Distribution-based maximum likelihood estimation methods are preferred for estimating Salmonella concentration in chicken when contamination data are highly left-censored

文献类型： 外文期刊

第一作者： Sun, Tianmei

作者： Sun, Tianmei;Liu, Yangtai;Qin, Xiaojie;Lin, Zijie;Dou, Xin;Wang, Xiang;Dong, Qingli;Gao, Shufei;Zhang, Hui

作者机构：

关键词： Foodborne pathogen; Limit of detection; Count distribution; Maximum likelihood estimation; Multiple imputation method

期刊名称：FOOD MICROBIOLOGY （ 影响因子：5.3； 五年影响因子：5.5 ）

ISSN： 0740-0020

年卷期： 2023 年 113 卷

页码：

收录情况： SCI

摘要： Salmonella is a common chicken-borne pathogen that causes human infections. Data below the detection limit, referred to as left-censored data, are frequently encountered in the detection of pathogens. The approach of handling the censored data was regarded to affect the estimation accuracy of microbial concentration. In this study, a set of Salmonella contamination data was collected from chilled chicken samples using the most probable number (MPN) method, which consisted of 90.42% (217/240) non-detect values. Two simulated datasets with fixed censoring degrees of 73.60% and 90.00% were generated based on the real-sampling Salmonella dataset for comparison. Three methodologies were applied for handling left-censored data: (i) substitution with different alternatives, (ii) the distribution-based maximum likelihood estimation (MLE) method, and (iii) the multiple imputation (MI) method. For each dataset, the negative binomial (NB) distribution-based MLE and zero-modified NB distribution-based MLE were preferable for highly censored data and resulted in the least root mean square error (RMSE). Replacing the censored data with half the limit of quantification was the next best method. The mean concentration of Salmonella monitoring data estimated by the NB-MLE and zero-modified NB-MLE methods was 0.68 MPN/g. This study provided an available statistical method for handling bacterial highly left-censored data.

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