Development and Validation of a Predictive Model for Growth of Salmonella Infantis in Ground Turkey.

Most retail samples (25 g) of ground turkey contain no or low levels of Salmonella. However, temperature abuse after retail can lead to spread and growth of Salmonella in the package. In addition, it can lead to levels that pose a significant risk of salmonellosis.

Poultry Food Assess Risk Model for Salmonella and Chicken Gizzards: III. Dose Consumed Step.

The Dose Consumed step of the Poultry Food Assess Risk Model (PFARM) for Salmonella and chicken gizzards was presented and compared to the Exposure Assessment step of Quantitative Microbial Risk Assessment (QMRA). The specific objectives were 1) to demonstrate the dose consumed step of PFARM for Salmonella and chicken gizzards; 2) to compare Salmonella dose consumed from cooked chicken gizzards to that from cross-contaminated and temperature-abused lettuce; 3) to determine if Salmonella dose consumed changed over time in a production chain; and 4) to compare PFARM and QMRA predictions of Salmonella dose consumed. The PFARM and QMRA were developed in an Excel notebook and simulated with @Risk.

Poultry Food Assess Risk Model for Salmonella and Chicken Gizzards: II. Illness Dose Step.

The Illness Dose (ID) step of a Poultry Food Assess Risk Model (PFARM) for Salmonella and chicken gizzards (CGs) was shown in the present study. The illness dose is the minimum dose of Salmonella consumed that causes an illness. It depends on the zoonotic potential (ZP) of Salmonella, food consumption behavior (FCB), and consumer health and immunity (CHI) or the disease triangle (DT).

Poultry Food Assess Risk Model for Salmonella and Chicken Gizzards: I. Initial Contamination.

The Poultry Food Assess Risk Model (PFARM) project was initiated in 1995 to develop data collection and modeling methods for simulating the risk of salmonellosis from poultry food produced by individual production chains. In the present study, the Initial Contamination (IC) step of PFARM for Salmonella and chicken gizzards (CG) was conducted as a case study. Salmonella prevalence (Pr), number (N), and serotype/zoonotic potential (ZP) data (n = 100) for one sample size (56 g) of CG were collected at meal preparation (MP), and then Monte Carlo simulation (MCS) was used to obtain data for other sample sizes (112, 168, 224, 280 g).

Monte Carlo Simulation Model for Predicting Salmonella Contamination of Chicken Liver as a Function of Serving Size for Use in Quantitative Microbial Risk Assessment.

Abstract: The first step in quantitative microbial risk assessment (QMRA) is to determine the distribution of pathogen contamination among servings of the food in question at some point in the farm-to-table chain. In the present study, the distribution of Salmonella contamination among servings of chicken liver for use in the QMRA was determined at meal preparation. Salmonella prevalence (P), most probable number (MPN, N), and serotype for different serving sizes were determined by use of a combination of five methods: (i) whole sample enrichment; (ii) quantitative PCR; (iii) culture isolation; (iv) serotyping; and (v) Monte Carlo simulation.

A multiple therapy hypothesis for treatment of COVID-19 patients.

The coronavirus disease 2019 (COVID-19) pandemic, which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has killed more than one million people as of October 1, 2020. Consequently, a search is on for a treatment that can bring the pandemic to an end. However, treatments (vaccine, antiviral, plasma) that are directed at specific viral proteins (RNA polymerase, spike proteins) may not work well against all strains of the virus.

Short-term and long-term effects of pathogen reduction interventions on salmonellosis from whole chickens.

The current study was undertaken to evaluate short-term and long-term effects of pathogen reduction interventions on food safety. This was accomplished using a model that predicts risk of salmonellosis from whole chickens produced by different scenarios. Interventions investigated were a 50% pathogen reduction before retail (PR), a 50% pathogen reduction at serving by consumer education (CE), and a 75% pathogen reduction by PR + CE.

General regression neural network model for behavior of Salmonella on chicken meat during cold storage.

