (1% in ethanol); and agar, 20 g/L (pH 7.3).
Isolation and screening of denitrifier by enrichment methods
The isolation of microorganisms was from nitrate enriched (66mg/L) municipal waste water was carried out by enrichment technique. 5 mL or 5g of collected samples were transferred separately into NR medium and incubated in a shaker at 30°C and at 150 rpm for 2days, and the flasks were maintained under aerobic and anoxic conditions separately. After two days, 5 mL of the sample was withdrawn from each, and transferred to fresh NR media and incubated under the same conditions. This procedure was repeated for two more times. After 6 days of incubation period, the samples were diluted from 10-3 to 10-7since they were more turbid. The resulting bacterial suspensions were plated onto bromothymol blue (BTB) medium plates using spread plate technique and incubated at 30°C for 1–3 days to screen denitrifiers. The colonies formed on each plate were counted using a colony counter and the Colony Forming Units (CFU) per ml or g was calculated by a standard plate count method. The blue color colonies and /or halo forming colonies on the BTB medium which indicated the presence of denitrifying microorganisms of the cultures were subjected to further screening. The colonies showing halo on the selective BTB medium were further screened by inoculating into NR medium and incubated under aerobic (Erlenmeyer flasks) and anoxic (BOD bottles) conditions separately. 10 mL of samples were withdrawn after 48 hours and then centrifuged at 1000 rpm for 10 min, and the supernatant was analyzed for residual nitrate to select the efficient denitrifier.
Culture maintenance and storage
Nutrient Agar (NA) medium was used for the growth and maintenance of bacteria. Nutrient agar medium containing the components-peptone 5.0 g/L, sodium chloride 5.0 g/L, yeast extract 2.0 g/L, beef extract 1.0 g/L and agar 15.0 g/L was used and the initial pH of the medium was maintained at 7.2. The medium components were suspended in distilled water before autoclaving at 121ºC for 20 min at 15 psi. The medium was then cooled prior to transferring into sterile petri dishes. The molten agar was left to cool and solidify at room temperature. The bacteria were streaked on the agar medium and incubated at 30ºC for 1 to 2 days and after observing growth they were stored at 4ºC. The pure cultures of bacteria were sub-cultured at regular intervals.
Identification of isolate
Based on the results of various screening tests, the bacterial isolate, designated as ASA was identified as a potential denitrifier and it was selected for further studies. The bacterial isolate was sent to Cyxton Biosolutions Pvt. Ltd., Hubballi, Karnataka, India for partial 16s RNA sequencing for its identification. The purity of stains, DNA isolation, purity and quantification, 1.5kb PCR run, sequencing, blast and gene bank run, and phylogenetic tree were analyzed.
Denitrification studies of a potential Isolate
Nitrate rich (NR) medium inoculated with isolate was used for denitrification to study the effect of various physico-chemical parameters on denitrification. The experiments were conducted to study the effect of parameters like initial pH of the medium, incubation temperature, agitation speed, carbon sources, and carbon to nitrogen ratio on denitrification. In each case, sample cultures were withdrawn for every 6h of incubation for biomass, and nitrate analysis.
The statistical method of factorial design of experiments (DOEs) eliminates systematic errors with an estimate of the experimental error and minimizes the number of experiments. In this study, the central composite design (CCD) was applied to design the experimental conditions using Design-Expert software (version 9.0). The experimental design consisted of 2k factorial points augmented by 2k axial points and a center point, where k is the number of variables (Lim and Lee, 2013; Rastegar et al., 2011). The behavior of the system was explained by the quadratic equation
Where Y represents the response, βo is the interception coefficient, βi is coefficient of the linear effect, βii is the coefficient of quadratic effect and βij is the coefficient of the interaction effect. Xi and Xj represent the coded independent variables. From the initial screening experiments by one factor at a time method, the factors such as temperature (A), pH (B) and C: N ratio (C) was found to have a significant effect on percentage denitrification. Hence, these variables were chosen as the independent variables. The model obtained from regression analysis was employed to generate response surface and contour plots. The quality of the fitting of the polynomial model equation was expressed via the coefficient of determination, R2, and its statistical significance was analyzed through an F-test in the same program. The significance of the regression coefficient was tested via a t-test (Rastegar et al., 2011; Yue et al., 2007). Numerical optimization of the process was performed through the model developed in the software according to different limitations placed on the primary variables.
