title: Bioinactivation: Software for modelling dynamic microbial inactivation.
abstract: This contribution presents the bioinactivation software, which implements functions for the modelling of isothermal and non-isothermal microbial inactivation. This software offers features such as user-friendliness, modelling of dynamic conditions, possibility to choose the fitting algorithm and generation of prediction intervals. The software is offered in two different formats: Bioinactivation core and Bioinactivation SE. Bioinactivation core is a package for the R programming language, which includes features for the generation of predictions and for the fitting of models to inactivation experiments using non-linear regression or a Markov Chain Monte Carlo algorithm (MCMC). The calculations are based on inactivation models common in academia and industry (Bigelow, Peleg, Mafart and Geeraerd). Bioinactivation SE supplies a user-friendly interface to selected functions of Bioinactivation core, namely the model fitting of non-isothermal experiments and the generation of prediction intervals. The capabilities of bioinactivation are presented in this paper through a case study, modelling the non-isothermal inactivation of Bacillus sporothermodurans. This study has provided a full characterization of the response of the bacteria to dynamic temperature conditions, including confidence intervals for the model parameters and a prediction interval of the survivor curve. We conclude that the MCMC algorithm produces a better characterization of the biological uncertainty and variability than non-linear regression. The bioinactivation software can be relevant to the food and pharmaceutical industry, as well as to regulatory agencies, as part of a (quantitative) microbial risk assessment.
authors.affiliation: Departamento de Ingeniería de Alimentos y del Equipamiento Agrícola, Instituto de Biotecnología Vegetal, Universidad Politécnica de Cartagena (ETSIA), Paseo Alfonso XIII, 48, 30203 Cartagena, Spain.
authors.forename: Alberto
authors.initials: A
authors.lastname: Garre
authors.affiliation: Departamento de Ingeniería de Alimentos y del Equipamiento Agrícola, Instituto de Biotecnología Vegetal, Universidad Politécnica de Cartagena (ETSIA), Paseo Alfonso XIII, 48, 30203 Cartagena, Spain. Electronic address: pablo.fernandez@upct.es.
authors.forename: Pablo S
authors.initials: PS
authors.lastname: Fernández
authors.affiliation: National Food Agency, Box 622, SE 751 26 Uppsala, Sweden.
authors.forename: Roland
authors.initials: R
authors.lastname: Lindqvist
authors.affiliation: Departamento de Matemática Aplicada y Estadística, Universidad Politécnica de Cartagena, Antiguo Hospital de Marina (ETSII), Av. Dr. Fleming S/N, 30202 Cartagena, Spain.
authors.forename: Jose A
authors.initials: JA
authors.lastname: Egea
mesh_terms: D000465:Algorithms; D001407:Bacillus / Q000502:physiology; D003198:Computer Simulation; D005516:Food Microbiology / Q000379:methods*; D050296:Microbial Viability; D008954:Models, Biological; D008962:Models, Theoretical; D012984:Software; D013696:Temperature
keywords: Freeware tool; Model fitting; Non-isothermal microbial inactivation; Predictive microbiology