Molybdenum Blue Production from Serratia sp. strain DRY5: Secondary Modeling

2021 ◽  
Vol 9 (2) ◽  
pp. 21-24
Author(s):  
Ibrahim Alhaji Sabo ◽  
Salihu Yahuza ◽  
Mohd Yunus Shukor
Keyword(s):  
Confidence Interval ◽  
Degradation Rate ◽  
Growth Models ◽  
Coefficient Of Determination ◽  
Specific Substrate ◽  
The Novel ◽  
Monod Model ◽  
Molybdenum Blue ◽  
Kinetic Growth ◽  
Bias Factor

In this work, kinetic growth models such as Luong, Yano, Teissier-Edward, Aiba, Haldane, Monod, Han and Levenspiel were used to model molybdenum blue production from Serratia sp. strain DRY5. Based on statistical analyses such as root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), and accuracy factor (AF), the Monod model was chosen as the best. The calculated values for the monod constants qmax (the maximum specific substrate degradation rate (h−1), and Ks (concentration of substrate at the half maximal degradation rate (mg/L)) were found to be 3.86 (95% confidence interval of 2.29 to 5.43), and 43.41 (95% confidence interval of 12.36 to 74.46) respectively. The novel constants discovered during the modelling exercise could be used in further secondary modelling.

scholarly journals Isothermal Modelling of the Adsorption of Cibacron Blue onto Bean Peel

2021 ◽  
Vol 3 (2) ◽  
pp. 20-24
Author(s):  
Mohd Yunus Shukor
Keyword(s):  
Confidence Interval ◽  
Freundlich Isotherm ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Maximum Adsorption Capacity ◽  
Cibacron Blue ◽  
A Value ◽  
Bias Factor ◽  
Nonlinear Regression Method ◽  
Parameter Values

Biosorption is a sort of sorption technology in which the sorbent is a substance that is biologically sourced. In today's world, biosorption is seen as a simple, inexpensive, and ecologically friendly way for removing pollutants from the environment. One of the branches of bioremediation that is utilised to decrease environmental pollution in the context of minimising improper textile waste disposal is this method. The sorption isotherm of Cibacron Blue onto bean peel were analyzed using ten models—Henry, Langmuir, Dubinin-Radushkevich, Freundlich, BET, Toth, Sips, Fritz-Schlunder IV, Baudu and Fritz-Schlunder V, and fitted using non-linear regression. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), BIC and HQC showed that the Freundlich model was the best model in terms of overall best criteria. The calculated evidence ratio was 8 with an AICc probability value of 0.89 indicating that the best model was at least 8 times better than the nearest best model, which was Sips. The calculated Freundlich parameters KF (Freundlich isotherm constant) and nF (Freundlich exponent) were 5.369 (L/g) (95% confidence interval from 4.359 to 6.379) and 3.125 (95% confidence interval from 2.717 to 3.533). The Langmuir constant was utilized to calculate the maximum adsorption capacity QmL (mg/g) which gave a value of 27.83 mg/g (95% confidence interval from 23.69 to 31.98). The nonlinear regression method allows for the parameter values to be represented in the 95% confidence interval range which can better allow comparison with published results.

scholarly journals Kinetic Analysis of the Adsorption of Ethyl Violet onto Graphene Oxide Sheets Integrated with Gold Nanoparticles

2021 ◽  
Vol 9 (2) ◽  
pp. 35-39
Author(s):  
Bilal Ibrahim Dan-Iya ◽  
Ain Aqilah Basirun ◽  
Mohd Yunus Shukor
Keyword(s):  
Graphene Oxide ◽  
Confidence Interval ◽  
Information Criterion ◽  
Cost Effective ◽  
Order Rate Constant ◽  
Coefficient Of Determination ◽  
Order Model ◽  
Ethyl Violet ◽  
Bias Factor ◽  
Pseudo Second Order

