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Food Analysis

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Machine Learning-Based Nanozyme Sensor Array as an Electronic Tongue for the Discrimination of Endogenous Phenolic Compounds in Food.

Analytical chemistry
The detection of endogenous phenolic compounds (EPs) in food is of great significance in elucidating their bioactivity and health effects. Here, a novel bifunctional vanillic acid-Cu (VA-Cu) nanozyme with peroxidase-like and laccase-like activities w...

Environmentally Sustainable Detection of Arsenic using Convolutional Neural Networks and Imidazole-Based Organic Probes: Application in Food Samples and Arsenic Album.

Chemical research in toxicology
Arsenic contamination poses a significant health risk, particularly when it infiltrates water supplies. While current detection methods offer precise analysis, they often involve complex instrumentation not suitable for field use. This study presents...

Enhanced food authenticity control using machine learning-assisted elemental analysis.

Food research international (Ottawa, Ont.)
With the increasing attention being paid to the authenticity of food, efficient and accurate techniques that can solve relevant problems are crucial for improving public trust in food. This review explains two main aspects of food authenticity, namel...

Machine vision combined with deep learning-based approaches for food authentication: An integrative review and new insights.

Comprehensive reviews in food science and food safety
Food fraud undermines consumer trust, creates economic risk, and jeopardizes human health. Therefore, it is essential to develop efficient technologies for rapid and reliable analysis of food quality and safety for food authentication. Machine vision...

Enhancing dietary analysis: Using machine learning for food caloric and health risk assessment.

Journal of food science
In the wake of growing concerns regarding diet-related health issues, this study investigates the application of machine learning methods to estimate the energy content and classify the health risks of foods based on the USDA National Nutrient Databa...

Lightweight deep learning algorithm for real-time wheat flour quality detection via NIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wheat flour quality, determined by factors such as protein and moisture content, is crucial in food production. Traditional methods for analyzing these parameters, though precise, are time-consuming and impractical for large-scale operations. This st...

Mass Spectrometry Imaging for Spatial Ingredient Classification in Plant-Based Food.

Journal of the American Society for Mass Spectrometry
Mass spectrometry imaging (MSI) techniques enable the generation of molecular maps from complex and heterogeneous matrices. A burger patty, whether plant-based or meat-based, represents one such complex matrix where studying the spatial distribution ...

Machine Learning-Assisted, Dual-Channel CRISPR/Cas12a Biosensor-In-Microdroplet for Amplification-Free Nucleic Acid Detection for Food Authenticity Testing.

ACS nano
The development of novel detection technology for meat species authenticity is imperative. Here, we developed a machine learning-supported, dual-channel biosensor-in-microdroplet platform for meat species authenticity detection named CC-drop (RISPR/C...

Active Quantum Biomaterials-Enhanced Microrobots for Food Safety.

Small (Weinheim an der Bergstrasse, Germany)
Timely disruptive tools for the detection of pathogens in foods are needed to face global health and economic challenges. Herein, the utilization of quantum biomaterials-enhanced microrobots (QBEMRs) as autonomous mobile sensors designed for the prec...

Recent advances of machine learning in the geographical origin traceability of food and agro-products: A review.

Comprehensive reviews in food science and food safety
The geographical origin traceability of food and agro-products has been attracted worldwide. Especially with the rise of machine learning (ML) technology, it provides cutting-edge solutions to erstwhile intractable issues to identify the origin of fo...