AIMC Topic: Food Safety

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Nondestructive freshness recognition of chicken breast meat based on deep learning.

Scientific reports Jul 29, 2025
Identifying chicken breast freshness is an important component of poultry food safety. Traditional methods for chicken breast freshness recognition suffer from issues such as high cost, difficulty in recognition, and low efficiency. In this study, th...
Algorithms Animals Food Microbiology Meat Food Safety Deep Learning Chickens
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CRISPR/Cas-Based Biosensing Strategies for Non-Nucleic Acid Contaminants in Food Safety: Status, Challenges, and Perspectives.

Journal of agricultural and food chemistry Jul 9, 2025
Non-nucleic acid targets (non-NATs), such as heavy metals, toxins, and pesticide residues, pose critical threats to food safety. Although CRISPR/Cas systems were initially developed for nucleic acid detection, recent advances have enabled their adapt...
Metals, Heavy Nucleic Acids Food Safety Food Contamination CRISPR-Cas Systems Biosensing Techniques
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Multifunctional Hydrogen-Bonded Organic Frameworks for Intelligent Anti-Counterfeiting and Food Safety Monitoring.

ACS applied materials & interfaces May 28, 2025
In an era of increasing digital threats and product counterfeiting, this study introduces MA-IPA@NPA, a groundbreaking hydrogen-bonded organic framework (HOF) material designed for advanced anticounterfeiting applications. This innovative material sh...
Food Safety Hydrogen Bonding Food Contamination Gallic Acid Fraud Nanofibers Polyvinyl Alcohol
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Smartphone-integrated Nanozyme approaches for rapid and on-site detection: Empowering smart food safety.

Food chemistry May 7, 2025
Smartphone-integrated nanozyme technologies (S-INTs) have emerged as a promising solution for rapid, on-site food safety analysis, addressing the detection of foodborne pathogens, contaminants, and hazards. While the applications of nanozymes in food...
Smartphone Biosensing Techniques Nanotechnology Food Safety Food Contamination Humans Animals
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Hyperspectral Imaging and Deep Learning for Quality and Safety Inspection of Fruits and Vegetables: A Review.

Journal of agricultural and food chemistry Apr 16, 2025
Quality inspection of fruits and vegetables linked to food safety monitoring and quality control. Traditional chemical analysis and physical measurement techniques are reliable, they are also time-consuming, costly, and susceptible to environmental a...
Food Quality Food Inspection Fruit Quality Control Hyperspectral Imaging Food Safety Vegetables Humans Deep Learning
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Progress in machine learning-supported electronic nose and hyperspectral imaging technologies for food safety assessment: A review.

Food research international (Ottawa, Ont.) Mar 17, 2025
The growing concern over food safety, driven by threats such as food contaminations and adulterations has prompted the adoption of advanced technologies like electronic nose (e-nose) and hyperspectral imaging (HSI), which are increasingly enhanced by...
Humans Neural Networks, Computer Deep Learning Food Contamination Machine Learning Electronic Nose Hyperspectral Imaging Food Safety
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An ultra-sensitive, intelligent platform for food safety monitoring: Label-free detection of illegal additives using self-assembled SERS substrates and machine learning.

Food chemistry Mar 7, 2025
To overcome the limitations of SERS in food safety monitoring, particularly significant interference from citrate ions, this study introduces an intelligent SERS-based platform for food safety monitoring. The platform utilizes sodium borohydride to a...
Machine Learning Spectrum Analysis, Raman Food Additives Food Safety Limit of Detection Food Contamination Silver Metal Nanoparticles
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Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.

Journal of food protection Feb 6, 2025
While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to help improve food safety, the development and deployment of these models in the food safety domain are by and large lacking. The absence of publicly a...
Benchmarking Food Safety Food Contamination Food Microbiology Humans Animals Chickens Machine Learning Soil Microbiology Databases, Factual
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Research on Risk Prediction of Condiments Based on Gray Correlation Analysis - Deep Neural Networks.

Journal of food protection Nov 27, 2024
Food safety is directly related to the health of the public, and the safety of condiments is also of great significance. In this study, a risk assessment model for condiments based on gray correlation analysis was established by using publicly availa...
Food Safety Risk Assessment Soy Foods Humans Condiments Neural Networks, Computer China
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Recommendations for the Development of Artificial Intelligence Applications for the Retail Level.

Journal of food protection Nov 13, 2024
Some of the early applications of artificial intelligence (AI) for food safety appear to be intended for use at the level of manufacturing and distribution. Artificial intelligence applications to facilitate foodborne illness outbreak investigations,...
Food Safety Food Contamination Foodborne Diseases Humans Artificial Intelligence
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