AIMC Topic: Food Contamination

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Machine learning-assisted SERS detection of pyrethroid pesticides in edible fungi using a magnetic nanosensor.

Mikrochimica acta
Pyrethroid pesticide residues pose a significant global public health challenge, particularly in complex edible fungus matrices where trace, structurally similar pesticides are difficult to distinguish and detect. To address this critical gap, a nove...

Machine Learning-Assisted Ratiometric Fluorescence Electrospun Nanofiber Films for Portable and Intelligent Monitoring of Multiple Alkylresorcinol Homologues in Whole Wheat Foods.

ACS applied materials & interfaces
The intelligent authentication of whole wheat products remains a significant challenge due to the difficulty in simultaneously monitoring multiple alkylresorcinol (AR) homologues within complex food matrices. To address this, we have developed a nove...

Enhanced YOLO-based framework for accurate detection and identification of common wheat impurities with distinct objects.

Scientific reports
Real-time detecting and identifying impurities in wheat grain mass is crucial for wheat storage silos, flour mills and modern combines. Depending on the detection objectives, accuracy is typically prioritized in laboratory-based applications, whereas...

QDs fluorescent immunosensor based on magnetic separation coupled with machine learning for aflatoxin B1 detection in vegetable oils.

Food chemistry
Aflatoxin B1 (AFB1) is a common mycotoxin frequently found in vegetable oils. It poses a severe threat to public health, therefore there is a need for rapid and sensitive detection methods. In this study, a novel competitive immunofluorescent biosens...

Hybrid Sampling and Ensemble Learning for Food Safety Sampling Inspection Classification.

Journal of food protection
Food safety sampling inspection is critical for risk prevention in complex supply chains. However, extreme class imbalance, where unqualified samples are significantly outnumbered by qualified ones, biases machine learning (ML) models to prioritize m...

Portable AI-driven electrochemical aptasensor for real-time Staphylococcus aureus detection in food and beverages.

Mikrochimica acta
A portable electrochemical aptasensor integrated with machine learning was developed for rapid and on-site detection of Staphylococcus aureus (S. aureus) in food and beverage samples. The aptasensor was fabricated using screen-printed carbon electrod...

Leveraging RegNet and CBAM for precise detection of honey adulteration using thermal image analysis.

Scientific reports
Honey adulteration poses a huge challenge with considerable health and economic consequences, underscoring the necessity for effective and precise quality evaluation techniques. This research introduces a novel approach for classifying levels of hone...

An analytical and machine learning approach for total mercury and methylmercury determination in squid: enhancing food safety testing and traceability monitoring systems.

Food chemistry
This study presents the first assessment of total mercury (THg) and methylmercury (MeHg) in squids (Todarodes sagittatus, L.), providing insights into contamination levels and their correlation with the geographical origin. A method based on acidic e...

Molecularly imprinted polymers for mycotoxin biosensing: Rational design, advanced applications, and future horizons.

Biosensors & bioelectronics
Molecularly imprinted polymers (MIPs) have emerged as transformative synthetic receptors for mycotoxin detection, addressing critical global food safety challenges through their exceptional stability and design flexibility. This review systematically...

Lactic acid bacteria as promising dietary-derived bioadsorbents for foodborne contaminants: Mechanism, application advances and future perspectives.

Food chemistry
Foodborne contaminants, such as mycotoxins and microplastics, pose significant threats to human health due to their high toxicity and persistence in the food chain, thus necessitate effective mitigation strategies. Lactic acid bacteria (LAB), charact...