Growth of the bacterium was monitored by measuring the optical density at 610 nm using UV-Visible Spectrophotometer (Genesys 10S). The culture samples were centrifuged at 10,000 rpm for 10 min (Make Laby, T-60) and supernatant was used for nitrate analysis by UV-Visible Spectrophotometer (Genesys 10S) (Dhamole et al., 2007; Joshi et al., 2014). This study was done using APHA 2012 Section 4500 NO3-B method and materials used were HCl, nitrite ion standard (1000 mg NO3– /L), and Reverse Osmosis (RO) water samples. Sample analysis was carried out using UV-Visible Spectrophotometer (Genesys 10S) and followed 220 nm and 275 nm wavelength.The nitrate removal percentage was estimated by taking the difference with initial and final concentration of nitrate and divided by the initial concentration.
RESULTS AND DISCUSSION
Isolation of microorganism
Aerobic denitrifying bacteria were isolated from municipal waste water plant nearby the Dharwad city, Karnataka, India. Four strains were obtained as denitrifier from the initial solid agar screening techniques. Here the colonies formed blue color and/or halos zones on BTB agar medium due to an increase in pH (Kim et al., 2008). These strains were individually separated and further employed in liquid cultures for confirming the denitrification process. Among the four strains, ASA3 showed 98% nitrate reduction and it was further sent for identification.
Identification of microorganism
The bacterial isolate was further identified by 16S rRNA partial genome sequencing method. The culture sample was processed for isolation and purification of genomic RNA. The isolated RNA was amplified using PCR with a combination of primers FDD2 – RPP2 as shown in Fig.1.a. After the amplification process, the 16S rRNA genomic sequence was identified using the Basic Local Alignment Search Tool (BLAST). The genomic sequence is presented in Fig. 1.b. Polymerase chain reaction (PCR) is a technique used in molecular biology to amplify a single copy or a few copies of a segment of DNA across several orders of magnitude, generating thousands to millions of copies of a particular DNA sequence. The first step in a PCR cycle is the denaturation step, where the hydrogen bonds holding the complementary strands of DNA together are broken. The second step in a PCR cycle is the annealing step, in which the primers anneal, or attach, to the DNA template. A phylogenetic tree was constructed by the neighbor joining method as shown in Fig. 1.c. (Kim et al., 2008; Saitou et al., 1987). With closest phylogenetic identification, the isolate was identified as Enterobacter sp. NCCP-29.
Figure 1 (a) Amplification profile of the strain, (b) 16S rRNA gene sequence of the bacterial isolate (c) Phylogenetic tree based on a comparison of the 16S rRNA gene sequence
Effect of physical and chemical parameters on the denitrification efficiency
The one factor at a time (OFAT) approach was adopted to select the significant physical parameters and the levels for the denitrification process using isolated microorganism are given in Table 1.
Table 1 Parameters and their range for OFAT studies
|Agitation speed (rpm)||0–250|
Effect of initial medium pH on denitrification
The effect of pH on denitrification was studied by growing the isolated organism in NR media of different initial medium pH with a known initial nitrate concentration. The isolate was grown for 48h and the residual nitrate concentration and biomass quantity were estimated thereafter. The results of the effect of initial medium pH on denitrification are presented in Fig. 2. It is evident from the Fig. 2 that at pH 6.5, the maximum nitrate removal of 97 % was achieved and the corresponding biomass quantity observed was 0.89 g/L. The results indicate that the isolate was found to be more effective in nitrate removal at pH ranging from 6-7.
The decomposition of carbonate ions and carbon dioxide stripping in the acidic pH range, resulting in carbon source deficiency, may be one of the reasons for less growth which further leads to less nitrate removal. It is known that, pH can affect directly the bacterial growth and its enzymatic activities (Campos and Flotats, 2003). At alkaline pH, when the reaction proceeds, the alkalinity of the reaction mixture increases which may reduce the activity of the microorganisms. Wang et al., (1995) reported that, because many enzymes are involved in the denitrification process and that enzyme kinetics are pH dependent and hence, denitrification is also pH dependent. The control of pH is important in the completion of entire denitrification without accumulation of intermediates.
