We present a method for comparing models used to detect food fraud based on stable isotopes and trace element (SITE) levels. Existing modeling procedures generally do not provide an uncertainty estimate on a model's performance due to variations in t...
Sensitive and rapid detection of aflatoxin B (AFB) is vital for safeguarding food safety, considering its potent carcinogenic toxicity. Herein, an artificial intelligence-enabled microsphere imaging (AI-MI) immunosensor based on magnetic metal-organi...
To determine the authenticity of honey, a deep learning network based on the Canny-GoogLeNet architecture combined with three-dimensional (3D) fluorescence spectroscopy was established. The canny edge detection algorithm was used to extract 3D spectr...
This study presents a simple approach for detecting honey adulteration by integrating calorimetric data from differential scanning calorimetry (DSC) with machine learning classification (MLC) techniques, specifically using convolutional neural networ...
Honey is a valuable natural food product, prized for its nutritional and therapeutic properties. However, the widespread issue of honey adulteration, often involving the addition of plant-based syrups, poses significant challenges to global markets. ...
This study introduces the Milk Quality Index (MQI), a novel metric for assessing milk quality that utilizes machine learning to enhance predictive accuracy. Lead (Pb) levels (318 ± 185 mg/kg) exceeded safety limits, with chromium (Cr), aluminum (Al),...
Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment
Apr 21, 2025
In recent years, food fraud issues related to whey protein supplements have disrupted the market and caused significant concern among consumers. Conventional analytical methods such as HPLC and ion exchange chromatography are commonly used to detect ...
Food research international (Ottawa, Ont.)
Apr 20, 2025
Food adulteration is an important threat to food safety and can be difficult to detect. Some analytical methods are complex and difficult to meet the needs of large numbers of samples. In this study, we introduced the application of six spectroscopic...
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...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Apr 9, 2025
This study developed a convolutional neural network (CNN) model based on feature-level data fusion for quantitatively detecting aflatoxin B1 (AFB1) in peanuts. Using a portable near-infrared (NIR) spectrometer and a Raman spectrometer, NIR and Raman ...
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