An example of biosorption is when the sorbent is made from a biodegradable material. Biosorption is now being seen as a simple, cost-effective, and environmentally acceptable alternative to traditional pollution treatment methods. Bioremediation is one of the branches of bioremediation that is used to minimise pollution in the context of incorrect dye waste disposal. The sorption isotherm of Ethyl Violet onto graphene oxide were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC) that showed that the pseudo-second-order model was the best which was the same finding from the original published work. The calculated evidence ratio was 11 with an AICc probability value of 0.91 indicating that the best model was at least 11 times better than the nearest best model, which was pseudo-1st. Further analysis is needed to provide proof for the mechanism usually tied to this kinetic. Nonlinear regression analysis using the pseudo-2nd order model for the highest concentration tested, which was 10 mM, gave values of equilibrium sorption capacity qe of 30.928 mg/g (95% confidence interval from 29.328 to 32.527) and a value of the pseudo-2nd-order rate constant, k2 of 0.020 (95% confidence interval from 0.011 to 0.028).

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

2021 ◽  
Vol 9 (2) ◽  
pp. 25-29
Author(s):  
Salihu Yahuza ◽  
Ibrahim Alhaji Sabo
Keyword(s):  
Confidence Interval ◽  
Bacillus Cereus ◽  
Malachite Green ◽  
Bacterial Growth ◽  
Growth Models ◽  
Von Bertalanffy ◽  
Bacterial Growth Rate ◽  
Von Bertalanffy Model ◽  
Malachite Green Dye ◽  
Bias Factor

In this paper, various growth models such as Von Bertalanffy, Huang, Baranyi-Roberts, Modified Gompertz, Buchnam-3-phase, Modified-Richards and Modified-Logistics, were presented in fitting and evaluating the growth of Bacillus cereus wwcp1 on Malachite green dye. The Von Bertalanffy model was found to be the best model with the lowest RMSE and highest R2 values. The Accuracy and Bias factor values were near unity (1.0). The von Bertalanffy parameters such as A (lower asymptote bacterial growth), μ (bacterial growth rate) and k (curve fitting parameter) were found to be 2.757 (95% confidence interval from 2.131 to 3.382 ), 0.287 (95% confidence interval from 0.244 to 0.329) and 4.323 (95% confidence interval from 4.285 to 4.361) respectively.

scholarly journals Isothermal Modelling of the Adsorption of Chromium onto Calcium Alginate Nanoparticles

2021 ◽  
Vol 9 (2) ◽  
pp. 1-7
Author(s):  
Bilal Ibrahim Dan-Iya ◽  
Mohd Yunus Shukor
Keyword(s):  
Confidence Interval ◽  
Calcium Alginate ◽  
Information Criterion ◽  
Industrial Applications ◽  
Coefficient Of Determination ◽  
Refractory Materials ◽  
Bias Factor ◽  
Nonlinear Regression Method ◽  
Parameter Values ◽  
Better Than

Because of its extensive usage in industrial applications such as leather tanning, metallurgy, electroplating, and refractory materials, chromium is one of the most dangerous trace elements introduced into surface and ground waters. The sorption isotherm of chromium sorption onto calcium alginate nanoparticles were analyzed using ten models—Henry, Langmuir, Dubinin-Radushkevich, Freundlich, BET, Toth, Sips, Fritz-Schlunder IV, Baudu and Fritz-Schlunder V, and fitted using non-linear regression. Only the Toth and Fritz-Schlunder V models were unable to fit the data. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), BIC and HQC showed that the Langmuir model was the best model in terms of overall best criteria. The calculated evidence ratio was 7 with an AICc probability value of 0.87 indicating that the best model was at least 7 times better than the nearest best model, which was Freundlich. The calculated Langmuir parameters qmL value of 79.174 mg/g (95% confidence interval from 50.702 to 107.646) and bL value of 0.332 L/mg (95% confidence interval from 0.294 to 0.371) is not much different from the linearized published work for the qmL value of 145 mg/g but lower than the bL value of 0.34 L/mg. The nonlinear regression method allows for the parameter values to be represented in the 95% confidence interval range which can better allow comparison with published results.

scholarly journals Kinetic Analysis of the Adsorption of Malachite Green onto Graphene Oxide Sheets Integrated with Gold Nanoparticles

