Bootstrap parametric GB2 and bootstrap nonparametric distributions for studying shiga toxin-producing Escherichia coli strains growth rate variability. (June 2019)

• Record Type: Journal Article
• Authors: Quinto, E.J.; Marín, J.M.; Caro, I.; Mateo, J.; Redondo-del-Río, M.P.; de-Mateo-Silleras, B.; Schaffner, D.W.
• Is Part Of: Food research international. Volume 120(2019)
• Page Start: 829
• Page End: 838
• Publication Date: 2019-06
• Subjects: Escherichia coli -- Pathogenic -- Bootstrap -- Parametric -- Nonparametric -- GB2 distribution; Food -- Analysis -- Periodicals; Food industry and trade -- Periodicals; Food industry and trade -- Canada -- Periodicals; Food Technology -- Periodicals; Food -- Periodicals; Food-Processing Industry -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Industrie et commerce -- Canada -- Périodiques; Aliments -- Recherche -- Périodiques; Food industry and trade; Canada; Periodicals; Electronic journals; 664.005
• DOI: 10.1016/j.foodres.2018.11.045
• Languages: English
• ISSNs: 0963-9969

Abstract

Abstract: Shiga toxin-producing Escherichia coli (VTEC) strains, including the serotype O157:H7, are considered foodborne pathogens. Transmission occurs through consumption of undercooked meat, unpasteurized dairy products, vegetables, or contaminated water. The variability of pathogenic and nonpathogenic E. coli strains growth parameters at different temperatures and in different media was studied. Bootstrap parametric (Generalized Beta of the Second Kind, GB2) or nonparametric models were used. GB2 estimations show increased growth rates and shortened lag times with increased temperature, as expected. Similar estimations were obtained using the nonparametric model. Parametric and nonparametric growth rate confidence intervals were wider with increased temperature; lag times confidence intervals were wider with decreased temperature. The nonparametric method gives similar confidence intervals to the parametric method, confirming its suitability for growth parameters estimation. The estimations obtained from nonpathogenic E. coli strains approximate distributions from pathogenic E. coli strains. Graphical abstract: Unlabelled Image Highlights: The variability of Shiga toxin-producing E. coli strains was modeled. Bootstrap parametric and nonparametric models were used. The GB2 distribution was used for the first time to study microbial growth data. No differences between growth parameters and their estimations were found.