AIMC Topic: Food Microbiology

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Integrating MALDI-TOF Mass Spectrometry with Machine Learning Techniques for Rapid Antimicrobial Resistance Screening of Foodborne Bacterial Pathogens.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
Although MALDI-TOF mass spectrometry (MS) is considered as the gold standard for rapid and cost-effective identification of microorganisms in routine laboratory practices, its capability for antimicrobial resistance (AMR) detection has received limit...
Drug Resistance, Bacterial Microbial Sensitivity Tests Machine Learning Anti-Bacterial Agents Foodborne Diseases Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Campylobacter Bacteria Food Microbiology Humans
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Optical sensing for real-time detection of food-borne pathogens in fresh produce using machine learning.

Science progress Jan 1, 2024
Contaminated fresh produce remains a prominent catalyst for food-borne illnesses, prompting the need for swift and precise pathogen detection to mitigate health risks. This paper introduces an innovative strategy for identifying food-borne pathogens ...
Humans Machine Learning Foodborne Diseases Vegetables Food Safety Food Contamination Food Microbiology Salmonella Escherichia coli
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Using a Six Sigma Fishbone Analysis Approach To Evaluate the Effect of Extreme Weather Events on Salmonella Positives in Young Chicken Slaughter Establishments.

Journal of food protection Dec 1, 2016
A six sigma fishbone analysis approach was used to develop a machine learning model in SAS, Version 9.4, by using stepwise linear regression. The model evaluated the effect of a wide variety of variables, including slaughter establishment operational...
Total Quality Management Humans Salmonella Animals Food Contamination Chickens Weather Food Microbiology Abattoirs
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Automated analysis of food-borne pathogens using a novel microbial cell culture, sensing and classification system.

The Analyst Feb 21, 2016
We hereby report the design and implementation of an Autonomous Microbial Cell Culture and Classification (AMC(3)) system for rapid detection of food pathogens. Traditional food testing methods require multistep procedures and long incubation period,...
Automation Electrochemistry Food Microbiology Quality Control Cell Culture Techniques Staphylococcus epidermidis Neural Networks, Computer Artificial Intelligence Support Vector Machine Escherichia coli Humans
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Fermentation optimization of goat milk with Lactobacillus acidophilus and Bifidobacterium bifidum by Box-Behnken design.

Acta scientiarum polonorum. Technologia alimentaria Jan 1, 2016
BACKGROUND: Goat milk is only limited to the processing of goat milk powder and liquid milk, the products are mainly about milk powder and a few of them are made as milk tablet. Therefore, the study of probiotic goat milk will have great significance...
Animals Food Microbiology Food Handling Bifidobacterium bifidum Colony Count, Microbial Taste Temperature Lactobacillus acidophilus Yogurt Fermentation Milk Probiotics Goats
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Neural Network Model for Survival and Growth of Salmonella enterica Serotype 8,20:-:z6 in Ground Chicken Thigh Meat during Cold Storage: Extrapolation to Other Serotypes.

Journal of food protection Oct 1, 2015
Mathematical models that predict the behavior of human bacterial pathogens in food are valuable tools for assessing and managing this risk to public health. A study was undertaken to develop a model for predicting the behavior of Salmonella enterica ...
Food Storage Salmonella enterica Cold Temperature Humans Neural Networks, Computer Food Microbiology Colony Count, Microbial Animals Chickens Meat Serogroup Poultry Food Contamination
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