4.4 Article

Prevalence and Counts of Salmonella and Enterohemorrhagic Escherichia coli in Raw, Shelled Runner Peanuts

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JOURNAL OF FOOD PROTECTION
卷 76, 期 10, 页码 1668-1675

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INT ASSOC FOOD PROTECTION
DOI: 10.4315/0362-028X.JFP-13-047

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Three major outbreaks of salmonellosis linked to consumption of peanut butter during the last 6 years have underscored the need to investigate the potential sources of Salmonella contamination in the production process flow. We conducted a study to determine the prevalence and levels of Salmonella in raw peanuts. Composite samples (1,500 g, n = 8) of raw, shelled runner peanuts representing the crop years 2009, 2010, and 2011 were drawn from 10,162 retained 22-kg lot samples of raw peanuts that were negative for aflatoxin. Subsamples (350 g) were analyzed for the presence of Salmonella and enterohemorrhagic Escherichia coli. Salmonella was found in 68 (0.67%) of 10,162 samples. The highest prevalence rate (P < 0.05) was for 2009 (1.35%) compared with 2010 (0.36%) and 2011 (0.14%). Among four runner peanut market grades (Jumbo, Medium, No. 1, and Splits), Splits had the highest prevalence (1.46%; P < 0.05). There was no difference (P > 0.05) in the prevalence by region (Eastern versus Western). Salmonella counts in positive samples (most-probable-number [MPN] method) averaged 1.05 (range, 0.74 to 5.25) MPN per 350 g. Enterohemorrhagic E. coli was found in only three samples (0.030%). Typing of Salmonella isolates showed that the same strains found in Jumbo and Splits peanuts in 2009 were also isolated from Splits in 2011. Similarly, strains isolated in 2009 were also isolated in 2010 from different peanut grades. These results indicated the persistence of environmental sources throughout the years. For five samples, multiple isolates were obtained from the same sample that had different pulsed-field gel electrophoresis types. This multistrain contamination was primarily observed in Splits peanuts, in which the integrity of the kernel is usually compromised. The information from the study can be used to develop quantitative microbial risk assessments models.

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