AIMC Topic: Food Contamination

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Machine Learning-Assisted Multicolor Fluorescence Assay for Visual Data Acquisition and Intelligent Inspection of Multiple Food Hazards Regardless of Matrix Interference.

ACS sensors
Regarding the significant health risks of pesticide residue in foods, while current sensors still suffer from limited efficiency and stability, as well as difficulties in qualitative identification and quantitative detection of mixtures, development ...

Machine learning-assisted Fourier transform infrared spectroscopy to predict adulteration in coriander powder.

Food chemistry
Coriander is a widely used spice, valued for its flavor, aroma, and nutritional benefits in various cuisines and food products. However, adulteration, such as the addition of sawdust, poses significant risks to food safety and authenticity. This stud...

Machine learning: An effective tool for monitoring and ensuring food safety, quality, and nutrition.

Food chemistry
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 ...

The fluorescence spectrum combined with a broad learning system to characterize the content of difenoconazole in cabbage.

Analytical methods : advancing methods and applications
Pesticide residue detection plays an important role in vegetable quality and food safety. In this work, we propose a method for detecting difenoconazole pesticide residues based on fluorescence spectroscopy technology and machine learning algorithms....

A machine learning multimodal profiling of Per- and Polyfluoroalkyls (PFAS) distribution across animal species organs via clustering and dimensionality reduction techniques.

Food research international (Ottawa, Ont.)
Per- and polyfluoroalkyl substances (PFAS) contamination in aquatic and terrestrial organisms poses significant environmental and health risks. This study quantified 15 PFAS compounds across various tissues (liver, kidney, gill, muscle, skin, lung, b...

Application of Bioinformatics and Machine Learning Tools in Food Safety.

Current nutrition reports
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...

Hidden threats beneath: uncovering the bio-accessible hazards of chromite-asbestos mine waste and their impacts on rice components via multi-machine learning algorithm.

Environmental geochemistry and health
The chromite-asbestos mining leaves behind tonnes of toxic waste, contaminating nearby agricultural fields with potentially toxic elements (PTEs). Over time, wind and water erosion spread these pollutants, severely impacting the ecosystem, food chain...

Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples.

Scientific reports
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...

Enhancing pyrrolizidine alkaloid separation and detection: LC-MS/MS method development and integration of ion mobility spectrometry into the LC-HRMS workflow.

Journal of chromatography. A
Pyrrolizidine alkaloids (PAs) are plant toxins occurring in different foodstuffs, including teas, herbal infusions and species. Additionally, PAs may be transferred to honey and pollen when honeybees come into contact with contaminated plants. Due to...

New Strategies and Artificial Intelligence Methods for the Mitigation of Toxigenic Fungi and Mycotoxins in Foods.

Toxins
The proliferation of toxigenic fungi in food and the subsequent production of mycotoxins constitute a significant concern in the fields of public health and consumer protection. This review highlights recent strategies and emerging methods aimed at p...