AIMC Topic: Food Safety

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Designing a biochip following multiplex polymerase chain reaction for the detection of Salmonella serovars Typhimurium, Enteritidis, Infantis, Hadar, and Virchow in poultry products.

Journal of food and drug analysis Mar 7, 2017
Salmonella-contaminated foods, especially poultry-derived foods (eggs, chicken meat), are the major source of salmonellosis. Not only in the European Union (EU), but also in the United States, Japan, and other countries, has salmonellosis been an iss...
Serogroup Salmonella enterica Poultry Products Food Safety Lab-On-A-Chip Devices Salmonella typhimurium Food Microbiology Equipment Design Animals Salmonella Multiplex Polymerase Chain Reaction
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The locus of heat resistance (LHR) mediates heat resistance in Salmonella enterica, Escherichia coli and Enterobacter cloacae.

Food microbiology Dec 29, 2016
Enterobacteriaceae comprise food spoilage organisms as well as food-borne pathogens including Escherichia coli. Heat resistance in E. coli was attributed to a genomic island called the locus of heat resistance (LHR). This genomic island is also prese...
Thermotolerance Meat Sodium Chloride Bacterial Load Cattle Microbial Viability Escherichia coli Animals Hot Temperature Enterobacter cloacae Salmonella enterica Genomic Islands Cooking Food Safety
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Towards a Food Safety Knowledge Base Applicable in Crisis Situations and Beyond.

BioMed research international Jul 13, 2015
In case of contamination in the food chain, fast action is required in order to reduce the numbers of affected people. In such situations, being able to predict the fate of agents in foods would help risk assessors and decision makers in assessing th...
Computer Simulation Risk Assessment Incidence Food Contamination Models, Statistical Foodborne Diseases Pandemics Forecasting Databases, Factual Humans Software Bioterrorism Knowledge Bases Food Safety Hazard Analysis and Critical Control Points
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An assessment of the barriers to the consumers' uptake of genetically modified foods: a neural network analysis.

Journal of the science of food and agriculture Jun 9, 2015
BACKGROUND: This paper studies which of the attitudinal, cognitive and socio-economic factors determine the willingness to purchase genetically modified (GM) food, enabling the forecasting of consumers' behaviour in Andalusia, southern Spain. This cl...
Perception Food, Genetically Modified Consumer Behavior Food Safety Spain Adolescent Health Knowledge, Attitudes, Practice Socioeconomic Factors Female Aged Adult Male Middle Aged Risk Assessment Humans Neural Networks, Computer
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Machine learning: An effective tool for monitoring and ensuring food safety, quality, and nutrition.

Food chemistry Jun 15, 2025
The domains of food safety, quality, and nutrition are inundated with complex datasets. Machine learning (ML) has emerged as a powerful tool in food science, offering fast, accessible, and effective solutions compared with conventional methods. This ...
Nutritive Value Food Safety Humans Machine Learning Food Contamination
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Application of Bioinformatics and Machine Learning Tools in Food Safety.

Current nutrition reports May 19, 2025
PURPOSE OF REVIEW: Food safety is a fundamental challenge in public health and sustainable development, facing threats from microbial, chemical, and physical contamination. Innovative technologies improve our capacity to detect contamination early an...
Humans Machine Learning Food Contamination Disease Outbreaks Food Microbiology Foodborne Diseases Computational Biology Food Safety Proteomics
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Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples.

Scientific reports May 13, 2025
The accurate determination of mycotoxins in food samples is crucial to guarantee food safety and minimize their toxic effects on human and animal health. This study proposed the use of a support vector regression (SVR) predictive model improved by tw...
Food Safety Humans Algorithms Support Vector Machine Water Food Contamination Models, Theoretical Mycotoxins
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Machine vision combined with deep learning-based approaches for food authentication: An integrative review and new insights.

Comprehensive reviews in food science and food safety Nov 1, 2024
Food fraud undermines consumer trust, creates economic risk, and jeopardizes human health. Therefore, it is essential to develop efficient technologies for rapid and reliable analysis of food quality and safety for food authentication. Machine vision...
Algorithms Deep Learning Food Contamination Artificial Intelligence Food Analysis Food Safety Food Quality
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Application and effectiveness of artificial intelligence for the border management of imported frozen fish in Taiwan.

Journal of food and drug analysis Mar 15, 2024
In Taiwan, the number of applications for inspecting imported food has grown annually and noncompliant products must be accurately detected in these border sampling inspections. Previously, border management has used an automated border inspection sy...
United States Taiwan Fishes Humans Artificial Intelligence Animals Food Safety Fish Products
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A snail species identification method based on deep learning in food safety.

Mathematical biosciences and engineering : MBE Feb 17, 2024
In daily life, snail classification is an important mean to ensure food safety and prevent the occurrence of situations that toxic snails are mistakenly consumed. However, the current methods for snail classification are mostly based on manual labor,...
Software Deep Learning Food Safety Food
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