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Comparative assessment of plate count and PMA-qPCR methods for modeling the growth of lactic acid bacteria in smoked turkey ham

Food Control(2024)

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摘要
This study compared the quantitative polymerase chain reaction (qPCR) method combined with propidium monoazide (PMA) and the plate count (PC) method, both combined with predictive modeling, to describe the behavior of lactic acid bacteria (LAB) in vacuum-packaged sliced smoked turkey ham (STH). The PMA-qPCR method does not allow the DNA amplification of died cells but allow the amplification of viable cells, including the non-culturable. The standard curves relating quantification cycle (Cq) and log10 CFU/g demonstrated good linearity (R2 > 0.95), evidencing its accuracy and reproducibility. These curves were used to quantify Leuconostoc mesenteroides and Weissella viridescens in artificially inoculated STH samples stored at different isothermal temperatures (8, 10, 12, 16 and 20 °C). Firstly, the PMA-qPCR and PC methods were compared, and the analysis demonstrated a good correlation (R2 = 0.99) and agreement between the results. However, the PC method underestimated the quantification of W. viridescens cells by 0.76 log10 CFU/g at 8 °C, suggesting bacterial stress at this temperature, which was not observed for L. mesenteroides. In terms of growth, the maximum specific growth rate increased with rising temperature for both LAB. Predictive modeling indicated that the growth of L. mesenteroides and W. viridescens at 8 °C suggests a shelf life of approximately 4.25 days for STH based on PC data, and 4.13 days based on PMA-qPCR data. In conclusion, the PMA-qPCR method presented an advantage in terms of accuracy, especially under bacterial stress conditions, and proved to be a promising alternative for the quantification of LAB in refrigerated ready-to-eat meat products. The predictive models used were suitable for describing microbial growth, reinforcing the importance of the PMA-qPCR method in shelf life and food safety studies.
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关键词
Leuconostoc mesenteroides,Microbial growth,Molecular method,Predictive modeling,Ready-to-eat product,Weissella viridescens
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