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首页> 外文期刊>Food and bioprocess technology >Evaluation of High Pressure Processing Kinetic Models for Microbial Inactivation Using Standard Statistical Tools and Information Theory Criteria, and the Development of Generic Time-Pressure Functions for Process Design
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Evaluation of High Pressure Processing Kinetic Models for Microbial Inactivation Using Standard Statistical Tools and Information Theory Criteria, and the Development of Generic Time-Pressure Functions for Process Design

机译:使用标准统计工具和信息论准则对微生物灭活的高压处理动力学模型进行评估,并开发通用的时间压力函数进行工艺设计

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摘要

Generic kinetic models for microbial inactivation by high pressure processing (HPP) would accelerate the development of commercial applications. The aim of this work was to develop a generic model obtained by fitting peer-reviewed microbial inactivation data (124 kinetic curves) to first-order kinetics (LKM), Weibull (WBLL), and Gompertz (GMPZ) primary and secondary models. Standard statistics (coefficient of determination (R (2)), variance, residuals plots, experimental vs. predicted plots) and information theory criteria (Akaike Information Criteria, AIC; Akaike differences, a dagger AIC (i) , Bayesian Information Criteria) determined their goodness of fit. Standard statistics showed no differences between WBLL and GMPZ, whereas information theory criteria identified WBLL as the best model (lowest AIC (i) value, 61.3 % of cases). LKM performed poorly according to all statistics (e.g., a dagger AIC (i) > 10, 58.1 % of cases). The dispersion of model parameters prevented the derivation of a secondary model for the whole dataset, but clear trends and sufficient data (56 kinetic curves) were found to develop one for milk. A secondary WBLL model (b' = 0.056-2.230, n = 0.758 -aEuro parts per thousand 0.403; 150-600 MPa) was the best alternative (AIC (i) = 183.8). A GMPZ model yielded similar predictions, but registered a dagger AIC (i) = 19.3 reflecting its larger number of parameters (p = 8). Selecting datasets with pressure holding times of commercial interest (t a parts per thousand currency signaEuro parts per thousand 10 min) yielded different parameter estimates for the generic WBLL model (b' = 0.079-1.859, n = 1.340-0.557; 300-600 MPa). In conclusion, information theory criteria complemented standard statistics, and the simpler WBLL secondary model (p = 4) provided a product-specific time-pressure function of industrial relevance.
机译:通过高压处理(HPP)灭活微生物的通用动力学模型将加速商业应用的开发。这项工作的目的是开发一个通用模型,该模型是通过将同行评议的微生物灭活数据(124个动力学曲线)与一阶动力学(LKM),威布尔(WBLL)和Gompertz(GMPZ)初级和次级模型拟合而获得的。确定标准统计量(确定系数(R(2)),方差,残差图,实验图与预测图)和信息理论标准(Akaike信息标准,AIC; Akaike差异,匕首AIC(i),贝叶斯信息标准)他们的适合度。标准统计数据显示WBLL和GMPZ之间没有差异,而信息理论标准确定WBLL为最佳模型(最低AIC(i)值,占病例的61.3%)。根据所有统计数据,LKM的表现不佳(例如,匕首AIC(i)> 10,占案件的58.1%)。模型参数的分散阻止了整个数据集的二级模型的推导,但是发现了清晰的趋势和足够的数据(56条动力学曲线),可以开发出一个牛奶模型。二级WBLL模型(b'= 0.056-2.230,n = 0.758 -aEuro千分之0.403; 150-600 MPa)是最佳替代方法(AIC(i)= 183.8)。一个GMPZ模型产生了相似的预测,但是记录了一个匕首AIC(i)= 19.3,反映出它的大量参数(p = 8)。选择具有商业关注压力保持时间的数据集(ta千分之一货币符号a十亿分之一欧元十分钟)对于通用WBLL模型得出不同的参数估计值(b'= 0.079-1.859,n = 1.340-0.557; 300-600 MPa) 。总之,信息论标准补充了标准统计数据,更简单的WBLL二级模型(p = 4)提供了与产品相关的特定于时间的产业关联函数。

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