Response surface modeling of bioremediation of acid black 52 dye using Aspergillus flavus

A worldwide environmental concern has been invited over the past few decades due to the tremendous increase in industrialization and urbanization. Industries such as textile, mining, steel electroplating, etc. generate aqueous effluents containing relatively high levels of synthetic dyes and heavy metals (Madhavan et al. 2009; Suditu et al. 2013). Chromium complex dyes are generally used in leather and nylon industries (Aksu & Balibek 2010). Hexavalent chromium has a more toxic effect on human beings than trivalent chromium. Exposure to hexavalent chromium may cause hemorrhage, epigastric pain, dermatitis, bronchitis, severe diarrhea, nausea, and also may cause cancer in the digestive tract and lungs (Pillai et al. 2013). Trivalent chromium gets absorbed in the digestive tract and develops harmful compounds with proteins, which affect the health of humans and animals (Carmona et al. 2012). Due to the toxicity of both chromium and dyes, the effluents from these industries need to be treated prior to their discharge. The acceptable range for trivalent chromium and hexavalent chromium in potable water is 0.1 mg/L as per the rule of the environmental protection agency (Panayotova et al. 2007). Different techniques for treatment of wastewater include ion-exchange, oxidation, precipitation, evaporation, electroplating and membrane filtration (Banerjee & Dastidar 2005). However, application of such techniques is limited because of technical or economic constraints (Meunier et al. 2003). Extensive studies have been reported on bioremediation of dyes and metals using various micro-organisms such as bacteria, fungi and algae (Mehta & Gaur 2001). Micro-organisms acquire toxicity resistance via different processes such as transport across the cell membrane, biosorption to cell walls and oxidation–reduction reactions, entrapment in extracellular capsules, precipitation, complexation, etc. (Macaskie & Dean 1989; Avery & Tobin 1993). Fungal strains have been reported to remove and degrade various pollutants efficiently due to the high biomass yield and presence of different oxidoreductive enzymes (Anastasi et al. 2010). The optimization of process parameters for bioremediation of pollutants by conventional batch process is time consuming and requires many experimental runs. These problems are minimized by optimizing the process parameters together by statistical methods such as Taguchi or response surface methods (Preetha & Viruthagiri 2007; Pundir et al. 2016).

However, very little information in literature is available on simultaneous removal of chromium and color from a synthetic solution of chromium complex dye. Kalpana et al. (2011) reported color removal of a chromium complex dye (Isolan Dark Blue) using growing Irpex lacteus. Aspergillus tamarii isolated from the sludge of a textile industry in the laboratory of the present authors was reported to remove trivalent chromium complex dye (acid black 52) (Ghosh et al. 2016a). Previously, Aspergillus flavus was isolated from an electroplating effluent, which was reported to remove different heavy metals and dyes separately from aqueous solutions (Ranjusha et al. 2010; Pundir et al. 2016). In the present study, an attempt was made to compare the efficiency of Aspergillus flavus with that of Aspergillus tamarii for simultaneous removal of color and chromium from the solution of acid black 52 dye in a batch bioreactor. Response surface modeling was performed to optimize the parameters for color removal from an aqueous solution of acid black 52 dye using Aspergillus flavus.

Acid black 52 was collected from a local textile industry at Delhi National Capital Region (India). This dye was water soluble and was used without any purification in the present study. The dye was mainly complexed with trivalent chromium. Copper and iron were present in the dye molecules as impurities (Ghosh et al. 2016a). The concentrations of chromium and copper were observed to be 4.1 and 0.091 mg/L, respectively, using an atomic absorption spectrophotometer (AAS) in a 100 mg/L acid black 52 dye solution (Ghosh et al. 2016a, 2016b).

The fungal strain Aspergillus flavus, isolated previously in the laboratory from an effluent of an electroplating industry, was used to remove heavy metals such as copper, zinc, nickel and remazol black b, methylene blue, acid orange 80 in separate studies (Ranjusha et al. 2010; Kumar et al. 2014; Ghosh et al. 2016c; Pundir et al. 2016). A growth medium containing glucose: 10.00 g/L; K₂HPO₄: 0.5 g/L; NaCl: 1 g/L; MgSO₄: 0.1 g/L; NH₄NO₃: 0.5 g/L and yeast extract: 5.0 g/L was prepared and the required quantity of acid black 52 dye was added to the media, which was autoclaved and inoculated with Aspergillus flavus (Ranjusha et al. 2010). The pH for maximum growth of Aspergillus flavus in the absence of dye was reported to be 4.5, which was maintained in the batch experiments.

The sterile growth medium (100 mL) containing acid black 52 dye of different initial concentrations (100–2,000 mg/L) was inoculated with the actively growing cells of Aspergillus flavus in 250 mL conical flasks. This was incubated aerobically at 27 °C under shaking condition (110 rpm) in an Orbitek shaker for up to 50 hours. The samples were collected from the conical flasks after set time intervals and centrifuged at 4,000 rpm (Eltek centrifuge, Model no. TC 4100F). The concentrations of metals (copper and chromium) and dye were determined using AAS and a UV-visible spectrophotometer, respectively. The biomass collected after centrifugation was dried at 60 °C in a hot air oven (Ambassador, India) and estimated gravimetrically to determine the biomass concentration. The dried fungal biomass after bioremediation of dye (100 mg/L) was also preserved in an air-tight glass container for scanning electron microscopic (SEM) and energy dispersive X-ray (EDX) analyses.

