Geeraerd A H, Valdramidis V P, Van Impe J F
BioTeC-Bioprocess Technology and Control, Department of Chemical Engineering, Katholieke Universiteit Leuven, W. de Croylaan 46, B-3001 Leuven, Belgium.
Int J Food Microbiol. 2005 Jun 25;102(1):95-105. doi: 10.1016/j.ijfoodmicro.2004.11.038.
This contribution focuses on the presentation of GInaFiT (Geeraerd and Van Impe Inactivation Model Fitting Tool), a freeware Add-in for Microsoft Excel aiming at bridging the gap between people developing predictive modelling approaches and end-users in the food industry not familiar with or not disposing over advanced non-linear regression analysis tools. More precisely, the tool is useful for testing nine different types of microbial survival models on user-specific experimental data relating the evolution of the microbial population with time. As such, the authors believe to cover all known survivor curve shapes for vegetative bacterial cells. The nine model types are: (i) classical log-linear curves, (ii) curves displaying a so-called shoulder before a log-linear decrease is apparent, (iii) curves displaying a so-called tail after a log-linear decrease, (iv) survival curves displaying both shoulder and tailing behaviour, (v) concave curves, (vi) convex curves, (vii) convex/concave curves followed by tailing, (viii) biphasic inactivation kinetics, and (ix) biphasic inactivation kinetics preceded by a shoulder. Next to the obtained parameter values, the following statistical measures are automatically reported: standard errors of the parameter values, the Sum of Squared Errors, the Mean Sum of Squared Errors and its Root, the R(2) and the adjusted R(2). The tool can help the end-user to communicate the performance of food preservation processes in terms of the number of log cycles of reduction rather than the classical D-value and is downloadable via the KULeuven/BioTeC-homepage at the topic "Downloads" (Version 1.4, Release date April 2005).
本文着重介绍GInaFiT(吉拉德和范因佩失活模型拟合工具),这是一款针对Microsoft Excel的免费插件,旨在弥合开发预测建模方法的人员与食品行业中不熟悉或没有先进非线性回归分析工具的终端用户之间的差距。更确切地说,该工具可用于根据微生物数量随时间变化的用户特定实验数据,测试九种不同类型的微生物存活模型。因此,作者认为该工具涵盖了所有已知的营养细菌细胞存活曲线形状。这九种模型类型分别为:(i)经典对数线性曲线;(ii)在对数线性下降明显之前呈现所谓肩部的曲线;(iii)在对数线性下降之后呈现所谓尾部的曲线;(iv)同时呈现肩部和尾部行为的存活曲线;(v)凹曲线;(vi)凸曲线;(vii)先凸/凹后尾部的曲线;(viii)双相失活动力学;(ix)在双相失活动力学之前有肩部的曲线。除了获得的参数值外,还会自动报告以下统计量:参数值的标准误差、平方和误差、均方误差及其平方根、R(2)和调整后的R(2)。该工具可帮助终端用户以对数减少周期数而非传统的D值来描述食品保鲜过程的性能,可通过鲁汶大学/生物技术中心主页上的“下载”主题(版本1.4,发布日期2005年4月)下载。
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