AIMC Topic: Food Contamination
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Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation.
Journal of hazardous materials
Aug 10, 2024
Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing's central urban area. Results indicated...
A MOF-on-MOF heterostructure ratiometric/colorimetric dual-mode fluorescence sensor based on support vector machine for detecting tetracyclines in animal-derived foods.
Food chemistry
Jul 31, 2024
The misuse of tetracyclines in livestock production poses significant health risks. Thus, establishing convenient detection methods to replace complex laboratory tests for food safety is crucial. In this study, a heterostructure Zn-BTC/IRMOF-3 (denot...
Application of untargeted liquid chromatography-mass spectrometry to routine analysis of food using three-dimensional bucketing and machine learning.
Scientific reports
Jul 18, 2024
For the detection of food adulteration, sensitive and reproducible analytical methods are required. Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) is a highly sensitive method that can be used to obtain analytical finger...
Machine learning trained poly (3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles for precise monitoring of nitrite from pickled vegetables.
Food chemistry
Jul 17, 2024
Precise monitoring of nitrite from real samples has gained significant attention due to its detrimental impact on human health. Herein, we have fabricated poly(3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles (PEDOT...
ATR-FTIR spectroscopy and machine/deep learning models for detecting adulteration in coconut water with sugars, sugar alcohols, and artificial sweeteners.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 3, 2024
Packaged coconut water offers various options, from pure to those with added sugars and other additives. While the purity of coconut water is esteemed for its health benefits, its popularity also exposes it to potential adulteration and misrepresenta...
A Support Vector Machine-Assisted Metabolomics Approach for Non-Targeted Screening of Multi-Class Pesticides and Veterinary Drugs in Maize.
Molecules (Basel, Switzerland)
Jun 26, 2024
The contamination risks of plant-derived foods due to the co-existence of pesticides and veterinary drugs (P&VDs) have not been fully understood. With an increasing number of unexpected P&VDs illegally added to foods, it is essential to develop a non...
The development of honey recognition models with broad applicability based on the association of isotope and elemental content with ANNs.
Food chemistry
Jun 24, 2024
Honey adulteration represents a worldwide problem, driven by the illicit economic gain that producers, traders, or merchants pursue. Among the falsification methods that can unfairly influence the price is the incorrect declaration of the botanical o...
Ensuring food safety by artificial intelligence-enhanced nanosensor arrays.
Advances in food and nutrition research
Jun 18, 2024
Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple c...
Development of automatic tuning for combined preprocessing and hyperparameters of machine learning and its application to NIR spectral data of coconut milk adulteration.
Food chemistry
Jun 15, 2024
This study proposed a novel approach to automatically select the preprocessing methods and hyperparameters of machine learning (ML) algorithms based on their best performance in cross-validation for near-infrared (NIR) spectroscopy data. The proposed...
Rapid identification and quantitative analysis of malachite green in fish via SERS and 1D convolutional neural network.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jun 13, 2024
Rapid and quantitative detection of malachite green (MG) in aquaculture products is very important for safety assurance in food supply. Here, we develop a point-of-care testing (POCT) platform that combines a flexible and transparent surface-enhanced...
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