Micobial Pathogenesis, ( ISI ), Volume (85), No (6), Year (2015-6) , Pages (58-65)

Title : ( Application of intelligent modeling to predict the population dynamics of Pseudomonas aeruginosa in Frankfurter sausage containing Satureja bachtiarica extracts )

Authors: Ali Alghooneh , behrooz alizadeh behbahani , Hamid Noorbakhsh , Farideh Tabatabaei yazdi ,

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Abstract

Stepwise regression, Genetic Algorithm-Artificial Neural Network (GA-ANN) and Co-Active Neuro Fuzzy Inference System (CANFIS) were used to predict the effect of Satureja extracts (water and ethanol) on the population dynamics of Pseudomonas aeruginosa in a complex food system (Frankfurter sausage). The stepwise regression, GA-ANN and CANFIS were fed with four inputs: concentration (at five levels 0, 2000,4000, 6000 and 8000 ppm), type of extract (water and ethanol), temperature (at three levels 5, 15 an 250С) and time (1e20 days). The results showed that the stepwise regression was good for modeling the population dynamics of P. aeruginosa (R2 ¼ 0.92). It was found that ANN with one hidden layer comprising 14 neurons gave the best fitting with the experimental data, so that made it possible to predict with a high determination coefficient (R2 ¼ 0.98). Also, an excellent agreement between CANFIS predictions and experimental data was observed (R2 ¼ 0.96). In this research, GA-ANN was the best approach to simulate the population dynamics of P. aeruginosa. Furthermore, Satureja bachtiarica ethanol extract was able to reduce P. aeruginosa population, showing stronger effect at 5 C and the concentration of 8000 ppm.

Keywords

, Modeling, Pseudomonas aeruginosa, Satureja bachtiarica, Genetic algorithm, Artificial neural network Co-active neuro fuzzy inference system
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@article{paperid:1048398,
author = {Alghooneh, Ali and Alizadeh Behbahani, Behrooz and Noorbakhsh, Hamid and Tabatabaei Yazdi, Farideh},
title = {Application of intelligent modeling to predict the population dynamics of Pseudomonas aeruginosa in Frankfurter sausage containing Satureja bachtiarica extracts},
journal = {Micobial Pathogenesis},
year = {2015},
volume = {85},
number = {6},
month = {June},
issn = {0882-4010},
pages = {58--65},
numpages = {7},
keywords = {Modeling، Pseudomonas aeruginosa، Satureja bachtiarica، Genetic algorithm، Artificial neural network Co-active neuro fuzzy inference system},
}

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%0 Journal Article
%T Application of intelligent modeling to predict the population dynamics of Pseudomonas aeruginosa in Frankfurter sausage containing Satureja bachtiarica extracts
%A Alghooneh, Ali
%A Alizadeh Behbahani, Behrooz
%A Noorbakhsh, Hamid
%A Tabatabaei Yazdi, Farideh
%J Micobial Pathogenesis
%@ 0882-4010
%D 2015

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