A predictive model was made for the logarithm of the thermal decimal reduction time (logD) of Salmonella enterica (D = time to 90% reduction by inactivation). The model was fitted with multiple linear regression from 521 logD-values reported in literature for laboratory media and foods highly varying in water activity and pH. The single regression model with temperature as the only variable had a high residual standard error (RSE) of 0.883 logD and no predictive value (fraction of variance explained (R²) < 0.001). Adding water activity, sugar content and pH as predictors resulted in a model with a lower RSE of 0.458 logD and an adjusted R² of 0.73. The model was validated by comparing 985 predicted with observed logD for S. enterica from other publications. The model was subsequently validated with 1498 published logD-values for inactivation of vegetative cells of nine other pathogenic bacteria genera (mainly Listeria monocytogenes, Escherichia coli, Clostridium perfringens, Cronobacter spp., Staphylococcus aureus, Yersinia enterocolitica) in or on a variety of laboratory media, meat, fish, dairy, nuts, fruits and vegetables. Regression analyses for validation with the 985 logD of S. enterica and 2483 logD of all genera show deviations from the expected slope of 1 (both 0.81) and the expected intercept of 0 (0.04 and 0.19 logD respectively). However, only 0.7% and 2% respectively of the new logD (expected: 0.5%) were observed above the 99% prediction interval of the original S. enterica model based on 521 logD. The findings suggest that i) the variability of thermal resistance of strains within species is larger than between genera and species; ii) one generic predictive model, also accounting for variability, suffices for designing the thermal inactivation of a variety of vegetative pathogenic bacteria in many food types.

建立了肠道沙门氏菌热小数减少时间 (logD) 的对数的预测模型（D  = 灭活减少 90% 的时间）。该模型根据文献中报道的 521 个 logD 值进行多元线性回归，实验室介质和食物的水分活度和 pH 值变化很大。以温度为唯一变量的单一回归模型具有 0.883 logD 的高残差标准误差 (RSE)，并且没有预测值（解释的方差分数 (R ² ) < 0.001）。添加水分活度、糖含量和 pH 作为预测因子，导致模型的 RSE 较低，为 0.458 logD，调整后的 R ²为 0.73。该模型通过比较 985 个预测值与观察到的 logD 来验证S. enterica来自其他出版物。该模型随后使用 1498 个已发布的 logD 值进行验证，用于在各种实验室中或在各种实验室中灭活其他九种病原菌属（主要是单核细胞增生李斯特菌、大肠杆菌、产气荚膜梭菌、克罗诺杆菌属、金黄色葡萄球菌、小肠结肠炎耶尔森氏菌）的营养细胞媒体、肉类、鱼类、乳制品、坚果、水果和蔬菜。使用S. enterica的 985 logD 进行验证的回归分析所有属的 2483 logD 和 2483 logD 显示与 1 的预期斜率（均为 0.81）和 0 的预期截距（分别为 0.04 和 0.19 logD）的偏差。然而，在基于 521 logD的原始S. enterica模型的 99% 预测区间之上，分别仅观察到 0.7% 和 2% 的新 logD（预期：0.5%）。研究结果表明：i) 种内菌株耐热性的变异性大于属与种之间；ii) 一个通用的预测模型，也考虑了变异性，足以设计许多食物类型中各种营养致病菌的热灭活。