2021 ◽  
Vol 9 (2) ◽  
pp. 48-52
Author(s):  
Ibrahim Alhaji Sabo ◽  
Salihu Yahuza ◽  
Bilal Ibrahim Dan-Iya ◽  
Abdussamad Abubakar
Keyword(s):  
Graphene Oxide ◽  
Confidence Interval ◽  
Malachite Green ◽  
Information Criterion ◽  
Cost Effective ◽  
Order Rate Constant ◽  
Visual Observation ◽  
Coefficient Of Determination ◽  
Textile Dye ◽  
Bias Factor

Malachite green is extensively used in the textile dye industry and in agriculture as fish pests’ pesticide. Biosorption is a type of sorption technique that uses a biological sorbent. As of now, biosorption is viewed as a simple and cost-effective process that might be used as an alternative to traditional pollution treatment methods. Bioremediation is one of the branches of bioremediation that is used to minimise pollution in the context of incorrect textile waste disposal. The sorption isotherm of Malachite Green onto graphene oxide were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. The Elovich model was the poorest in fitting the curve based on visual observation and the best was pseudo-2nd order based on statistical analysis such as root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC). Nonlinear regression analysis using the pseudo-2nd order model gave values of equilibrium sorption capacity qe of 6.164 mg/g (95% confidence interval from 5.918 to 6.410) and a value of the pseudo-2nd-order rate constant, k2 of 0.034 (95% confidence interval from 0.024 to 0.045). Further analysis is needed to provide proof for the chemisorption mechanism usually tied to this kinetic.

scholarly journals Biosensing Membrane Base on Ferulic Acid and Glucose Oxidase for an Amperometric Glucose Biosensor

Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3757
Author(s):  
Gabriela Valdés-Ramírez ◽  
Laura Galicia
Keyword(s):  
Ferulic Acid ◽  
Glucose Oxidase ◽  
Aqueous Media ◽  
Glucose Biosensor ◽  
Single Step ◽  
Coefficient Of Determination ◽  
The Novel ◽  
Carbon Paste ◽  
Glucose Response ◽  
Glucose Biosensors

A biosensing membrane base on ferulic acid and glucose oxidase is synthesized onto a carbon paste electrode by electropolymerization via cyclic voltammetry in aqueous media at neutral pH at a single step. The developed biosensors exhibit a linear response from 0.082 to 34 mM glucose concentration, with a coefficient of determination R2 equal to 0.997. The biosensors display a sensitivity of 1.1 μAmM−1 cm−2, a detection limit of 0.025 mM, and 0.082 mM as glucose quantification limit. The studies reveal stable, repeatable, and reproducible biosensors response. The results indicate that the novel poly-ferulic acid membrane synthesized by electropolymerization is a promising method for glucose oxidase immobilization towards the development of glucose biosensors. The developed glucose biosensors exhibit a broader linear glucose response than other polymer-based glucose biosensors.

Dynamic Predictive Model for Growth of Bacillus cereus from Spores in Cooked Beans

2017 ◽  
Vol 81 (2) ◽  
pp. 308-315 ◽  
Author(s):  
Vijay K. Juneja ◽  
Abhinav Mishra ◽  
Abani K. Pradhan
Keyword(s):  
Bacillus Cereus ◽  
Growth Rates ◽  
Linear Models ◽  
Growth Models ◽  
Maximum Growth ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Growth Data ◽  
Three Phase ◽  
Primary Model

ABSTRACT Kinetic growth data for Bacillus cereus grown from spores were collected in cooked beans under several isothermal conditions (10 to 49°C). Samples were inoculated with approximately 2 log CFU/g heat-shocked (80°C for 10 min) spores and stored at isothermal temperatures. B. cereus populations were determined at appropriate intervals by plating on mannitol–egg yolk–polymyxin agar and incubating at 30°C for 24 h. Data were fitted into Baranyi, Huang, modified Gompertz, and three-phase linear primary growth models. All four models were fitted to the experimental growth data collected at 13 to 46°C. Performances of these models were evaluated based on accuracy and bias factors, the coefficient of determination (R2), and the root mean square error. Based on these criteria, the Baranyi model best described the growth data, followed by the Huang, modified Gompertz, and three-phase linear models. The maximum growth rates of each primary model were fitted as a function of temperature using the modified Ratkowsky model. The high R2 values (0.95 to 0.98) indicate that the modified Ratkowsky model can be used to describe the effect of temperature on the growth rates for all four primary models. The acceptable prediction zone (APZ) approach also was used for validation of the model with observed data collected during single and two-step dynamic cooling temperature protocols. When the predictions using the Baranyi model were compared with the observed data using the APZ analysis, all 24 observations for the exponential single rate cooling were within the APZ, which was set between −0.5 and 1 log CFU/g; 26 of 28 predictions for the two-step cooling profiles also were within the APZ limits. The developed dynamic model can be used to predict potential B. cereus growth from spores in beans under various temperature conditions or during extended chilling of cooked beans.

