Transfer coefficient models for Escherichia coli O157:H7 on contacts between beef tissue and high density polyethylene surfaces
Flores, RA and Marmer, B and Tamplin, ML and Phillips, J and Cooke, P, Transfer coefficient models for Escherichia coli O157:H7 on contacts between beef tissue and high density polyethylene surfaces, Journal of Food Protection, 69, (6) pp. 1248-1257. ISSN 0362-028X (2006) [Refereed Article]
Risk studies have identified cross-contamination during beef fabrication as a knowledge gap, particularly as to how and at what levels Escherichia coli O157:H7 transfers among meat and cutting board (or equipment) surfaces. The objectives of this study were to determine and model transfer coefficients (TCs) between E. coli O157:H7 on beef tissue and high-density polyethylene (HDPE) cutting board surfaces. Four different transfer scenarios were evaluated: (i) HDPE board to agar, (ii) beef tissue to agar, (iii) HDPE board to beef tissue to agar, and (iv) beef tissue to HDPE board to agar. Also, the following factors were studied for each transfer scenario: two HDPE surface roughness levels (rough and smooth), two beef tissues (fat and fascia), and two conditions of the initial beef tissue inoculation with E. coli O157:H7 (wet and dry surfaces), for a total of 24 treatments. The TCs were calculated as a function of the plated inoculum and of the cells recovered from the first contact. When the treatments were compared, all of the variables evaluated interacted significantly in determining the TC. An overall TC-per-treatment model did not adequately represent the reduction of the cells on the original surface after each contact and the interaction of the factors studied. However, an exponential model was developed that explained the experimental data for all treatments and represented the recontamination of the surfaces with E. coli O157:H7. The parameters for the exponential model for cross-contamination with E. coli O157:H7 between beef tissue and HDPE surfaces were determined, allowing for the use of the resulting model in quantitative microbial risk assessment.