1a. Objectives (from AD-416):
1: Derive data and model Salmonella serotype changes in movement from incoming product, through whole bird processing, post-carcass cut-up, to final product. 1A. Develop an exposure assessment (EA) model for Salmonella serotype changes in movement from post-carcass cut-up to final product (cooked chicken parts). 2: Study the survival characteristics for Salmonella serotypes: are there serotypes that survive interventions on farm, in the processing plant and/or final product. 2A. Use the EA model to evaluate efficacy of a plastic chicken house floor for Salmonella serotype control. 3: Derive additional predictive microbiology data of multi-drug resistant (MDR) Salmonella spp., such as Salmonella Typhimurium DT104. 3A. Use MDR Salmonella serotypes to develop the predictive microbiology models needed for the EA model.
1b. Approach (from AD-416):
Predictive microbiology models for contamination, growth and survival of Salmonella serotypes on chicken parts will be developed and linked to form an exposure assessment model that predicts changes in incidence and number of Salmonella serotypes on chicken parts produced by different farm-to-table scenarios. The exposure assessment model will predict consumer exposure to Salmonella serotypes that survive cooking of chicken parts and that cross-contaminate cooked chicken parts during serving. The exposure assessment model will be designed to evaluate effects of interventions on consumer exposure to Salmonella serotypes of chicken origin. The intervention evaluated in the project will be a plastic chicken house floor that has potential to reduce Salmonella serotypes entering the processing plant and surviving on chicken parts after final processing.
3. Progress Report:
The ultimate goal of this project is to develop a computer model that predicts the risk of exposure of consumers to Salmonella on edible parts of the chicken carcass before they are shipped from the processing plant. This exposure assessment model will help the U.S. Department of Agriculture, Food Safety and Inspection Service and the chicken industry to better identify higher risk lots of chicken before they cause a public health crisis. This year a prototype of the model was developed and is being used as a research framework for acquisition of data and development of sub-models that will improve its predictions. A focus of the data collection efforts this year was the investigation and modeling of the survival and growth of Salmonella on chicken meat during cold storage. Other areas of investigation were to acquire data that define the levels and distribution of Salmonella among edible parts of the whole chicken carcass and to acquire data that define how readily Salmonella are transferred from raw chicken to cooked chicken during meal preparation. When completed, the model will predict how the number and types of Salmonella change on edible chicken parts as the move from the processing plant through cold storage, meal preparation, cooking and cooling and to the consumer’s table. The model will also be used in future years of the project to evaluate the ability of the chicken industry to reduce consumer exposure to Salmonella by implementation of intervention methods on-the-farm and in-the-processing plant, such as the use of a new chicken house design with a plastic floor.
1. Salmonella on chicken parts. How many Salmonella are on my favorite piece of chicken? The number of Salmonella on chicken wings, chicken breast fillets, chicken thighs and chicken drumsticks was investigated by an ARS researcher at Princess Anne, Maryland. He found that most pieces of chicken (97%) contained no Salmonella and those that did have Salmonella only had a few cells (i.e. 1 or 3 cells). These results indicate that the chicken examined posed a very low risk of foodborne illness from Salmonella.
2. Salmonella and the cutting board. Sometimes consumers use the cutting board and utensils used to prepare raw chicken for cooking without first washing them to prepare other foods. This could result in the transfer of Salmonella from raw chicken to other foods and consumption of this pathogen by consumers. This scenario was investigated by an ARS researcher at Princess Anne, Maryland and it was found that on only 1 out of 57 occasions was Salmonella transferred from raw chicken to cooked chicken during meal preparation when the cutting board and utensils were not washed before cutting the cooked chicken. On that one occasion where Salmonella was transferred only a single cell was found on the cooked chicken. These results illustrate that when the chicken company provides the consumer with chicken containing low levels of Salmonella that even when the consumer makes a food handling mistake, the risk of getting foodborne illness is low.
3. Salmonella and cold chicken. Although chicken meat may contain low levels of Salmonella when purchased, if the consumer stores the chicken meat in a refrigerator at an improper temperature for an extended period of time, the Salmonella could grow to high and dangerous levels. An ARS researcher at Princess Anne, Maryland investigated this possibility and developed a model for predicting growth of Salmonella on different types of chicken meat during cold storage. The model predicts that Salmonella grows best on thigh meat, second best on chicken skin, and third best on breast meat. Salmonella survived and did not grow on chicken meat stored at temperatures from -8C (17.6F) to 10C (50F) for up to 8 days. However, at temperatures from 11C (51.8F) to 16C (60.8F), Salmonella grew on chicken meat with the amount of growth increasing as time of storage (up to 8 days) and temperature of storage increased. In fact, after 2 days of storage at 16C, one cell of Salmonella became 1,383 cells on thigh meat, 164 cells on chicken skin, and 31 cells on breast meat. The model will be incorporated into the ARS, Pathogen Modeling Program (http://portal.arserrc.gov/) where it can be used by consumer’s to help them decide whether or not their chicken is safe to eat after extended time in the refrigerator.Oscar, T.P. 2011. Extrapolation of a predictive model for growth of a low inoculum size of Salmonella typhimurium DT104 on chicken skin to higher inoculum sizes. Journal of Food Protection. 74(10)1630-1638.