Introducing a sinusoidal equation to describe lactation curves for cumulative milk yield and composition in Holstein cows

2020 ◽  
Vol 87 (2) ◽  
pp. 220-225
Author(s):  
Navid Ghavi Hossein-Zadeh ◽  
Hassan Darmani Kuhi ◽  
James France ◽  
Secundino López
Keyword(s):  
Linear Model ◽  
Milk Yield ◽  
Milk Fat ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Information Criterion ◽  
Holstein Cows ◽  
Coefficient Of Determination ◽  
Production Traits ◽  
Lactation Curve

AbstractThe aim of the work reported here was to investigate the appropriateness of a sinusoidal function by applying it to model the cumulative lactation curves for milk yield and composition in primiparous Holstein cows, and to compare it with three conventional growth models (linear, Richards and Morgan). Data used in this study were 911 144 test-day records for milk, fat and protein yields, which were recorded on 834 dairy herds from 2000 to 2011 by the Animal Breeding Centre and Promotion of Animal Products of Iran. Each function was fitted to the test-day production records using appropriate procedures in SAS (PROC REG for the linear model and PROC NLIN for the Richards, Morgan and sinusoidal equations) and the parameters were estimated. The models were tested for goodness of fit using adjusted coefficient of determination $\lpar {R_{{\rm adj}}^2 } \rpar $, root mean square error (RMSE), Akaike's information criterion (AIC) and the Bayesian information criterion (BIC). $R_{{\rm adj}}^2 $ values were generally high (>0.999), implying suitable fits to the data, and showed little differences among the models for cumulative yields. The sinusoidal equation provided the lowest values of RMSE, AIC and BIC, and therefore the best fit to the lactation curve for cumulative milk, fat and protein yields. The linear model gave the poorest fit to the cumulative lactation curve for all production traits. The current results show that classical growth functions can be fitted accurately to cumulative lactation curves for production traits, but the new sinusoidal equation introduced herein, by providing best goodness of fit, can be considered a useful alternative to conventional models in dairy research.

Yield stress evaluation of Finnish clays based on analytical piezocone penetration test (CPTu) models

2020 ◽  
Vol 57 (11) ◽  
pp. 1623-1638 ◽  
Author(s):  
Bruno Di Buò ◽  
Marco D’Ignazio ◽  
Juha Selänpää ◽  
Tim Länsivaara ◽  
Paul W. Mayne
Keyword(s):  
Yield Stress ◽  
Soil Mechanics ◽  
Friction Angle ◽  
Coefficient Of Determination ◽  
Soil Conditions ◽  
Piezocone Penetration Test ◽  
Bias Factor ◽  
Constant Rate ◽  
Target Values ◽  
Spherical Cavity Expansion

A well-established analytical model based on spherical cavity expansion and critical state soil mechanics theories is applied to piezocone soundings for profiling the yield stress and overconsolidation ratio of five soft sensitive test sites located in Finland. Yield stress is related to three piezocone parameters: net cone resistance, excess porewater pressure, and effective cone resistances. Input geoparameters include the effective stress friction angle, defined at both peak strength and at maximum obliquity, and the model directly provides the operational value of the undrained rigidity index. The piezocone-evaluated profiles compare favorably with results from laboratory constant-rate-of-strain consolidation tests for all the investigated sites. Based on the obtained experimental results, simplified correlations valid for Finnish soil conditions are derived. Their validity is assessed based on the bias factor, coefficient of variation, and coefficient of determination, showing a fairly good agreement between the predicted and the target values.

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