Development and validation of a molecular predictive model to describe the growth of Listeria monocytogenes in vacuum-packaged chilled pork
Development and validation of a molecular predictive model to describe the growth of Listeria monocytogenes in vacuum-packaged chilled pork
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描述真空包装冷却猪肉中单核细胞增生李斯特氏菌生长的分子预测模型的开发和验证
DOI：
10.1016/j.foodcont.2012.11.017
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发表时间：
2013-07
期刊：
影响因子：
6
通讯作者：
Zhou, Guanghong
中科院分区：
文献类型：
--
作者：
Ye, Keping;Wang, Huhu;Zhang, Xinxiao;Jiang, Yun;Xu, Xinglian;Zhou, Guanghong
本研究的目的是通过适当的实时PCR方法建立分子预测模型，以描述在选择的温度条件（4、10、15、20和25℃）下，单核细胞增生李斯特菌鸡尾酒菌株在真空包装冷鲜猪肉中的生长情况。我们将该模型与利用传统微生物学方法获得的原始数据的传统预测模型进行了比较。利用Real-time PCR成功构建预测模型。所有生长曲线均呈s型曲线，4种主要生长模型（修正的Gompertz、Baranyi、Logistic和Huang）均可拟合生长曲线。所有模型的r2值为0.97，MSE值为0.2198 log cfu/mL。除25℃实时PCR检测结果外，其余Bf、Af值均在1.0≤Bf≤Af≤1.1范围内。F检验表明，修正后的Gompertz、Logistic和Baranyi模型足以描述生长曲线，但在10个案例中，Huang模型被拒绝两次。经F检验，大多数生长曲线的分子预测模型与传统预测模型的准确度无显著差异。此外，实时PCR与传统微生物学方法在生长速率和滞后期均无差异。分子预测模型的应用不仅有助于在其他细菌存在的情况下更准确地建立某些病原体的模型，而且节省了时间和劳动力。因此，它将降低病原体的风险，提高肉类和肉制品的安全性。
The aim of this study was to develop a molecular predictive model from appropriate real-time PCR methods, so as to describe the growth of a cocktail of Listeria monocytogenes strains in vacuum-packaged chilled pork during storage at selected temperature conditions (4, 10, 15, 20 and 25 °C). We compared this model with a traditional predictive model which used original data obtained by conventional microbiological methods. Real-time PCR was successfully used in the construction of a predictive model. A sigmoidal trend was observed for all growth curves, and four primary growth models (modified Gompertz, Baranyi, Logistic and Huang) could be used to fit the growth curves. The R2values were >0.97 and MSE values were 0.2198 log cfu/mL in all models used. Most of the Bf and Af values were within the limit of 1.0 ≤ Bf ≤ Af ≤ 1.1, except for one obtained by real-time PCR at 25 °C. The F test showed that the modified Gompertz, Logistic and Baranyi models were sufficient to describe growth curves, but the Huang model was rejected twice in ten cases. No difference was observed in accuracy between the molecular and traditional predictive models for most of growth curves when assessed by F test. Further, no differences in both growth rate and lag phase were observed between real-time PCR and conventional microbiological methods. The application of molecular predictive model not only can aid to establish models of certain pathogens more accurately in the presence of other bacteria, but also save time and labor. Thereby, it will reduce the risk of pathogens and enhance the safety of meat and meat products.
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影响因子：
5.3
作者：
S. Sheen;C. Hwang;V. Juneja
通讯作者：
S. Sheen;C. Hwang;V. Juneja
影响因子：
3.9
作者：
G. Muratore;Fabio Licciardello
通讯作者：
G. Muratore;Fabio Licciardello
影响因子：
6
作者：
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通讯作者：
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DOI：
10.1016/j.lwt.2006.03.020
发表时间：
2007-06
期刊：
Lwt - Food Science and Technology
影响因子：
--
作者：
Hou-yin Wang;Yuanying Ni;Xiaosong Hu;Jihong Wu;X. Liao;Fang Chen;Zhengfu Wang
通讯作者：
Hou-yin Wang;Yuanying Ni;Xiaosong Hu;Jihong Wu;X. Liao;Fang Chen;Zhengfu Wang
影响因子：
5.3
作者：
T. Oscar
通讯作者：
T. Oscar