AIMC Topic: Food Contamination

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Assessment of POPs in foods from western China: Machine learning insights into risk and contamination drivers.

Environment international Apr 11, 2025
Persistent organic pollutants (POPs), including PCDD/Fs, PCBs, and PBDEs, are major environmental and food safety concerns due to their bioaccumulative and toxic properties. However, comprehensive research on the concentrations and influencing factor...
Polychlorinated Biphenyls Persistent Organic Pollutants Polychlorinated Dibenzodioxins Halogenated Diphenyl Ethers Meat Eggs Fishes Environmental Monitoring Food Contamination Swine Machine Learning China Animals Cattle Risk Assessment
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Aflatoxin detection in naturally contaminated peanuts based on vision transformer and multi-scale convolutional fusion.

Food chemistry Apr 9, 2025
Aflatoxin is a highly toxic substance found in peanuts, posing a serious threat to human health. To address this issue, an improved 1D-MCFViT model combining the Vision Transformer with multi-scale convolutional fusion is proposed to detect aflatoxin...
Arachis Aflatoxins Deep Learning Machine Learning Food Contamination
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A fluorescence probe-smartphone-machine learning integrated platform for the visual and intelligent detection of imidacloprid in agricultural products.

Food chemistry Apr 3, 2025
Imidacloprid is a pesticide commonly used in agriculture production. Portable and accurate detection of imidacloprid residues is of great significance to food safety and human health. Herein, a red-emitting rare earth complex (Eu-IMDC) probe is prepa...
Neural Networks, Computer Oryza Insecticides Neonicotinoids Food Contamination Limit of Detection Nitro Compounds Fluorescent Dyes Machine Learning Pesticide Residues Smartphone
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Advancements in small molecule fluorescent probes for the detection of formaldehyde in environmental and food samples: A comprehensive review.

Food chemistry Mar 26, 2025
Formaldehyde (FA), a hazardous substance with carcinogenicity and mutagenicity, necessitates sensitive and accurate detection methods for protecting public health and the environment. While numerous reviews have explored FA fluorescent probes, the cu...
Humans Animals Environmental Monitoring Fluorescent Dyes Environmental Pollutants Food Contamination Food Analysis Formaldehyde
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Partial least squares methods in open-source software for identification of adulterated creatine using infrared spectroscopy.

Food chemistry Mar 22, 2025
Creatine is one of the most consumed food supplements by people who practice physical activity. We developed a new methodology by associating Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) with multivariate analyses for screening a...
Software Least-Squares Analysis Discriminant Analysis Creatine Spectroscopy, Fourier Transform Infrared Food Contamination Dietary Supplements
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Deep Learning-Based Detection of Aflatoxin B1 Contamination in Almonds Using Hyperspectral Imaging: A Focus on Optimized 3D Inception-ResNet Model.

Toxins Mar 22, 2025
Aflatoxin B1, a toxic carcinogen frequently contaminating almonds, nuts, and food products, poses significant health risks. Therefore, a rapid and non-destructive detection method is crucial to detect aflatoxin B1-contaminated almonds to ensure food ...
Aflatoxin B1 Food Contamination Deep Learning Prunus dulcis Nuts Support Vector Machine Hyperspectral Imaging
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Enhancing the application of near-infrared spectroscopy in grain mycotoxin detection: An exploration of a transfer learning approach across contaminants and grains.

Food chemistry Mar 17, 2025
Cereals are a primary source of sustenance for humanity. Monitoring, controlling, and preventing mycotoxins in cereals are vital for ensuring the safety of the cereals and their derived products. This study introduces transfer learning strategies int...
Mycotoxins Arachis Spectroscopy, Near-Infrared Food Contamination Triticum Edible Grain
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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...
Hyperspectral Imaging Food Safety Electronic Nose Humans Deep Learning Neural Networks, Computer Food Contamination Machine Learning
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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...
Spectroscopy, Near-Infrared Least-Squares Analysis Cooking Chemometrics Support Vector Machine Acrylamide Food Contamination Plant Tubers Hyperspectral Imaging Solanum tuberosum
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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...
Food Safety Limit of Detection Silver Food Additives Food Contamination Metal Nanoparticles Machine Learning Spectrum Analysis, Raman
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