• Journal of Environmental Science International
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• v.26 no.4
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• pp.421-432
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• 2017

In this study, we examined the suitability of ten disinfection models for predicting the inactivation of Artemia sp. via single or combined physical and chemical treatments. The effect of Hydraulic Retention Time (HRT) on the inactivation of Artemia sp. was examined experimentally. Disinfection models were fitted to the experimental data by using the GInaFiT plug-in for Microsoft Excel. The inactivation model were evaluated on the basis of RMSE (Root Mean Square Error), SSE (mean Sum Square Error) and $r^2$. An inactivation model with the lowest RMSE, SSE and $r^2$ close to 1 was considered the best. The Weibull+Tail model was found to be the most appropriate for predicting the inactivation of Artemia sp. via electrolytic treatment and electrolytic-ultrasonic combined treatment. The Log-linear+Tail model was the most appropriate for modeling inactivation via homogenization and combined electrolytic-homogenization treatment. The double Weibull disinfection model was the most suitable for the predicting inactivation via ultrasonic treatment.

• Journal of Environmental Science International
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• v.24 no.11
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• pp.1393-1404
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• 2015

Ten empirical disinfection models for the plasma process were used to find an optimum model. The variation of model parameters in each model according to the operating conditions (first voltage, second voltage, air flow rate, pH, incubation water concentration) were investigated in order to explain the disinfection model. In this experiment, the DBD (dielectric barrier discharge) plasma reactor was used to inactivate Phytophthora capsici which cause wilt in tomato plantation. Optimum disinfection models were chosen among ten models by the application of statistical SSE (sum of squared error), RMSE (root mean sum of squared error), $r^2$ values on the experimental data using the GInaFiT software in Microsoft Excel. The optimum models were shown as Log-linear+Tail model, Double Weibull model and Biphasic model. Three models were applied to the experimental data according to the variation of the operating conditions. In Log-linear+Tail model, $Log_{10}(N_o)$, $Log_{10}(N_{res})$ and $k_{max}$ values were examined. In Double Weibull model, $Log_{10}(N_o)$, $Log_{10}(N_{res})$, ${\alpha}$, ${\delta}_1$, ${\delta}_2$, p values were calculated and examined. In Biphasic model, $Log_{10}(N_o)$, f, $k_{max1}$ and $k_{max2}$ values were used. The appropriate model parameters for the calculation of optimum operating conditions were $k_{max}$, ${\alpha}$, $k_{max1}$ at each model, respectively.

• Food Science and Biotechnology
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• v.18 no.1
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• pp.137-142
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• 2009

One of the most important aspects of conducting this microbial risk assessment (MRA) is determining the model in microbial behaviors in food systems. However, to fully these modeling, large expenditures or newly laboratory experiments will be spent to do it. To overcome these problems, it has to be considered to develop the new strategies that can be used data in the published literatures. This study is to show whether or not the data set from the published experimental data has more value for modeling for MRA. To illustrate this suggestion, as example of data set, 4 published Salmonella survival in Cheddar cheese reports were used. Finally, using the GInaFiT tool, survival was modeled by nonlinear polynomial regression model describing the effect of temperature on Weibull model parameters. This model used data in the literatures is useful in describing behavior of Salmonella during different time and temperature conditions of cheese ripening.

• Journal of Environmental Science International
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• v.21 no.6
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• pp.695-704
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• 2012

The application of disinfection models on the plasma process was investigated. Nine empirical models were used to find an optimum model. The variation of parameters in model according to the operating conditions (first voltage, second voltage, air flow rate, pH) were investigated in order to explain the disinfection model. In this experiment, the DBD (dielectric barrier discharge) plasma reactor was used to inactivate Ralstonia Solanacearum which cause wilt in tomato plantation. Optimum disinfection models were chosen among the nine models by the application of statistical SSE (sum of squared error), RMSE (root mean sum of squared error), $r^2$ values on the experimental data using the GInaFiT software in Microsoft Excel. The optimum model was shown as Weibull+talil model followed by Log-linear+ Shoulder+Tail model. Two models were applied to the experimental data according to the variation of the operating conditions. In Weibull+talil model, Log10($N_o$), Log10($N_{res}$), ${\delta}$ and p values were examined. And in Log-linear+Shoulder+Tail model, the Log10($N_o$), Log10($N_{res}$), $k_{max}$, Sl values were calculated and examined.