Figure 2 Effect of initial medium pH on percentage of nitrate removal by Enterobacter sp. NCCP-29
Effect of incubation temperature on percentage denitrification
The effect of incubation temperature on denitrification by isolated organism was studied by incubating NR media at different temperatures such as 20, 25, 30, 35 and 40°C. The NR media with the initial nitrate supplement of 300 ppm was inoculated with isolated strain and incubated in an incubator shaker at the above-mentioned temperatures. Fig. 3 presents the results of the effect of incubation temperature on nitrate removal by the isolate. This organism showed its maximum growth and nitrate removal efficiency at an incubation temperature of 30°C. At this temperature, biomass yield was 0.91g/L. At lower temperatures i.e., 20 and 25°C, the biomass yield obtained were 0.21 g/L and 0.23 g/L, respectively. The corresponding percentages of nitrate removals were found to be 47%, and 54%, respectively. At higher temperatures, i.e., 35°C and for 40°C, the percentage denitrification observed was 71% and 65% with corresponding biomass yield of 0.45 g/L and 0.52 g/L, respectively.
Figure 3 Effect of incubation temperature on percentage nitrate removal by an Enterobacter sp. NCCP-29
It was observed from the above study that the temperature is one of the important parameters for the growth of microorganism and nitrate removal. Temperature variation affects the folding of enzyme structure, which further alters the enzyme kinetics. At a certain temperature, the arrangement of the proper catalytic site will be formed and at this particular temperature, enzyme activity is maximum. The activity of the enzyme is affected by the temperature of the growth process. Wang et al., (1995) reported that at 30°C, the culture reduced nitrate optimally and Arrhenius-type expressions were also used in describing the effect of temperature on each of the parameter. Suet al., (2001) reported that at 30°C after 20 h, the concentration of nitrate decreased rapidly in the presence of Pseudomonas stutzeri.
Effect of agitation speed on denitrification
The effect of mixing on denitrification was studied by varying the agitation speed of the flasks containing the NR medium with an initial nitrate supplement of 300 mg/L. The flasks were inoculated with isolate culture and incubated at 30ºC at different agitation speeds at 0 rpm (static culture), 50 rpm, 100 rpm, 150 rpm, 200 rpm, and 250 rpm. The results on the effect of agitation speed on nitrate removal are presented in Fig. 4. It is evident from Fig.4 that with an increase in agitation speed, no significant change in nitrate removal until 200 rpm was observed. In the present study, a maximum of 98% nitrate removal was achieved in the culture kept at an agitation speed of 150 rpm in an incubator shaker. The corresponding biomass quantity produced was 0.98 g/L. At agitation speed of 250 rpm, a decrease in nitrate removal, as well as biomass growth, was observed. In this condition, the observed percentage denitrification was 56% and the amount of biomass produced was 0.57 g/L. At agitation speed of 250 rpm, the reduction in nitrate removal may be because of the death of cells due to rupturing at high agitation speed.
Figure 4 Effect of agitation speed on percentage nitrate removal by Enterobacter sp. NCCP-29
In the literature, the effect of agitation speed is discussed with reference to DO level in denitrification process. With the increase in agitation speed, there was a corresponding increase in oxygen transfer into the media, which enhances the dissolved oxygen (DO) level of the medium (Taylor et al., 2009; Liang et al., 2011). Liang et al., (2011) reported that 420 mg/L NO3– N was completely removed within 30 h at 160 rpm and a further increase in agitation speed has not much effect in the efficiency in nitrate removal.
Effect of different carbon sources on denitrification
Growth rate and metabolic process of a bacterium mainly depend on the carbon consumption and the type of carbon source. In the present study, different carbon sources were selected to study their effect on the denitrification efficiency of the isolate. The carbon sources included in this study were dextrose, ethanol, sodium acetate, sodium succinate and methanol. Fig. 5 presents the results of the effect of different carbon sources on denitrification by isolated strain. The maximum nitrate removal of 95% with the corresponding biomass yield of 0.98 g/L was obtained in the medium supplemented with sodium succinate as a carbon source. In the case of other carbon sources like ethanol and sodium acetate, a satisfactory nitrate removal was observed. The nitrate removal efficiency was considerably less when dextrose and methanol were used as carbon sources. In these cases, nitrate removal was 72% and 39%, respectively. The corresponding biomass quantities produced were 0.33 g/L and 0.19 g/L, respectively.
