Neural network models for growth of Salmonella serotypes in ground chicken subjected to temperature abuse during cold storage for application in HACCP and risk assessment
Author:
Affiliation:
1. United States Department of Agriculture, Agricultural Research Service Residue Chemistry and Predictive Microbiology Research Unit Center for Food Science and Technology University of Maryland Eastern Shore Room 2111 Princess Anne MD 21853 USA
Funder
U.S. Department of Agriculture
Agricultural Research Service
Publisher
Wiley
Subject
Industrial and Manufacturing Engineering,Food Science
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/ijfs.13242
Reference11 articles.
1. Consumer handling of chilled foods: Perception and practice
2. Food Safety Knowledge of Consumers and the Microbiological and Temperature Status of Their Refrigerators
3. Development and Validation of Primary, Secondary, and Tertiary Models for Growth of Salmonella Typhimurium on Sterile Chicken†
4. 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†
5. Initial Contamination of Chicken Parts with Salmonella at Retail and Cross-Contamination of Cooked Chicken with Salmonella from Raw Chicken during Meal Preparation†
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