title: Application of intelligent modeling to predict the population dynamics of Pseudomonas aeruginosa in Frankfurter sausage containing Satureja bachtiarica extracts.
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 and 25°С) and time (1-20 days). The results showed that the stepwise regression was good for modeling the population dynamics of P. aeruginosa (R(2) = 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 (R(2) = 0.98). Also, an excellent agreement between CANFIS predictions and experimental data was observed (R(2) = 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.
authors.affiliation: Department of Food Science and Technology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran.
authors.forename: Ali
authors.initials: A
authors.lastname: Alghooneh
authors.affiliation: Department of Food Science and Technology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran.
authors.forename: Behrooz Alizadeh
authors.initials: BA
authors.lastname: Behbahani
authors.affiliation: Department of Food Science and Technology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran.
authors.forename: Hamid
authors.initials: H
authors.lastname: Noorbakhsh
authors.affiliation: Department of Food Science and Technology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran. Electronic address: tabatabai@um.ac.ir.
authors.forename: Farideh Tabatabaei
authors.initials: FT
authors.lastname: Yazdi
mesh_terms: D000465:Algorithms; D005503:Food Additives / Q000494:pharmacology*; D007700:Kinetics; D008461:Meat Products / Q000382:microbiology*; D016571:Neural Networks, Computer; D010936:Plant Extracts / Q000494:pharmacology*; D011550:Pseudomonas aeruginosa / Q000737:chemistry / Q000187:drug effects* / Q000254:growth & development*; D031362:Satureja / Q000737:chemistry*
chemical_list: D005503:Food Additives; D010936:Plant Extracts
keywords: Artificial neural network; Co-active neuro fuzzy inference system; Genetic algorithm; Modeling; Pseudomonas aeruginosa; Satureja bachtiarica