Table_1_New Term to Quantify the Effect of Temperature on pHmin-Values Used in Cardinal Parameter Growth Models for Listeria monocytogenes.pdf

The aim of this study was to quantify the influence of temperature on pHmin-values of Listeria monocytogenes as used in cardinal parameter growth models and thereby improve the prediction of growth for this pathogen in food with low pH. Experimental data for L. monocytogenes growth in broth at different pH-values and at different constant temperatures were generated and used to determined pHmin-values. Additionally, pHmin-values for L. monocytogenes available from literature were collected. A new pHmin-function was developed to describe the effect of temperatures on pHmin-values obtained experimentally and from literature data. A growth and growth boundary model was developed by substituting the constant pHmin-value present in the Mejlholm and Dalgaard (2009) model (J. Food. Prot. 72, 2132–2143) by the new pHmin-function. To obtain data for low pH food, challenge tests were performed with L. monocytogenes in commercial and laboratory-produced chemically acidified cheese including glucono-delta-lactone (GDL) and in commercial cream cheese. Furthermore, literature data for growth of L. monocytogenes in products with or without GDL were collected. Evaluation of the new and expanded model by comparison of observed and predicted μmax-values resulted in a bias factor of 1.01 and an accuracy factor of 1.48 for a total of 1,129 growth responses from challenge tests and literature data. Growth and no-growth responses of L. monocytogenes in seafood, meat, non-fermented dairy products, and fermented cream cheese were 90.3% correctly predicted with incorrect predictions being 5.3% fail-safe and 4.4% fail-dangerous. The new pHmin-function markedly extended the range of applicability of the Mejlholm and Dalgaard (2009) model from pH 5.4 to pH 4.6 and therefore the model can now support product development, reformulation or risk assessment of food with low pH including chemically acidified cheese and cream cheese.

本研究旨在量化温度对核心参数生长模型（cardinal parameter growth models）中所采用的单核细胞增生李斯特菌（Listeria monocytogenes）最小生长pH值（pHmin）的影响，以此提升该食源性致病菌在低pH食品中的生长预测精度。我们通过实验获取了不同pH值与恒定温度条件下，单核细胞增生李斯特菌在肉汤培养基中的生长数据，并以此测定其最小生长pH值。此外，我们还收集了公开文献中报道的单核细胞增生李斯特菌最小生长pH值数据。本研究开发了一种全新的pHmin函数，用以描述温度对实验测得及文献来源的单核细胞增生李斯特菌最小生长pH值的影响规律。我们将Mejlholm与Dalgaard（2009）发表于《食品保护杂志（Journal of Food Protection）》第72卷第2132-2143页的模型中所采用的固定最小生长pH值，替换为新开发的pHmin函数，由此构建了全新的生长及生长边界模型。为获取低pH食品相关实验数据，我们针对单核细胞增生李斯特菌开展了挑战试验：试验基质涵盖市售及实验室制备的、以葡萄糖酸δ-内酯（glucono-delta-lactone, GDL）为酸化剂的干酪，以及市售奶油干酪。此外，我们还收集了公开文献中有关单核细胞增生李斯特菌在添加或未添加GDL的食品中的生长数据。通过对比实测与预测的最大比生长速率（μmax），我们对新扩展模型进行了评估：基于挑战试验及文献来源的共计1129组生长响应数据，该模型的偏差因子为1.01，精准因子为1.48。针对单核细胞增生李斯特菌在海产品、肉类、非发酵乳制品及发酵奶油干酪中的生长与不生长响应情况，模型预测准确率达90.3%；其中错误预测中5.3%为安全型误判（fail-safe），4.4%为危险型误判（fail-dangerous）。新开发的pHmin函数将Mejlholm与Dalgaard（2009）模型的适用pH范围从5.4显著拓展至4.6，因此该模型如今可用于支撑低pH食品（包括化学酸化干酪与奶油干酪）的产品开发、配方改良或风险评估工作。