AIMC Topic: Food Analysis
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A FPGA based recurrent neural networks-based impedance spectroscopy system for detection of YAKE in tuna.
Scientific reports
Jul 1, 2025
This paper evaluates the use of impedance spectroscopy combined with artificial intelligence. Both technologies have been widely used in food classification and it is proposed a way to improve classifications using recurrent neural networks that trea...
Spectroscopic techniques combined with chemometrics for rapid detection of food adulteration: Applications, perspectives, and challenges.
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...
Integrating mass defect filtering and targeted molecular networking for foodomics research: A case study of Magnolia officinalis cortex.
Food research international (Ottawa, Ont.)
Apr 18, 2025
Mass spectrometry (MS)-based foodomics is widely used to tackle complex challenges in food science, although its effectiveness is often hampered by extensive data redundancy. To address this limitation, a novel MS-based foodomics strategy, integratin...
Advancements in small molecule fluorescent probes for the detection of formaldehyde in environmental and food samples: A comprehensive review.
Food chemistry
Mar 26, 2025
Formaldehyde (FA), a hazardous substance with carcinogenicity and mutagenicity, necessitates sensitive and accurate detection methods for protecting public health and the environment. While numerous reviews have explored FA fluorescent probes, the cu...
Deep-learning-assisted chemo-responsive alizarin red S-based hydrogel sensor for the rapid freshness sensing of aquatic product.
Food research international (Ottawa, Ont.)
Mar 15, 2025
Rapid detection of freshness particularly in aquatic products demands efficient sensing strategies. Here, a novel deep-learning-assisted chemo-responsive alizarin red S-based hydrogel sensing platform was established for rapid freshness assay of aqua...
Rapid and accurate identification and quantification of Lycium barbarum L. components: Integrating deep learning and NMR for nutritional assessment.
Food research international (Ottawa, Ont.)
Mar 15, 2025
Lycium barbarum L. (L. barbarum), revered for its nutritional and commercial value, exhibits variable nutritional contents depending on the consumption method. This study introduces an innovative approach, the Identification and Quantification of L.b...
Foodomics approaches: New insights in phenolic compounds analysis.
Food research international (Ottawa, Ont.)
Mar 13, 2025
Fruits, vegetables, and plant-based foods contain several bioactive substances such as phenolic compounds (PCs), that are plant secondary metabolites with attributed health properties. The study of the metabolic pathways of PCs, including those relat...
Origin traceability of agricultural products: A lightweight collaborative neural network for spectral information processing.
Food research international (Ottawa, Ont.)
Mar 6, 2025
The natural conditions of various regions, including climate, soil, and water quality, significantly influence the nutrient composition and quality of agricultural products. Identifying the origin of agricultural products can prevent adulteration, im...
Machine Learning-Assisted Chemical Tongues Based on Dual-channel Inclusion Complexes for Rapid Identification of Nonsteroidal Anti-inflammatory Drugs in Food.
ACS sensors
Feb 24, 2025
The improper application of nonsteroidal anti-inflammatory drugs (NSAIDs) presents significant health hazards via vector food contamination. A critical limitation of these traditional existing approaches is their inability to concurrently discern and...
Comparative performance of artificial neural networks and support vector Machines in detecting adulteration of apple juice concentrate using spectroscopy and time domain NMR.
Food research international (Ottawa, Ont.)
Dec 30, 2024
The detection of adulteration in apple juice concentrate is critical for ensuring product authenticity and consumer safety. This study evaluates the effectiveness of artificial neural networks (ANN) and support vector machines (SVM) in analyzing spec...
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