title: Modelling the growth of Listeria monocytogenes in dynamic conditions.
abstract: A recurrent neural network for the prediction of Listeria monocytogenes growth under pH and a(w) variable conditions was developed. The use of this model offered the possibility to take into account the consequences of the variations of the factors on L. monocytogenes growth. The effects of solutions, such as NaCl, acetic acid and NaOH, and their interactions on the response of L. monocytogenes cells were studied. Furthermore, the results showed the capacity of the recurrent neural network to predict growths carried out in different experimental conditions without using those used for its elaboration.
authors.affiliation: Station de Recherches sur la Viande, Institut National de la Recherche Agronomique, Saint-Genès Champanelle, France.
authors.forename: M
authors.initials: M
authors.lastname: Cheroutre-Vialette
authors.forename: A
authors.initials: A
authors.lastname: Lebert
mesh_terms: D000818:Animals; D004285:Dogs; D006863:Hydrogen-Ion Concentration; D008089:Listeria monocytogenes / Q000254:growth & development*; D008954:Models, Biological; D012965:Sodium Chloride / Q000494:pharmacology
chemical_list: D012965:Sodium Chloride