It was observed that maximum nitrate removal could be achieved in the cases of medium supplemented with sodium succinate, sodium acetate, and ethanol as carbon sources. Sodium succinate and sodium acetate are the intermediate molecules of the TCA cycle in the metabolic activity and hence, they can easily be utilized by bacteria as electron donors. The presence of these compounds enhances the microbial growth, which in turn resulted in more nitrate removal. Choice of the carbon source is very important to avoid this incomplete denitrification because of the toxicity for many bacteria at higher levels of nitrite accumulation. Acetate donates electrons closer to nitrate reductase, in the upstream region of the respiratory chain to either ubiquinone or cytochrome (Van Rijn et al., 1996), but acetate as carbon source stimulates denitrification in activated sludge samples (Eilersen et al., 1995). Methanol donates electrons closer to nitrite reductase (Van Rijn et al., 1996).
Figure 5 Effect of different carbon sources on nitrate removal by Enterobacter sp. NCCP-29
Effect of carbon to nitrogen ratio on denitrification
The optimization of carbon source concentration is very important in denitrification process. Denitrification rate will be reduced if the concentration of the carbon concentration becomes too low or high. In the present study, carbon to nitrogen ratios 3:1, 2:1 and 1:1 for the carbon sources of ethanol (a), sodium acetate (b) and for sodium succinate (c) were considered to prepare NR media, for inoculation with isolate. While preparing NR media, carbon concentration was only altered, and nitrate concentration was kept constant.
The results of the effect of carbon to nitrogen ratios on denitrification are presented in Fig. 6. It is evident from Fig. 8that, for all individual carbon sources, 3:1 ratio was found to be the optimum ratio for nitrate removal. At this ratio, the maximum nitrate removal of 98% was achieved for the medium containing sodium succinate. The corresponding biomass yield obtained was 1.29 g/L.
Figure 6 Effect of different carbon sources and carbon to nitrogen ratio on percentage nitrate removal by Enterobacter sp. NCCP-29
Nitrate removal is strongly dependent on the amount of carbon available (Elefsiniotis et al., 2004). Liang et al., (2011) reported at an insufficient carbon concentration, the electron flow is too low to provide enough energy for cell growth and causes accumulation of intermediate such as nitrite. When excess carbon substrates are added, it inhibits the growth of the bacteria, which may, in turn, delay the denitrification process. Wang et al., (2007) reported that the optimal C/N ratio was 5.5 – 6.0 for nearly complete denitrification by Pseudomonas sp.
Response Surface Methodology (RSM) studies
Central Composite Design (CCD) was used to optimize the concentration of three independent variables temperature, pH and C: N ratio (Table 2). The behavior of the system was explained with the quadratic equation
Where Y represents the response, βo is the interception coefficient, βi is coefficient of the linear effect, βii is the coefficient of quadratic effect and βij is the coefficient of interaction effect. Xi and Xj represent the coded independent variables. From the initial screening experiments by one factor at a time method, the factors such as temperature (A), pH (B) and C: N ratios (C) were found to have significant effect on percentage denitrification. Hence, these variables were chosen as the independent variables. To maximize the percentage denitrification, these variables were optimized using response surface methodology. Central Composite Design (CCD) was used to optimize the three independent variables. A 23 factorial design augmented by 6 axial points (α = 2) was implemented in 20 experiments where in the effect of each compound on denitrification rate was taken as a response. A total number of 20 experiments were conducted in duplicates to establish the relationship between independent variables (pH, Temperature and C:N ratio) and dependent variable/response (percentage denitrification). Details of the design have been mentioned in Table 3.
Table 2 Coded significant parameters and their actual levels for optimization by CCD
Table 3 Full factorial central composite design matrix and their observed response
|pH||Temperature||C:N Ratio||Y=% of removal (Actual)||Y=% of removal (Predicted)|
Experiments were carried out according to the design as given in Table 3. Experiments were conducted in random run order and tabulated in standard order. Actual and predicted values were compared. Actual values were the response obtained from the particular experimental run and predicted response were values determined by approximating functions employed by the model and are presented in Fig 7.
