title: Application of polynomial models to predict growth of mixed cultures of Pseudomonas spp. and Listeria in meat.
abstract: Three models for one rapid and one slow growing strain of Pseudomonas fragi and one slow growing strain of P. fluorescens were developed in a meat broth; they were designed to take account of variations in growth and to provide a growth response interval. These models, and another for Listeria monocytogenes (Lm14 model), were used to predict the growth of spoilage Pseudomonas spp. and pathogenic Listeria in meat products. The Pseudomonas and Listeria models provided satisfactory predictions concerning inoculated strains grown in decontaminated beef meat. It was also possible to use the Pseudomonas models to predict the growth of the natural flora (mainly Pseudomonas spp.) of refrigerated meat stored under aerobic conditions. In experiments with mixed populations, three situations were observed: (1) in decontaminated meat, L. monocytogenes inoculated alone grew well at 6 degrees C, and this result was correctly predicted by the model; (2) in decontaminated meat inoculated with Listeria and Pseudomonas strains, L. innocua grew well and was not affected by the presence of Pseudomonas, and the growth of both organisms was correctly predicted by the models; (3) in naturally contaminated meat inoculated with Listeria, the strain did not grow until Pseudomonas had reached the stationary phase. The models satisfactorily predicted the growth of Pseudomonas spp. but not that of Listeria. In conclusion, the Lm14 model cannot be used for refrigerated meat stored aerobically as the results suggest a 'fail-safe' level which may be too high: meat had already reached a spoilage state even though no increase in the level of Listeria was observed. The Pseudomonas models accurately predicted the growth of naturally occurring Pseudomonas spp.
authors.affiliation: Equipe Microbiologie, Station de Recherches sur la Viande, Institut National de la Recherche Agronomique, Saint-Genès Champanelle, France. ilebert@clermont.inra.fr
authors.forename: I
authors.initials: I
authors.lastname: Lebert
authors.forename: V
authors.initials: V
authors.lastname: Robles-Olvera
authors.forename: A
authors.initials: A
authors.lastname: Lebert
mesh_terms: D000818:Animals; D015982:Bias; D002417:Cattle; D005519:Food Preservation; D005544:Forecasting; D008087:Listeria / Q000254:growth & development*; D008460:Meat / Q000382:microbiology*; D008954:Models, Biological; D015233:Models, Statistical; D011549:Pseudomonas / Q000254:growth & development*; D013997:Time Factors