Garre Alberto, Fernández Pablo S, Lindqvist Roland, Egea Jose A
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.
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.
Food Res Int. 2017 Mar;93:66-74. doi: 10.1016/j.foodres.2017.01.012. Epub 2017 Jan 20.
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.
本文介绍了生物灭活软件，该软件实现了等温及非等温微生物灭活建模的功能。该软件具有用户友好性、动态条件建模、可选择拟合算法以及生成预测区间等特点。该软件有两种不同格式：生物灭活核心版（Bioinactivation core）和生物灭活标准版（Bioinactivation SE）。生物灭活核心版是一个用于R编程语言的包，其中包括使用非线性回归或马尔可夫链蒙特卡罗算法（MCMC）生成预测以及将模型拟合到灭活实验的功能。计算基于学术界和工业界常用的灭活模型（Bigelow、Peleg、Mafart和Geeraerd）。生物灭活标准版为生物灭活核心版的选定功能提供了一个用户友好的界面，即非等温实验的模型拟合和预测区间的生成。本文通过一个案例研究展示了生物灭活的能力，该案例研究对嗜热栖热芽孢杆菌的非等温灭活进行了建模。这项研究全面描述了细菌对动态温度条件的反应，包括模型参数的置信区间和存活曲线的预测区间。我们得出结论，与非线性回归相比，MCMC算法能更好地描述生物不确定性和变异性。作为（定量）微生物风险评估的一部分，生物灭活软件可能与食品和制药行业以及监管机构相关。
