Modeling the Degradation Rate of the Azo Dye Congo Red by Acinetobacter baumannii
DOI:
https://doi.org/10.54987/bessm.v7i2.913Keywords:
Biodegradation, Congo red, Inhibition kinetics, Azo dye, Acinetobacter baumanniiAbstract
One of the challenges that face the textile industry is the release of effluents that are not wanted, most notably colors that do not degrade. This is one of the issues that plagues the industry. This is a concern since it affects the environment. Bioremediation using dye-degrading bacterium is appealing as bacterial metabolism converts hazardous dye to harmless carbon dioxide and water as byproducts. In this study, various secondary growth models such as Luong, Yano, Teissier-Edward, Aiba, Haldane, Monod, Han, and Levenspiel were employed. Following thorough statistical analyses such as root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), and accuracy factor (AF), the Luong model emerged as the most optimal choice. The half-saturation constant for maximal growth, maximal growth rate and maximal concentration of substrate tolerated and curve parameter that defines the steepness of the growth rate decline from the maximum rate symbolized by Ks, qmax and Sm, and n were 76.54 mg/L (95% C.I., 50.51 to 102.57), 0.240 per h (95% C.I., 0.219 to 0.270), 1135.37 mg/L (95% C.I., 1041.04 to 1229.72) and 5.34 (95% C.I., 2.36 to 8.32), respectively. These novel constants discovered during the modeling process could serve as valuable inputs for subsequent modeling pursuits.
References
Yaseen DA, Scholz M. Textile dye wastewater characteristics and constituents of synthetic effluents: a critical review. Vol. 16, International Journal of Environmental Science and Technology. Springer Berlin Heidelberg; 2019. 1193-1226 p.
Saratale, G.D. et al. Dye wastewater treatment: A critical review on current treatment technologies. Environ Sci Pollut Res. 2009;2(16):103-18.
Azanaw A, Birlie B, Teshome B, Jemberie M. Textile effluent treatment methods and eco-friendly resolution of textile wastewater. Case Stud Chem Environ Eng. 2022;6(May):100230.
Mahar, R.B. et al. 2012. Textile dyeing industry an environmental hazard. Nat Sci. 2012;04(01):22-6.
Sreedharan V, Saha P, Rao KVB. Dye degradation potential of Acinetobacter baumannii strain VITVB against commercial azo dyes. Bioremediation J. 2021;25(4):347-68.
Gusmanizar N, Halmi MIE, Rusnam M, Rahman MFA, Shukor MS, Azmi NS, et al. Isolation and characterization of a molybdenum-reducing and azo-dye decolorizing Serratia Marcescens strain neni-1 from indonesian soil. J Urban Environ Eng. 2016;10(1):113-23.
Sabo IA, Yahuza S, Shukor MY. Mathematical Modeling of the growth of Acinetobacter baumannii YNWH 226 on Azo dye Congo red. J Environ Bioremediation Toxicol. 2021;4(2):7-10.
Jung J, Park W. Acinetobacter species as model microorganisms in environmental microbiology: current state and perspectives. Appl Microbiol Biotechnol. 2015;99(6):2533-48.
Li R, Ning X an, Sun J, Wang Y, Liang J, Lin M, et al. Decolorization and biodegradation of the Congo red by Acinetobacter baumannii YNWH 226 and its polymer production's flocculation and dewatering potential. Bioresour Technol. 2015;194:233-9.
Ning XA, Yang C, Wang Y, Yang Z, Wang J, Li R. Decolorization and biodegradation of the azo dye Congo red by an isolated Acinetobacter baumannii YNWH 226. Biotechnol Bioprocess Eng. 2014;19(4):687-95.
Harumain ZAS, Mohamad MAN, Nordin NFH, Shukor MYA. Biodegradation of Petroleum Sludge by Methylobacterium sp. Strain ZASH. Trop Life Sci Res. 2023 Jul 21;34(2):197-222.
Manogaran M, Habib NMSA, Shukor MY, Yasid NA. Mathematical Modeling of Substrate Inhibition Kinetics of Staphylococcus aureus Growth on Basic Violet 3. Bioremediation Sci Technol Res. 2022 Dec 31;10(2):50-5.