Figure 7 Comparison of experimental and predicted values for nitrate removal
Adequacy of the model is tested by determining the significant variables with ANOVA. ANOVA consists of statistical result which was tested by means of specified classification difference. It consists of classified and cross-classified statistical results analyzed by Fisher’s statistical test (F-test). F-value is defined as the ratio of the mean square of regression to the mean square residual or error (Anupam et al., 2011; Nejad et al., 2011). The coefficient of determination (R2) and the adjusted R2wasevaluated to test the global fit of the model. The value of R2 was found to be 93.8 % and hence the model did not explain only 6.2% of the total variability. The value of R2 (adj) was 88.35% deviates only by 6.2 % from the R2 value. This indicates that the model is highly significant and there is only a meager chance to include any insignificant terms in the model. The significance of individual coefficients and its interactions are determined by students T-test and P-value. T-value gives the ratio of estimated parameter effect to the estimated parameter standard deviation. If P-value is less than 0.05, then it is statistically significant at a confidence level of 98% (Anupam et al., 2011). P-value is used as a tool to check the significance of coefficients, a small P-value (<0.05) and a larger regression and T-value indicates the significant effect of the variables on the response variable (Nejad et al., 2011; Anupam et al., 2011). Square (P<0.001) and interaction (P<0.001) effects of all the three variables temperature, pH and C:N ratio had a significant influence on the percentage denitrification. Regression analysis of the data resulted in the polynomial equation which is given below. Regression equation in uncoded units
The positive coefficients of variables indicate that they have a synergistic effect on rate of denitrification whereas the negative coefficients of variables indicate an antagonistic effect on the rate of denitrification. The results of the ANOVA are given in Table 4. P-value of pH (A) is less than 0.05, also the P-value of AC is also less than 0.05. These are said to play a significant role in denitrification. These are said to be interacting, so the Response surface plots obtained are elliptical in nature (Fig.9 ) while other response surface plots obtained were circular in nature (Fig. 8 & 10).
Table 4 ANOVA test for response function of nitrate removal
|Source||Sum of squares||Df||Mean square||F Value||P Value|
|R2= 93.87% Adj R2=88.35% Predicted R2=49.86%|
Figure 8 Response surface plot for temperature and pH on percentage denitrification
Figure 9 Response surface plot for the effect C:N ratio and pH on percentage denitrification
Figure 10 Response surface plot for the effect C: N and temperature on percentage denitrification
Fig 8, 9, 10 represent the three dimensional response and contour plots for the parameters (pH, temperature and C:N ratio) which affect the denitrification efficiency. It can be seen from the figures that, the percentage denitrification decreased beyond the neutral range of pH, at very low and very high temperatures and at higher C:N ratio. Maximum percentage denitrification was obtained at a temperature of 30°C, pH 6.5 and C: N ratio of 3:1. These optimized values were validated by conducting experiments using these conditions, the percentage denitrification was found to be 98%. These results are in good agreement with the predicted results and confirmed adequacy of the model.
In this study, a potential novel denitrifying bacterial isolate was isolated from municipal waste water and identified as Enterobacter sp. NCCP-29. The bacterium showed the highest nitrate removal capability of 98% without nitrite accumulation. The bacterium, Enterobacter sp. NCCP-29 isolated in the present study was found be an efficient denitrifier in aerobic condition, 98 % of initial 300 ppm of nitrate was denitrified within 48hunder aerobic condition. It also showed significant nitrate removal at pH 6.5, 150 rpm agitation speed, the temperature of 30°C, and for sodium succinate as a carbon source and 3:1 as C:N ratio. Moreover, the denitrification activity of the bacterium was not much affected by the increase in agitation speed up to 200 rpm, which indicated the aerobic denitrification process of the bacterium. These results suggest that Enterobacter sp. NCCP-29may be a prospective candidate for aerobic wastewater treatment. The developed models with high correlation based on the experimental results of the CCD and RSM were useful to understand the direct effect of nitrate concentrations on the performance of the denitrification process. The optimum operational conditions in order to have a maximum denitrification rate with more than 98% removal of nitrate was achieved with pH 6.5, temperature 30°C and C:N of 3:1
ACKNOWLEDGMENT: The authors wish to thank, VGST (GRD 478), Government of Karnataka, Bangalore for funding the project and Management, Principal and Department of Chemical Engineering, SDMCET for the support and encouragement to carry out the work at the department. We also thank Department of Biotechnology Engineering, NMAMIT, Nitte for the kind support.
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