Bayesian inference for quantifying Listeria monocytogenes prevalence and concentration in minced pork meat from presence/absence microbiological testing
- 作者：Nikolaos D. Andritsos ; Marios Mataragas ; mmat@aua.gr ; Spiros Paramithiotis ; Panagiotis N. Skandamis ; Eleftherios H. Drosinos
- 关键词：Bayesian inference ; Listeria monocytogenes ; Pork meat ; Presence/absence testing ; Prevalence ; Uncertainty
- 刊名：Food Microbiology
- 出版年：2012
- 期刊代码：100_07400020
- 类别：imm
- 出版时间：September, 2012
- 卷：31
- 期：2
- 页码：148-153
- 文件大小：259 K
摘要
The purpose of this work was to estimate the prevalence and concentration of Listeria monocytogenes in minced pork meat by the application of a Bayesian modeling approach. Samples (n聽=聽100) collected from local markets were tested for L.聽monocytogenes using in parallel the PALCAM, ALOA and RAPID鈥橪.mono selective media. Presence of the pathogen was confirmed through biochemical and molecular tests. Independent experiments (n聽=聽10) for validation purposes were performed. No L.聽monocytogenes was enumerated by direct-plating (<10聽CFU/g), though the pathogen was detected in 22%of the samples. Sensitivity and specificity varied depending on the culture method. L.聽monocytogenes concentration was estimated at 14-17聽CFU/kg. Validation showed good agreement between observed and predicted prevalence (error聽=聽鈭?.17%). The use of at least two culture media in parallel enhanced the efficiency of L.聽monocytogenes detection. Bayesian modeling may reduce the time needed to draw conclusions regarding L.聽monocytogenes presence and the uncertainty of the results obtained.