Abubakar A, Gusmanizar N, Rusnam M, Syed MA, Shamaan NA, Shukor MY. Remodelling the Growth Inhibition Kinetics of Pseudomonas sp. Strain DrY Kertih on Acrylamide. Bioremediation Sci Technol Res. 2020 Dec 31;8(2):16-20.
Halmi MIE, Abdullah SRS, Johari WLW, Ali MSM, Shaharuddin NA, Khalid A, et al. Modelling the kinetics of hexavalent molybdenum (Mo6+) reduction by the Serratia sp. strain MIE2 in batch culture. Rendiconti Lincei. 2016 Dec 1;27(4):653-63.
Sabo IA, Yahuza S, Shukor MY. Molybdenum Blue Production from Serratia sp. strain DRY5: Secondary Modeling. Bioremediation Sci Technol Res. 2021 Dec 31;9(2):21-4.
Najim AA, Ismail ZZ, Hummadi KK. Biodegradation potential of sodium dodecyl sulphate (SDS) by mixed cells in domestic and non-domestic actual wastewaters: Experimental and kinetic studies. Biochem Eng J. 2022 Mar 1;180:108374.
Zhao H, Zhu J, Liu S, Zhou X. Kinetics study of nicosulfuron degradation by a Pseudomonas nitroreducens strain NSA02. Biodegradation. 2018;29(3):271-83.
Min J, Wang J, Chen W, Hu X. Biodegradation of 2-chloro-4-nitrophenol via a hydroxyquinol pathway by a Gram-negative bacterium, Cupriavidus sp. strain CNP-8. AMB Express. 2018 Mar 20;8(1):43.
Wen ZD, Gao DW, Wu WM. Biodegradation and kinetic analysis of phthalates by an Arthrobacter strain isolated from constructed wetland soil. Appl Microbiol Biotechnol. 2014;98(10):4683-90.
Basak SP, Sarkar P, Pal P. Isolation and characterization of phenol utilizing bacteria from industrial effluent-contaminated soil and kinetic evaluation of their biodegradation potential. J Environ Sci Health - Part ToxicHazardous Subst Environ Eng. 2014;49(1):67-77.
Rohatgi A. WebPlotDigitizer User Manual 4.3. HttparohatgiinfoWebPlotDigitizerapp Accessed June 2 2014. 2020;1-17.
Yahuza S, Dan-iya BI, Sabo IA. Modelling the Growth of Enterobacter sp . on Polyethylene. J Biochem Microbiol Biotechnol. 2020;8(1):42-6.
Sabo IA, Yahuza S, Shukor MY. Molybdenum Blue Production from Serratia sp. strain DRY5: Secondary Modeling. Bioremediation Sci Technol Res. 2021;9(2):21-4.
Wayman M, Tseng MC. Inhibition?threshold substrate concentrations. Biotechnol Bioeng. 1976;18(3):383-7.
Akaike H. Making statistical thinking more productive. Ann Inst Stat Math. 2010;62(1):3-9.
Kass RE, Raftery AE. Bayes Factors. J Am Stat Assoc. 1995 Jun 1;90(430):773-95.
Burnham KP, Anderson DR. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. Springer Science & Business Media; 2002. 528 p.
Ross T, McMeekin TA. Predictive microbiology. Int J Food Microbiol. 1994;23(3-4):241-64.
Zhou K, George SM, Métris A, Li PL, Baranyi J. Lag phase of Salmonella enterica under osmotic stress conditions. Appl Environ Microbiol. 2011;77(5):1758-62.
Zhao J, Gao J, Chen F, Ren F, Dai R, Liu Y, et al. Modeling and predicting the effect of temperature on the growth of Proteus mirabilis in chicken. J Microbiol Methods. 2014;99(1):38-43.
Velugoti PR, Bohra LK, Juneja VK, Huang L, Wesseling AL, Subbiah J, et al. Dynamic model for predicting growth of Salmonella spp. in ground sterile pork. Food Microbiol. 2011;28(4):796-803.
