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An Enumeration Method and Sampling Plan for Mapping the Number and Distribution of Salmonella on the Chicken Carcass Thomas P. Oscar, Agricultural Research.

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Presentation on theme: "An Enumeration Method and Sampling Plan for Mapping the Number and Distribution of Salmonella on the Chicken Carcass Thomas P. Oscar, Agricultural Research."— Presentation transcript:

1 An Enumeration Method and Sampling Plan for Mapping the Number and Distribution of Salmonella on the Chicken Carcass Thomas P. Oscar, Agricultural Research Service, USDA, Room 2111, Center for Food Science and Technology, University of Maryland Eastern Shore, Princess Anne, MD 21853; 410- 651-6062; 410-651-8498 (fax); Thomas.Oscar@ars.usda.gov INTRODUCTION Mapping the number and distribution of Salmonella on the chicken carcass will help guide better design of processing procedures to reduce or eliminate this human pathogen from chicken. The carcass rinse method coupled with the most probable number method is the most common approach used to enumerate Salmonella contamination on the chicken carcass. However, the carcass rinse method does not recover all the Salmonella on the chicken carcass 1. Incubation of the whole carcass in buffered peptone water (BPW) for 24 h results in increased recovery of Salmonella 2 and is equivalent to 1,440 consecutive carcass rinses. Similar to impedance methods for enumeration of bacteria 3, there should be an inverse relationship between the number of Salmonella and detection time (DT) during incubation of whole carcasses or parts in BPW for 24 h. Drop plating is an inexpensive method for detection and enumeration of pathogens in food sample incubations 4. OBJECTIVE To develop a low cost method and sampling plan for mapping the number and distribution of Salmonella on the chicken carcass. MATERIALS AND METHODS Organism. A multiple antibiotic resistant (MAR) strain (ATCC 700408) of Salmonella Typhimurium DT104 was used for method development. Chicken preparation. Cornish game hens were purchased at retail and were processed into 12 parts, as an initial sampling plan for future mapping studies: Chicken part inoculation and incubation. Chicken parts were spot inoculated (2 or 5 ul) with 0 to 6 log 10 S. Typhimurium DT104 followed by incubation in 300 ml of BPW for 24 h at 40C and 100 rpm: At 1, 2, 3, 4, 5, 6, 7, 8 and 24 h of incubation, 2 ul of BPW was removed and drop plated onto XLH-CATS, which contained four antibiotics (i.e. chloramphenicol, ampicillin, tetracycline and streptomycin; 25 ug/ml each). Enumeration method. Drop plates were incubated for a standard time (24 h) and temperature (38C). The image on the drop plate was captured and the number of pixels per drop was determined using a monochrome image and Image J software from NIH 5. The resulting density curves were fit to a sigmoid equation: Y = Bottom + (Top – Bottom)/(1 + 10 (X50 – X) ) where Bottom was fixed at zero pixels per drop, Top was constrained to being shared among the 12 curves and X 50 was the time (X) when the curve reached 50% of maximum, which was DT in hours. Standard curve. A standard curve for enumeration was generated by graphing the initial log 10 number (N o ) of S. Typhimurium DT104 inoculated as a function of DT and fitting (Prism software) the data to a linear equation: N o = a + (b* DT) where a was the Y intercept and b was the slope. In addition, the curve-fit generated a 95% prediction interval (PI) that provided stochastic results for N o and accounted for the variation of DT among trials. RESULTS At each sampling time, one drop (2 ul) from each chicken part (n = 12) incubation was inoculated onto XLH-CATS. Here are typical results for one sampling time (i.e. 5 h): The amount of growth within a drop on XLH-CATS depended on N o and time of incubation of the chicken part in BPW: When graphed as a function of time, the number of pixels per drop fit well (r 2 = 0.966) to a sigmoid equation: Drop Plate – Detection Time Assay Progression 5 Hours 6 Hours 7 Hours When N o was graphed as a function of DT, a linear standard curve was obtained, which included a 95% PI, and had high goodness-of-fit (r 2 = 0.968): The range of the assay was 0 to 6 log 10 per chicken part: DISCUSSION Gibson 6 used a commercial impedance system (Bactometer) to enumerate MAR (rifampicin and nalidixic acid) strains of Salmonella Thompson, Stanley and Infantis inoculated into culture medium and pork slurries. The linear correlation in broth between N o and DT was -0.959 and in pork slurry was -0.935. In comparison, a linear correlation of -0.984 was obtained in the current study between N o and DT for whole chicken parts by the drop plate method. In the study of Gibson 6, 95% of the N o in broth were within ± 1 log 10 of the standard curve, whereas 95% of the N o for pork slurry were within ± 1.65 log 10 of the standard curve. In the current study, 95% of the N o for whole chicken parts were within ± 0.61 log 10 of the standard curve. These results indicate that DT is variable among food samples with the same N o and that the deviation of N o from the standard curve was less in the current study for the drop plate method than in the study of Gibson 6 for the impedance method. REFERENCES 1.Lillard, H. S. 1988. J. Food Prot. 51:405-408. 2.Simmons, M. et al. 2003. J. Food Prot. 66:446-450. 3.Wawerla, M. et al. 1999. J. Food Prot. 62:1488-1496. 4.Chen, C. et al. 2003. J. Microbiol. Methods 55:475-479. 5. Available at: rsb.info.nih.gov/ij/. 6.Gibson, A.M. 1988. Lett. Appl. Microbiol. 6:89-92. ACKNOWLEDGMENTS The author would like to thank Jaci Ludwig of ARS and Hannah Bailey and Ebonie Emelle of UMES for their outstanding technical assistance on this project. N o = 7.78 ± 0.61 – (0.995*DT)


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