AI Medical Compendium Journal:
Food research international (Ottawa, Ont.)

Showing 21 to 30 of 133 articles

Fruit wines classification enabled by combing machine learning with comprehensive volatiles profiles of GC-TOF/MS and GC-IMS.

Food research international (Ottawa, Ont.) Feb 5, 2025
Fruit wines, produced through the fermentation of various fruits, are well-documented for their distinct flavor profiles. Intelligent sensory analysis, GC-TOF/MS and GC-IMS were used for the analysis of the volatile profile of eight types of fruit wi...
Wine Vitis Fruit Neural Networks, Computer Machine Learning Volatile Organic Compounds Blueberry Plants Prunus persica Gas Chromatography-Mass Spectrometry Fermentation Taste
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Automated and explainable machine learning for monitoring lipid and protein oxidative damage in mutton using hyperspectral imaging.

Food research international (Ottawa, Ont.) Feb 1, 2025
Current detection methods for lipid and protein oxidation using hyperspectral imaging (HSI) in conjunction with machine learning (ML) necessitate the involvement of data scientists and domain experts to adjust the model architecture and tune hyperpar...
Hyperspectral Imaging Machine Learning Animals Oxidative Stress Lipids Proteins Oxidation-Reduction
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A robust deep learning model for predicting green tea moisture content during fixation using near-infrared spectroscopy: Integration of multi-scale feature fusion and attention mechanisms.

Food research international (Ottawa, Ont.) Jan 30, 2025
Fixation is a critical step in green tea processing, and the moisture content of the leaves after fixation is a key indicator of the fixation quality. Near-infrared spectroscopy (NIRS)-based moisture detection technology is often applied in the tea p...
Tea Least-Squares Analysis Food Handling Temperature Deep Learning Spectroscopy, Near-Infrared Water Plant Leaves
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Determination of quality differences and origin tracing of green tea from different latitudes based on TG-FTIR and machine learning.

Food research international (Ottawa, Ont.) Jan 27, 2025
Latitude differences can significantly affect the quality of tea, while in-depth research in this field is lacking. This study investigates green teas from different latitudes in China using thermogravimetric analysis coupled with infrared spectrosco...
Principal Component Analysis Machine Learning Thermogravimetry China Kinetics Cluster Analysis Spectroscopy, Fourier Transform Infrared Pyrolysis Camellia sinensis Tea
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Machine learning-based classification and prediction of typical Chinese green tea taste profiles.

Food research international (Ottawa, Ont.) Jan 27, 2025
The taste of Chinese green tea is highly diverse. In this study, a combination of unsupervised and supervised learning methods was utilized to develop a model for classifying and predicting typical Chinese green tea taste. Three clustering methods we...
China Cluster Analysis Metabolomics Tea Taste Catechin Adult Male Spectroscopy, Near-Infrared Humans Electronic Nose Machine Learning
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Prediction of coffee traits by artificial neural networks and laser-assisted rapid evaporative ionization mass spectrometry.

Food research international (Ottawa, Ont.) Jan 23, 2025
BACKGROUND: Coffee is an important commodity in the worldwide economy and smart technologies are important for accurate quality control and consumer-oriented product development. Sensory perception is probably the most important information since it ...
Taste Lasers Coffee Mass Spectrometry Discriminant Analysis Fatty Acids Humans Neural Networks, Computer
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Discrimination of unsound soybeans using hyperspectral imaging: A deep learning method based on dual-channel feature fusion strategy and attention mechanism.

Food research international (Ottawa, Ont.) Jan 22, 2025
The application of high-level data fusion in the detection of agricultural products still presents a significant challenge. In this study, dual-channel feature fusion model (DCFFM) with attention mechanism was proposed to optimize the utilization of ...
Glycine max Deep Learning Support Vector Machine Hyperspectral Imaging Neural Networks, Computer Spectroscopy, Near-Infrared
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High-throughput, rapid, and non-destructive detection of common foodborne pathogens via hyperspectral imaging coupled with deep neural networks and support vector machines.

Food research international (Ottawa, Ont.) Jan 7, 2025
Foodborne pathogens such as Bacillus cereus, Staphylococcus aureus, and Escherichia coli are major causes of gastrointestinal diseases worldwide and frequently contaminate dairy products. Compared to nucleic acid detection and MALDI-TOF MS, hyperspec...
Discriminant Analysis High-Throughput Screening Assays Hyperspectral Imaging Bacillus cereus Neural Networks, Computer Deep Learning Support Vector Machine Food Microbiology Escherichia coli Foodborne Diseases Staphylococcus aureus Principal Component Analysis Food Contamination
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Computational approaches for decoding structure-saltiness enhancement and aroma perception mechanisms of odorants: From machine learning to molecular simulation.

Food research international (Ottawa, Ont.) Jan 7, 2025
The unclear relationship between structure and saltiness enhancement limits the development and application of savory odorants. The structure characteristic-saltiness enhancement perception (SEP) mechanisms of savory odorants were investigated by mac...
Sodium Chloride Smell Hydrogen Bonding Molecular Docking Simulation Odorants Hydrophobic and Hydrophilic Interactions Mutagenesis, Site-Directed Receptors, Odorant Humans Machine Learning
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Machine learning discovery of novel antihypertensive peptides from highland barley protein inhibiting angiotensin I-converting enzyme (ACE).

Food research international (Ottawa, Ont.) Jan 6, 2025
Hypertension is a major global health concern, and there is a need for new antihypertensive agents derived from natural sources. This study aims to identify novel angiotensin I-converting enzyme (ACE) inhibitors from bioactive peptides derived from f...
Machine Learning Peptides Molecular Docking Simulation Humans Angiotensin-Converting Enzyme Inhibitors Antihypertensive Agents Hordeum Molecular Dynamics Simulation Peptidyl-Dipeptidase A Plant Proteins
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