Mathematical Modelling of the Growth of Bacillus cereus Strain wwcp1on Malachite Green Dye

Yahuza, Salihu; Sabó, I

doi:10.54987/jobimb.v9i2.613

Cited by 5 publications

(4 citation statements)

References 32 publications

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“…The normality tests carried out shows that the model pass the normality tests with p >0.05 for all normality tests carried out [22]. Biodegradation of toxicants is just one of several situations aside from its common usage in food mcirobiology, where the Baranyi-Roberts model has proven useful for modeling microbial growth [30][31][32][33][34][35][36]. Important decolourisation rate parameters obtained in this study can be further utilized to gleam on the effect of substrate (Malachite Green) to the decolourization rate.…”

Section: Decolourization Kineticsmentioning

confidence: 69%

Modelling the Decolorization of Malachite Green by Staphylococcus aureus

Manogaran,

Gafar,

Azni

et al. 2022

Asian J Plant Biol

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Dyes plays an important role in our everyday life. From manufacturing plastics, paints, textile and even pills contain traces of dye used. With the ever-increasing demand for dye with growing world populations, the use of synthetic dyes has grown linearly. Bioremediation of dyes using microorganisms is on the rise. The ability to accurately predict the rate of bioremediation relies upon the gathering of the accurate rate of decolourisation, which is often inaccurately obtained by natural logarithm transformation of the decolourisation process over time. In this instance, a nonlinear regression of the curve needs to be carried out utilising available rate models. Hence, various primary models such as modified Logistic, modified Gompertz, modified logistics, modified Richards, modified Schnute, Baranyi-Roberts, Buchanan-3-phase, von Bertalanffy and the Huang models were utilized to fit the specific decolourisation rate. Several models failed to converge and was omitted and only Huang, Baranyi-Roberts, modified Gompertz, modified Richards and modified Logistics were able to model the data while other models failed to converge and were omitted. The best model based on statistical analysis was Baranyi Roberts with the highest value for Adjusted Coefficient of Determination and the lowest values for RMSE, AICc, HQC and BIC and the closest value to 1.0 for accuracy and bias factors. The Baranyi-Roberts fitted curve was found to conform to normality tests and is adequate to be used to fit the experimental data. The parameters obtained from this exercise can be utilized for further secondary modelling exercise to gleam information on how substrate (dye) affect the rate of decolourisation of the substrate.

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Section: Decolourization Kineticsmentioning

confidence: 69%

Modelling the Decolorization of Malachite Green by Staphylococcus aureus

Manogaran,

Gafar,

Azni

et al. 2022

Asian J Plant Biol

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“…The best model based on statistical analysis was Baranyi Roberts. The Baranyi-Roberts model has found numerous utility in modelling microorganisms growth in food and other applications including biodgredation of toxicants [22][23][24][25][26][27][28]. The Baranyi-Roberts fitted curve was found to conform to normality tests and is adequate to be used to fit the experimental data.…”

Section: Resultsmentioning

confidence: 97%

Degradation Kinetics of Basic violet 3 by Staphylococcus aureus

2022

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Synthetic dyes are abundantly used in recent years and mainly consumed in the textile, pharmaceutical, plastic and cosmetic industries. The release of toxic constituents from dyes give adverse effect on human health and marine life. In textile industries, large amount of dye discharged into the wastewater and eventually to the aquatic system are mainly came from the critical step of dyeing and finishing processes in textile. The be able to precisely forecast the rate of bioremediation, depends on the gathering of precise rate of decolourisation, and this can be inaccurately acquired by natural logarithm transformation of the decolourisation process over time. In cases like this, a nonlinear regression of the curve must be performed making use of accessible rate models. Consequently, numerous primary models for example modified Logistic, modified Gompertz, modified logistics, modified Richards, modified Schnute, Baranyi-Roberts, Buchanan-3-phase, von Bertalanffy and the Huang models were utilized to fit the specific decolourisation rate. Several models did not converge and was disregarded and only Huang, Baranyi-Roberts, modified Gompertz, modified Richards and modified Logistics could actually model the data. The very best model according to statistical analysis was Baranyi Roberts with the highest value for Adjusted Coefficient of Determination and the lowest values for RMSE, AICc, HQC and BIC and the closest value to 1.0 for accuracy and bias factors. The Baranyi-Roberts fitted curve was discovered to conform to normality tests and is satisfactory to be used to fit the experimental data. The parameters extracted from this exercise may be used for additional secondary modelling training to gleam information about how substrate (dye) impact the rate of decolourisation of the substrate

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“…The model takes into account environmental variables that can affect the development of microbes on harmful compounds, including temperature, pH, and the availability of nutrients. The capacity of the modified logistics model to represent the intricate dynamics of microbial development in the presence of harmful substances has contributed to its rising popularity [23][24][25][26][27][28][29]. To optimize bioremediation procedures, forecast microbial growth kinetics, and evaluate pollution impacts, researchers and environmental scientists utilize this model.…”

Section: Discussionmentioning

confidence: 99%

Primary Growth Models Investigation of Pseudomonas nitroreducens Growth on Octylphenol Polyethoxylates

Abubakar,

Magaji,

Othman

et al. 2023

J Environ Microbiol Toxicol

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This study evaluated the degradation of octylphenol polyethoxylates by Pseudomonas nitrore-ducens TX1 using secondary kinetics analysis. Nonlinear kinetic regression was employed through the utilization of curve-fitting software in order to fit the digitized growth degradation data. A comprehensive analysis was conducted using various statistical metrics including root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accu-racy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC), and Hannan-Quinn information criterion (HQC). The accuracy and statistical analysis of the kinetic models used showed that only the Huang, Baranyi Roborts, modified Gompertz, Bu-chanan-3-phase, modified Richards and Von Bertalanffy model fit the data, with modified Logis-tics having the best model with low RMSE and AICc values, highest adjusted R2 values, and Bias Factor and Accuracy Factor values closest to unity. The calculated values for the modified Logis-tics constant maximum growth rate (m), maximum growth value (A) and lag period (l), were 0.179 (h-1), 2.199 and 13.015 h, respectively. Growth curve of the bacterium on varying concen-trations of this compound can then be modelled using this model and the maximum growth rate value can be utilized for secondary modelling works further revealing important parameters.

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Mathematical Modelling of the Growth of Bacillus cereus Strain wwcp1on Malachite Green Dye

Cited by 5 publications

References 32 publications

Modelling the Decolorization of Malachite Green by Staphylococcus aureus

Modelling the Decolorization of Malachite Green by Staphylococcus aureus

Degradation Kinetics of Basic violet 3 by Staphylococcus aureus

Primary Growth Models Investigation of Pseudomonas nitroreducens Growth on Octylphenol Polyethoxylates

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