Optimization of Process Conditions for Effective  Degradation of Azo Blue Dye by Streptomyces DJP15

Pillai, Jai Shanker

doi:10.22207/jpam.11.4.14

Cited by 18 publications

(9 citation statements)

References 16 publications

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“…Web Plot Digitizer 2.5 [22] was used to digitise scanned plots into tables of data with sufficient precision before the data could be handled electronically. A previously published data [3], from Figures 2 which shows the degradation of Azo blue by streptomyces DJP15 at different concentrations were used in this study.…”

Section: Acquisition Of Datamentioning

confidence: 99%

“…Depending on the number of azo groups, azo dyes are classed as diazo dyes (brown 2, reactive brown 1, acid black 1, amido black), mono azo dyes (reactive yellow 201, acid orange 52, disperse blue 399), poly azo dyes (direct red 80) and tris azo dyes (direct black 19 and direct blue 78,) [2]. Azo dyes are characterized as reactive, dispersion, direct, cationic, anionic, and metalized azo dyes1 based on their application [3]. They're the only azo dyes that can bind covalently to cellulosic fibre and are widely used in the textile industry."…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Process Conditions for Effective Degradation of Azo Blue Dye by Streptomyces sp. DJP15: A Secondary Modelling Approac

Uba¹,

Abubakar²,

Ibrahim³

2021

Bull Environ Sci Sust Manage

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The well function of aquatic and soil organisms including terrestrial, as well as those of all other living things, can be jeopardized if dyes aren't properly treated, as their degradation might lead to carcinogenic chemicals. Complete mineralization of dye is the only option, and this can be done using microorganisms. The azo blue dye inhibitory effect to its biodegradation by Streptomyces DJP15 was modelled using several inhibition kinetic models such as Haldane, Monod, Luong, Aiba, Teissier-Edwards, Han-Levenspiel and Yano. The result shows that only the Luong model failed to fit the data. The rest of the models visually ft the data although data fitting is problematic with datapoints of less than 10, which the result in this work demonstrates where it is not easy to choose the best model where nearly all of the models fit the data in a similar manner. Resorting to statistical discriminatory function, the best model was Monod with the smallest RMSE and AICc values and the highest adjR2 values and values for AF and BF close to unity. However, Monod has only two parameters and is the most robust. The Monod’s parameters were maximum specific degradation rate of 0.431 (1/h) (95% confidence interval from 0.391 to 0.456) and concentration of substrate giving half maximal rate or Ks value of 0.0001 (mg/L) (95% C.I. from -0.01 to 12.12). The confidence interval value for the Ks value was very large indicating poor data quality. This should be an important consideration in future works where the data point number can be increased to improve model fitting exercise.

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Section: Acquisition Of Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Process Conditions for Effective Degradation of Azo Blue Dye by Streptomyces sp. DJP15: A Secondary Modelling Approac

Uba¹,

Abubakar²,

Ibrahim³

2021

Bull Environ Sci Sust Manage

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“…Kurade et al [49] have reviewed biodegradation of Disperse Red 54 with pregrown cell mass (24 h) of Brevibacillus laterosporus. Inoculum size of 1-5% v/v was tested using 3-day-old broth grown Streptomyces DJP15 for the degradation of Azo Blue dye [50]. Similarly, Shewanella decolorationis S12 was grown in 50 mL LB on shaker (150 rpm) at 30°C.…”

Section: Inoculum Preparationmentioning

confidence: 99%

“…AA09. Also, the decolorization studies of Azo Blue dye were carried out in starch-casein broth with Streptomyces DJP15 by Pillai [50], while Modi et al [31] carried out the decolorization assays for RR195 with pure culture and consortium using nutrient broth with and without glucose and in mineral salt medium.…”

Section: Physicochemical Parameters Influencing the Decolorization/ D...mentioning

confidence: 99%

Role of Various Physicochemical Factors in Enhancing Microbial Potential for Bioremediation of Synthetic Dyes

