Simulation Evaluation of Power of Sampling Plans to Detect Cronobacter in Powdered Infant Formula Production

被引:2
作者
Kim, Minho [1 ]
Reyes, Gustavo A. [1 ]
Cheng, Xianbin [1 ,3 ]
Stasiewicz, Matthew J. [1 ,2 ]
机构
[1] Univ Illinois, Dept Food Sci & Human Nutr, Urbana, IL 61801 USA
[2] 103 Agr Bioproc Lab,1302 W Penn, Urbana, IL 61801 USA
[3] Archer Daniels Midland Co, Decatur, IL 62526 USA
关键词
Cronobacter; Powdered infant formula; Sampling simulation; SELECTION; RISK; MILK;
D O I
10.1016/j.jfp.2023.100115
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Cronobacter is a hazard in Powdered Infant Formula (PIF) products that is hard to detect due to localized and low-level contamination. We adapted a previously published sampling simulation to PIF sampling and benchmarked industry-relevant sampling plans across different numbers of grabs, total sample mass, and sampling patterns. We evaluated performance to detect published Cronobacter contamination profiles for a recalled PIF batch [42% prevalence, -1.8 & PLUSMN; 0.7 log(CFU/g)] and a reference, nonrecalled, PIF batch [1% prevalence, -2.4 & PLUSMN; 0.8 log(CFU/g)]. Simulating a range of numbers of grabs [n = 1-22,000 (representing testing every finished package)] with 300 g total composite mass showed that taking 30 or more grabs detected contamination reliably (<1% median probability to accept the recalled batch). Benchmarking representative sampling plans ([n = 30, mass grab = 10g], [n = 30, m = 25g], [n = 60, m = 25g], [n = 180, m = 25g]) showed that all plans would reject the recalled batch (<1% median probability to accept) but would rarely reject the reference batch (>50% median probability of acceptance, all plans). Overall, (i) systematic or stratified random sampling patterns are equal to or more powerful than random sampling of the same sample size and total sampled mass, and, (ii) taking more samples, even if smaller, can increase the power to detect contamination.
引用
收藏
页数:9
相关论文
共 39 条
[1]  
Bassett J., 2010, ILSI EUROPE REPORT S
[2]  
Berfield S., 2022, BLOOMBERG 0824
[3]  
Buchanan R. L., 2015, Food Protection Trends, V35, P228
[4]   Modelling a two-dimensional spatial distribution of mycotoxin concentration in bulk commodities to design effective and efficient sample selection strategies [J].
Casado, M. Rivas ;
Parsons, D. J. ;
Weightman, R. M. ;
Magan, N. ;
Origgi, S. .
FOOD ADDITIVES AND CONTAMINANTS PART A-CHEMISTRY ANALYSIS CONTROL EXPOSURE & RISK ASSESSMENT, 2009, 26 (09) :1298-1305
[5]  
Centers for Disease Control and Prevention (CDC), 2022, CRON POWD INF FORM I
[6]   Evaluation of the Impact of Skewness, Clustering, and Probe Sampling Plan on Aflatoxin Detection in Corn [J].
Cheng, Xianbin ;
Stasiewicz, Matthew J. .
RISK ANALYSIS, 2021, 41 (11) :2065-2080
[7]  
Codex Alimentarius Commission (CAC), 2008, COD AL COD HYG PRACT, P66
[8]   Hygienic design of food processing lines to mitigate the risk of bacterial food contamination with respect to environmental concerns [J].
Faille, Christine ;
Cunault, Charles ;
Dubois, Thomas ;
Benezech, Thierry .
INNOVATIVE FOOD SCIENCE & EMERGING TECHNOLOGIES, 2018, 46 :65-73
[9]  
Fellows P.J., 2022, Food processing technology: principles and practice
[10]  
HABRAKEN CJM, 1986, NETH MILK DAIRY J, V40, P99