Unlabelled: A study was undertaken to investigate and model behavior of Salmonella on chicken meat during cold storage at constant temperatures. Chicken meat (white, dark, or skin) portions (0.75 cm(3)) were inoculated with a single strain of Salmonella Typhimurium DT104 (2.

Growth of Salmonella Typhimurium DT104 at 30°C is not affected by anatomical location on the chicken carcass.

Development of models for growth of Salmonella in the chicken food matrix is time-consuming and expensive. The current study was undertaken to examine growth of Salmonella on different anatomical locations of the chicken carcass. The purpose was to determine whether anatomical location should be included as an independent variable in predictive models for chicken.

Extrapolation of a predictive model for growth of a low inoculum size of Salmonella Typhimurium DT104 on chicken skin to higher inoculum sizes.

Validation of model predictions for independent variables not included during model development can save time and money by identifying conditions for which new models are not needed. A single strain of Salmonella Typhimurium DT104 was used to develop a general regression neural network (GRNN) model for growth of a low inoculum size (0.9 log) on chicken skin with native microflora as a function of time (0 to 8 h) and temperature (20 to 45°C).

Development and validation of a predictive microbiology model for survival and growth of Salmonella on chicken stored at 4 to 12 °C.

Salmonella spp. are a leading cause of foodborne illness. Mathematical models that predict Salmonella survival and growth on food from a low initial dose, in response to storage and handling conditions, are valuable tools for helping assess and manage this public health risk.

Survival of Campylobacter jejuni and Campylobacter coli on retail broiler meat stored at -20, 4, or 12 degrees C and development of Weibull models for survival.

Survival of Campylobacter jejuni and Campylobacter coli isolated from broiler meat was investigated and modeled on retail breast meat. Meat portions were inoculated with C. jejuni or C.

General regression neural network and monte carlo simulation model for survival and growth of salmonella on raw chicken skin as a function of serotype, temperature, and time for use in risk assessment.

A general regression neural network (GRNN) and Monte Carlo simulation model for predicting survival and growth of Salmonella on raw chicken skin as a function of serotype (Typhimurium, Kentucky, and Hadar), temperature (5 to 50 degrees C), and time (0 to 8 h) was developed. Poultry isolates of Salmonella with natural resistance to antibiotics were used to investigate and model survival and growth from a low initial dose (<1 log) on raw chicken skin. Computer spreadsheet and spreadsheet add-in programs were used to develop and simulate a GRNN model.

Development and validation of a predictive model for Listeria monocytogenes Scott A as a function of temperature, pH, and commercial mixture of potassium lactate and sodium diacetate.

The objective of this study was to develop and validate secondary models that can predict growth parameters of L. monocytogenes Scott A as a function of concentrations (0-3%) of a commercial potassium lactate (PL) and sodium diacetate (SDA) mixture, pH (5.5-7.

Prevalence and antimicrobial resistance of Salmonella recovered from processed poultry.

This study was conducted to determine the prevalence and antimicrobial resistance of Salmonella isolates recovered from processed poultry. Four hundred eighty pre- and postchill whole broiler chicken carcasses were collected from a poultry processing plant between July 2004 and June 2005. Water samples also were collected at the entrance and exit of the chiller.

A quantitative risk assessment model for Salmonella and whole chickens.

Existing data and predictive models were used to define the input settings of a previously developed but modified quantitative risk assessment model (QRAM) for Salmonella and whole chickens. The QRAM was constructed in an Excel spreadsheet and was simulated using @Risk. The retail-to-table pathway was modeled as a series of unit operations and associated pathogen events that included initial contamination at retail, growth during consumer transport, thermal inactivation during cooking, cross-contamination during serving, and dose response after consumption.

Development and validation of a tertiary simulation model for predicting the potential growth of Salmonella typhimurium on cooked chicken.

The growth of Salmonella typhimurium (ATCC 14028) on the surface of autoclaved ground chicken breast and thigh burgers incubated at constant temperatures from 8 to 48 degrees C in 2 degrees C increments was investigated and modeled. Growth curves at each temperature were fit to a two-phase linear primary model to determine lag time (lambda) and specific growth rate (mu). Growth of S.