Birmole¹,

Samudravijay²

2022

Environmental Sciences

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The Indian dye industry is globally recognized for production and export of every known class of dye. On the less attractive side of industrialization, they contribute considerably to environmental pollution. The dyes discarded by industries persist in the environment due to extremely slow rate of biodegradation. Moreover, these dyes are toxic to insects, birds and terrestrial life. The dyes also hamper the light penetration in water bodies, severely affecting the the process of photosynthesis. In spite of the problems associated with synthetic dye disposal, they are industrially preferred due to their fundamental requirement in enhancing overall appearance of goods, quality and cost effectiveness. Several studies have reported physicochemical techniques for remediation of dye effluents. Most of these techniques pose significant drawbacks due to their high energy and cost requirements. The bioremediation approach, on the other hand, offers advantages of sustainable environmental friendly processes to detoxify and degrade dyes into harmless products. This chapter provides an overview of the potential role of various physicochemical factors such as pH, temperature, oxygen and nutrient concentration in optimum decolorization of dyes by naturally isolated microbial strains. In addition, the role of cosubstrates, electron acceptors and microbial enzymes are also discussed.

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“…and Aeromonas sp Reactive dyes: Novacron Orange FN-R, Novacron Brilliant Blue FN-R, Novacron Super Black G, Bezema Yellow S8-G and Bezema Red S2-B 37 °C, pH 7, Static conditions Monoculture: 0–90% Consortium 65%–90% [ 46 ] Alcaligenes faecalis AZ26, Bacillus cereus AZ27 and Bacillus sp Novacron Super Black G (NSB-G), 37 °C, pH 8.0, 200 mg/L 96 h, static conditions 90% [ 47 ] Pseudomonas aeruginosa (RS1) and Thiosphaera pantotropha ATCC 35512 Reactive Yellow 145 (RY145) 96 and 72 h [ 48 ] Staphylococcus sp . K2204 Remazol Brilliant Blue R (RBBR), 100 mg/L 37 °C, 12 h, static condition 100% [ 38 ] Bacillus megaterium KY848339.1 Acid Red (AR337) pH 7, 30 °C, 24 h, 500 mg/L 91% [ 49 ] M.yunnaenensis Methyl Orange pH 7, 30 °C, 100 mg/L 98% [ 50 ] Acinetobacter baumannii JC359 Reactive Black 5 (B-GDN), Reactive Red 120 (RP) and Reactive Blue 19 (RNB) PH7,7, 9 (RP, B-GDN and RNB) 37 °C, 48 h, 500 mg/L 98.8% for B-GDN, 96% for RP and 96.2% for RNB [ 51 ] Acinetobacter baumannii Reactive Red 198 pH 7, 37 °C, 72 h, 200 mg/L 96.20% [ 52 ] Bacillus stratosphericus SCA1007 Methyl Orange pH 7, 35 °C, 12 h,150 mg/L static conditions 100% [ 53 ] Streptomyces DJP15 Reactive Blue 222 pH 7, 35 °C, 48 h, 50 mg/L, static conditions [ 54 ] Bacillus pseudomycoides Acid Black 24 pH 7, 37 °C, 24 h, 40 mg/L 96% …”

Section: Introductionmentioning

confidence: 99%

Use of bacterial isolates in the treatment of textile dye wastewater: A review

Moyo

Makhanya

Zwane

2022

Heliyon

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Optimization of Process Conditions for Effective Degradation of Azo Blue Dye by Streptomyces DJP15

Cited by 18 publications

References 16 publications

Optimization of Process Conditions for Effective Degradation of Azo Blue Dye by Streptomyces sp. DJP15: A Secondary Modelling Approac

Optimization of Process Conditions for Effective Degradation of Azo Blue Dye by Streptomyces sp. DJP15: A Secondary Modelling Approac

Role of Various Physicochemical Factors in Enhancing Microbial Potential for Bioremediation of Synthetic Dyes

Use of bacterial isolates in the treatment of textile dye wastewater: A review

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