AIMC Topic: Food Contamination

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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...
Neural Networks, Computer Machine Learning Food Contamination Hyperspectral Imaging Deep Learning Food Safety Humans Electronic Nose
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Mapping acrylamide content in potato chips using near-infrared hyperspectral imaging and chemometrics.

Food chemistry Mar 9, 2025
This study investigated the potential of near-infrared hyperspectral imaging (NIR-HSI) for the prediction of acrylamide content in potato chips. A total of 300 tubers from two potato varieties (Agria and Jaerla) grown in two seasons and processed und...
Plant Tubers Chemometrics Least-Squares Analysis Hyperspectral Imaging Spectroscopy, Near-Infrared Cooking Acrylamide Support Vector Machine Solanum tuberosum Food Contamination
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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 Contamination Silver Food Additives Food Safety Metal Nanoparticles Limit of Detection
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Origin traceability of agricultural products: A lightweight collaborative neural network for spectral information processing.

Food research international (Ottawa, Ont.) Mar 6, 2025
The natural conditions of various regions, including climate, soil, and water quality, significantly influence the nutrient composition and quality of agricultural products. Identifying the origin of agricultural products can prevent adulteration, im...
Arachis Food Quality Oryza Crops, Agricultural Agriculture Neural Networks, Computer Food Contamination Food Analysis
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Prediction of the packaging chemical migration into food and water by cutting-edge machine learning techniques.

Scientific reports Mar 6, 2025
Chemicals transfer from the packaging materials and their dissolution in food and water can create health risks. Due to the costly and time-intensive nature of experimental measurements, employing artificial intelligence (AI) methodologies is benefic...
Food Packaging Food Contamination Algorithms Water Neural Networks, Computer Machine Learning
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A Surface-Enhanced Raman Spectroscopy Platform Integrating Dual Signal Enhancement and Machine Learning for Rapid Detection of Veterinary Drug Residues in Meat Products.

ACS applied materials & interfaces Mar 2, 2025
The detection and quantification of veterinary drug residues in meat remain a significant challenge due to the complex background interference inherent to the meat matrix, which compromises the stability and accuracy of spectroscopic analysis. This s...
Drug Residues Veterinary Drugs Animals Spectrum Analysis, Raman Metal Nanoparticles Meat Products Food Contamination Machine Learning
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Measuring the Level of Aflatoxin Infection in Pistachio Nuts by Applying Machine Learning Techniques to Hyperspectral Images.

Sensors (Basel, Switzerland) Mar 2, 2025
This paper investigates the use of machine learning techniques on hyperspectral images of pistachios to detect and classify different levels of aflatoxin contamination. Aflatoxins are toxic compounds produced by moulds, posing health risks to consume...
Machine Learning Hyperspectral Imaging Food Contamination Pistacia Nuts Aflatoxins
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Machine Learning-Assisted Chemical Tongues Based on Dual-channel Inclusion Complexes for Rapid Identification of Nonsteroidal Anti-inflammatory Drugs in Food.

ACS sensors Feb 24, 2025
The improper application of nonsteroidal anti-inflammatory drugs (NSAIDs) presents significant health hazards via vector food contamination. A critical limitation of these traditional existing approaches is their inability to concurrently discern and...
Bridged-Ring Compounds Anti-Inflammatory Agents, Non-Steroidal Imidazolidines Spectrometry, Fluorescence Food Contamination Food Analysis Machine Learning Macrocyclic Compounds Imidazoles Animals Milk Heterocyclic Compounds, 2-Ring
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Ultrafast on-site adulteration detection and quantification in Asian black truffle using smartphone-based computer vision.

Talanta Feb 14, 2025
Asian black truffle Tuber sinense (BT) is a premium edible fungus with medicinal value, but it is often prone to adulteration. This study aims to develop a fast, non-destructive, automatic, and intelligent method for identifying BT. A novel lightweig...
Neural Networks, Computer Smartphone Food Contamination Ascomycota
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Enhanced authentication of organic milk using MALDI-TOF MS with combined lipid-peptide fingerprinting and machine learning integration.

Food chemistry Feb 10, 2025
This study introduces a method for authenticating organic milk and determining its geographic region using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Both lipids and peptides were analyzed, and their ...
Machine Learning Animals Peptides Lipids Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Milk Cattle Food Contamination Food, Organic Peptide Mapping
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