In the present study, optimization of process parameters was performed to treat a known synthetic dye solution for academic purposes, whereas optimization of the process parameters to treat the actual effluent for practical applications is quite difficult. Statistically based response surface modeling (RSM) was performed to find out the optimum conditions of process parameters for maximum color removal from the acid black 52 dye solution. Different RSM models such as the Box-Behnken method and central composite design (CCD) are available. The advantage of CCD is that a high range prediction can be possible within and outside the design range as compared to the Box-Behnken method, which can be applied within the design range only (Ghosh et al. 2015).

The total chromium was determined using AAS (Perkin-Elmer AAnalyst 200), whereas the hexavalent chromium was determined using a UV-Vis spectrophotometer 117 (Systronics). The amount of trivalent chromium was determined by subtracting the amount of hexavalent chromium from the amount of total chromium. The UV-Vis spectral analysis of the acid black 52 dye in the wavelength range of 200–900 nm before bioremediation indicated maximum absorbance at 569.6 nm. SEM analysis was conducted using a ZEISS EVO Series Scanning Electron Microscope Model EVO 50 to investigate the changes in surface morphology of the fungal biomass after bioremediation of acid black 52 dye. EDX analysis was performed to determine the presence of multi-metal in the biomass after bioremediation of acid black 52 dye, using the Bruker-AXS EDX System. Initially, the biomass samples were kept on a stainless steel stub and then under a vacuum condition gold and carbon were plated respectively for SEM and EDX analyses.

Bioremediation experiments were carried out to determine the color and chromium removal during the growth period of the fungal strain at initial concentrations of dye ranging from 100 to 2,000 mg/L. No growth of the fungi was observed at 3,000 mg/L initial dye concentration. Aspergillus flavus was able to grow and remove color and chromium up to 2,000 mg/L dye concentration. It was expected that the simultaneous removal of chromium along with dye would take place under growing conditions of Aspergillus sp.

The EDX micrograph (Figure 3(c)) shows that chromium was absent in the fungal biomass before bioremediation. The EDX micrograph (Figure 3(d)) shows the presence of chromium, copper and iron in the fungal biomass after bioremediation of acid black 52.

Table 2 shows the comparison of color and chromium removal from solutions of dye and chromium using different growing Aspergillus sp. In general, higher removal of color was observed from the dye solution which was not complexed with chromium. Similarly, higher removal of chromium was observed when it was not complexed with dye. The lower values of color and chromium removal were obtained in the present study due to the complexity of the structure of acid black 52 dye.

Twenty experiments were performed under different combinations of dye concentration, pH and time as designed by RSM for optimization study. Removal of color obtained in bioremediation experiments using the CCD matrix are presented in Table 3.

The 3-D contour plots of response surfaces were drawn to find out the combined effect of different parameters on percentage color removal of acid black 52 dye. The analysis of variance (ANOVA) is believed to be practicable to test statistical significance of response surface model.

The ANOVA results (Table 4) of the quadratic model indicate that the model was highly significant, as indicated from the Fisher's F value (higher F value, i.e. 300.31) with a low probability value (P < 0.0001). The ‘Lack of fit F value’ of 2.73 was insignificant, which proves that the model is fit for the study (Ghosh & Saha, 2012). The value (0.9963) of the determination coefficient (R²) expresses that more than 99% of the data deviation can be explained by the model. The predicted correlation coefficient (predicted R² = 0.9771) also shows good agreement with the adjusted correlation coefficient (adjusted R² = 0.9930).

Table 5 shows the regression analysis of color removal by using CCD. In this model, the P values of A, B, C, AB, BC, A², B² and C² express that the terms are significant.

With increasing pH up to 4.75, color removal was observed to increase. At pH above 4.75, color removal was observed to decrease. Maximum removal of color was observed at pH 4.75. The solution pH value affects the charge of the functional groups on the cell wall. Initially, at higher acidic pH, competition occurs between positively charged hydrogen ions and acid black 52 dye molecules for free binding sites on the cell wall. The concentration of hydrogen ions decreases in the solution with increasing pH, which favors binding of dye molecules to the free cell wall groups. Color removal decreased with increasing dye concentrations above 200 mg/L. Maximum removal of color (76.52%) was observed at dye concentration: 200 mg/L, pH: 4.75 and time: 50 hours.

The confirmatory experiment was performed under the optimum conditions (dye concentration: 200 mg/L, pH: 4.75 and time: 50 hours) as suggested by the RSM model. Under the optimum conditions, removal of color was up to 75.80%, and the RSM predictive value was 76.52%, with a marginal deviation.

Aspergillus flavus was found to be efficient in removing color and chromium from a synthetic solution of acid black 52 dye under growing conditions. The specific removal of dye and chromium was increased from 19.51 to 350 mg/g and from 0.84 to 22.55 mg/g, respectively with increasing dye concentrations from 100–2,000 mg/L at pH 4.5 in 50 hours in a batch bioreactor. Based on response surface modeling, the optimum conditions for 76.52% color removal were observed as: pH 4.75, initial dye concentration 200 mg/L and time 50 hours. The SEM analysis indicated distortion of the cell surface after bioremediation of acid black 52, and the EDX analysis showed chromium uptake by the fungal cell. Aspergillus flavus, therefore, seems to have the potential to biologically treat effluent contaminated with dye as well as chromium.