Linking intraspecies variability of Salmonella enterica isolates under acidic conditions to genotype.

There is a lack of information about Salmonella enterica strains under acidic conditions and their association with their genome. This study characterized intraspecies variability in the growth of 167 S. enterica isolates under two acid conditions (pH 4 and 5) and linked to the whole genome sequencing (WGS) data.

Developing a risk management framework to improve public health outcomes by enumerating and serotyping in ground turkey.

continues to be a leading cause of foodborne morbidity worldwide. A quantitative risk assessment model was developed to evaluate the impact of pathogen enumeration and serotyping strategies on public health after consumption of undercooked contaminated ground turkey in the USA. The risk assessment model predicted more than 20,000 human illnesses annually that would result in ~700 annual reported cases.

Genotypic and phenotypic quantitative microbial risk assessment model of human salmonellosis related to the consumption of chicken meat in the central region of Mexico.

Chicken meat is often associated withSalmonella entericacontamination worldwide. This study proposes a risk assessment model for human salmonellosis linked to the domestic consumption of chicken meat in the central region of Mexico, incorporating genotypic and phenotypic data. SixS.

Risk ranking of food categories associated with Salmonella enterica contamination in the central region of Mexico.

To prevent and control foodborne diseases, there is a fundamental need to identify the foods that are most likely to cause illness. The goal of this study was to rank 25 commonly consumed food products associated with Salmonella enterica contamination in the Central Region of Mexico. A multicriteria decision analysis (MCDA) framework was developed to obtain an S.

Guidance on validation of lethal control measures for foodborne pathogens in foods.

Food manufacturers are required to obtain scientific and technical evidence that a control measure or combination of control measures is capable of reducing a significant hazard to an acceptable level that does not pose a public health risk under normal conditions of distribution and storage. A validation study provides evidence that a control measure is capable of controlling the identified hazard under a worst-case scenario for process and product parameters tested. It also defines the critical parameters that must be controlled, monitored, and verified during processing.

Relationships of Water Activity and Moisture Content to the Thermal Inactivation Kinetics of in Low-Moisture Foods.

Water affects thermal inactivation kinetics of in low-moisture foods. Water activity and moisture content are both feasible predictors of heat resistance. Sorption state of food materials may affect heat resistance.

Impact of Process Temperature, Humidity, and Initial Product Moisture on Thermal Inactivation of Salmonella Enteritidis PT 30 on Pistachios during Hot-Air Heating.

Some thermal processes, such as pistachio roasting, are not yet well characterized with respect to the impact of product and process variables on Salmonella lethality. This study aimed to quantify the effects of process temperature, humidity, and initial product water activity (a), on Salmonella lethality for in-shell pistachios. In-shell pistachios were inoculated with Salmonella Enteritidis PT 30 (∼8.

Effects of Inoculation Procedures on Variability and Repeatability of Salmonella Thermal Resistance in Wheat Flour.

Limited prior research has shown that inoculation methods affect thermal resistance of Salmonella in low-moisture foods; however, these effects and their repeatability have not been systematically quantified. Consequently, method variability across studies limits utility of individual data sets and cross-study comparisons. Therefore, the objective was to evaluate the effects of inoculation methodologies on stability and thermal resistance of Salmonella in a low-moisture food (wheat flour), and the repeatability of those results, based on data generated by two independent laboratories.

Use of simulation tools to illustrate the effect of data management practices for low and negative plate counts on the estimated parameters of microbial reduction models.

In the last 20 years, the use of microbial reduction models has expanded significantly, including inactivation (linear and nonlinear), survival, and transfer models. However, a major constraint for model development is the impossibility to directly quantify the number of viable microorganisms below the limit of detection (LOD) for a given study. Different approaches have been used to manage this challenge, including ignoring negative plate counts, using statistical estimations, or applying data transformations.