McElroy DM, Jaykus LA, Foegeding PM. Validation and analysis of modeled predictions of growth of Bacillus cereus spores in boiled rice. J Food Prot. 2000;63(2):268-72.
Kowalik J, Lobacz A, Tarczynska AS, Ziajka S. Graphie validation of growth models for Listeria monocytogenes in milk during storage. Milchwissenschaft. 2012;67(1):38-42.
Jung SH, Park SJ, Chun HH, Song KB. Effects of combined treatment of aqueous chlorine dioxide and fumaric acid on the microbial growth in fresh-cut paprika (capsicum annuum L.). J Appl Biol Chem. 2014;57(1):83-7.
Huang L, Hwang CA, Phillips J. Evaluating the Effect of Temperature on Microbial Growth Rate-The Ratkowsky and a B?lehrádek-Type Models. J Food Sci. 2011;76(8):M547-57.
Monod J. The Growth of Bacterial Cultures. Annu Rev Microbiol. 1949;3(1):371-94.
Boon B, Laudelout H. Kinetics of nitrite oxidation by Nitrobacter winogradskyi. Biochem J. 1962;85:440-7.
Teissier G. Growth of bacterial populations and the available substrate concentration. Rev Sci Instrum. 1942;3208:209-14.
Aiba S, Shoda M, Nagatani M. Kinetics of product inhibition in alcohol fermentation. Biotechnol Bioeng. 1968 Nov 1;10(6):845-64.
Yano T, Koga S. Dynamic behavior of the chemostat subject to substrate inhibition. Biotechnol Bioeng. 1969 Mar 1;11(2):139-53.
Han K, Levenspiel O. Extended Monod kinetics for substrate, product, and cell inhibition. Biotechnol Bioeng. 1988;32(4):430-7.
Luong JHT. Generalization of monod kinetics for analysis of growth data with substrate inhibition. Biotechnol Bioeng. 1987;29(2):242-8.
Moser A. Kinetics of batch fermentations. In: Rehm HJ, Reed G, editors. Biotechnology. VCH Verlagsgesellschaft mbH, Weinheim; 1985. p. 243-83.
Webb JLeyden. Enzyme and metabolic inhibitors [Internet]. New York: Academic Press; 1963. 984 p. Available from: https://www.biodiversitylibrary.org/bibliography/7320
Hinshelwood CN. The chemical kinetics of the bacterial cell. Clarendon Press, Gloucestershire, UK; 1946.
Mulchandani A, Luong JHT, Groom C. Substrate inhibition kinetics for microbial growth and synthesis of poly-?-hydroxybutyric acid by Alcaligenes eutrophus ATCC 17697. Appl Microbiol Biotechnol. 1989;30(1):11-7.
Chen G, An X, Feng L, Xia X, Zhang Q. Genome and transcriptome analysis of a newly isolated azo dye degrading thermophilic strain Anoxybacillus sp. Ecotoxicol Environ Saf. 2020 Oct 15;203:111047.
Gopinath KP, Asan Meera Sahib H, Muthukumar K, Velan M. Improved biodegradation of Congored by using Bacillus sp. Bioresour Technol. 2009 Jan 1;100(2):670-5.
Wang ZW, Liang JS, Liang Y. Decolorization of Reactive Black 5 by a newly isolated bacterium Bacillus sp. YZU1. Int Biodeterior Biodegrad. 2013 Jan 1;76:41-8.
Song XY, Liu FJ, Zhou HB, Yang HL. Biodegradation of Acid Scarlet 3R by a New Salt-tolerant Strain Alcaligenes faecalis LJ-3: Character, Enzyme and Kinetics Analysis. Chem Biochem Eng Q. 2018 Oct 13;32(3):371-81.
Uba G, Abubakar A, Ibrahim S. Optimization of Process Conditions for Effective Degradation of Azo Blue Dye by Streptomyces sp. DJP15: A Secondary Modelling Approac. Bull Environ Sci Sustain Manag. 2021 Dec 31;5(2):28-32.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Bulletin of Environmental Science and Sustainable Management (e-ISSN 2716-5353)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).