Abstract The present study was aimed at developing a mathematical model to predict the growth of Salmonella in ground chicken in the presence of the background microflora. Ground chicken was inoculated with a cocktail of S. Typhimurium and S. Enteritidis and incubated at various isothermal temperatures (8-33 °C). Salmonella grew at all temperatures, except at 8 °C, while the background microflora could grow under all conditions. The observed growth data of both Salmonella and background microflora at temperatures between 12 and 33 °C were analyzed simultaneously to develop the predictive growth models. The Huang-Jameson effect (HJE) model and Huang-Lotka-Volterra (HLV) model were used to describe the growth and interaction between Salmonella and background microflora. The Huang square-root model was used to evaluate the effect of temperature on the growth rates and lag times of Salmonella and background microflora. A one-step analysis method was used to directly build the tertiary models and to determine the kinetic parameters from the growth curves. The minimum growth temperature (Tmin) for Salmonella estimated by both the HJE and HLV models was 7.2 °C. The Tmin for background flora determined by HJE and HLV model was 1.3 and 1.8 °C, respectively. Under competition, the growth rate of Salmonella could be lower than that of the background microflora at temperatures below 16.8 °C, while Salmonella would grow faster than the background microflora at temperatures above 16.8 °C. With relatively low value of RMSE (0.3 log CFU/g), the HJE and HLV models could both successfully describe the growth of Salmonella and native microflora and the interaction between the two. Although the Akaike Information Criterion (AIC) value of the HJE model (−349.1) was slightly smaller than that of the HLV model (−339.4), both models were practically equal in accuracy for predicting the competitive growth of Salmonella and background flora in ground chicken. The HJE model and kinetic parameters were validated using separate isothermal and dynamic growth data. The validation results indicated the competition model was accurate, with the RMSE of the predictions was 0.3 log CFU/g. Overall, the residual errors of predictions followed a normal distribution, with approximately 86.3% of them were within ±0.5 log CFU/g. The results from this study may be useful for microbial risk assessments of Salmonella and shelf-life prediction of ground chicken.

中文翻译：

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沙门氏菌竞争性生长的一步动力学分析。和地面鸡的背景植物群

摘要 本研究旨在开发一种数学模型，以预测存在背景微生物群落的碎鸡中沙门氏菌的生长情况。用鼠伤寒沙门氏菌和肠炎沙门氏菌的混合物接种碎鸡，并在各种等温温度 (8-33 °C) 下孵育。沙门氏菌在所有温度下都能生长，除了 8 °C，而背景微生物群落可以在所有条件下生长。同时分析沙门氏菌和背景微生物群在 12 至 33 °C 温度下观察到的生长数据，以开发预测生长模型。Huang-Jameson 效应(HJE) 模型和Huang-Lotka-Volterra (HLV) 模型用于描述沙门氏菌与背景微生物群落之间的生长和相互作用。Huang平方根模型用于评估温度对沙门氏菌和背景微生物群落的生长速率和滞后时间的影响。一步分析方法用于直接建立三级模型并从生长曲线确定动力学参数。HJE 和 HLV 模型估计的沙门氏菌的最低生长温度 (Tmin) 为 7.2 °C。HJE 和 HLV 模型确定的背景菌群的 Tmin 分别为 1.3 和 1.8 °C。在竞争条件下，沙门氏菌在低于 16.8 °C 的温度下的生长速度可能低于背景菌群的生长速度，而在高于 16.8 °C 的温度下，沙门氏菌的生长速度会快于背景菌群。RMSE 值相对较低（0.3 log CFU/g），HJE 和 HLV 模型都可以成功地描述沙门氏菌和本地微生物群落的生长以及两者之间的相互作用。尽管 HJE 模型的 Akaike 信息准则 (AIC) 值 (-349.1) 略小于 HLV 模型的值 (-339.4)，但两种模型在预测沙门氏菌和地面背景菌群的竞争性生长方面的准确度几乎相同鸡。HJE 模型和动力学参数使用单独的等温和动态生长数据进行验证。验证结果表明竞争模型是准确的，预测的 RMSE 为 0.3 log CFU/g。总体而言，预测的残差遵循正态分布，其中约 86.3% 在 ±0.5 log CFU/g 以内。