The aim of this study was to evaluate the application of real-time polymerase chain reaction (PCR)-based quantification as a rapid and accurate tool for the monitoring and prediction of Listeria monocytogenes growth in pasteurized milk under constant and fluctuating temperature conditions. The growth of L. monocytogenes was monitored under constant temperature conditions at 4°C, 10°C, 15°C, 20°C, and 35°C. High correlation was obtained between the bacterial growth rate and incubation temperature, where the R² of the slope of the square root model was calculated to be 0.993 and 0.996 for real-time PCR and the conventional culture method, respectively. Moreover, the obtained maximum specific growth rate (μ_max) data plots were correlated with 188 L. monocytogenes μ_max data points from the existing model according to ComBase database, with an R² of 0.961 for real-time PCR and of 0.931 for the conventional culture method. The growth models were examined under three different patterns of fluctuating temperature conditions ranging from 2°C to 30°C. The prediction results fell within ±20% of the relative error zone, showing that real-time PCR quantification could be used for fast, sensitive, and specific bacterial growth monitoring with high-throughput results. Real-time PCR should be considered a promising option and powerful tool for the construction of a bacterial growth prediction model for safety risk analysis in the dairy industry.

中文翻译：

---

利用实时聚合酶链反应预测巴氏杀菌奶中温度波动条件下单核细胞增生李斯特菌的生长模型。

本研究的目的是评估基于实时聚合酶链反应 (PCR) 的定量作为一种快速、准确的工具的应用，用于在恒定和波动的温度条件下监测和预测巴氏杀菌牛奶中单核细胞增生李斯特菌的生长情况。在 4°C、10°C、15°C、20°C 和 35°C 的恒温条件下监测单核细胞增生李斯特菌的生长。细菌生长速率和培养温度之间获得了高度相关性，其中实时 PCR 和常规培养方法计算平方根模型斜率的R ^{2 分别}为 0.993 和 0.996。此外，获得的最大比增长率（μ _max) 数据图与来自现有模型的188 个单核细胞增生李斯特菌 μ _max数据点相关，根据 ComBase 数据库，实时 PCR的R ²为 0.961，常规培养方法的R ²为 0.931。在从 2°C 到 30°C 的三种不同温度波动模式下检查了生长模型。预测结果落在±20%的相对误差范围内，表明实时PCR定量可用于快速、灵敏、特异的细菌生长监测，具有高通量结果。实时 PCR 应该被认为是一种有前景的选择和强大的工具，用于构建用于乳制品行业安全风险分析的细菌生长预测模型。