AIMC Topic: Seafood

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Comparative evaluating laser ionization and iKnife coupled with rapid evaporative ionization mass spectrometry and machine learning for geographical authentication of Larimichthys crocea.

Food chemistry Jul 20, 2024
Larimichthys crocea (LYC) holds significant economic value as a marine fish species. However, inaccuracies in labeling its origin can adversely affect consumer interests. Herein, a laser assisted rapid evaporative ionization mass spectrometry (LA-REI...
Machine Learning Animals China Seafood Lasers Geography Mass Spectrometry Fishes
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Data fusion of near-infrared and Raman spectroscopy: An innovative tool for non-destructive prediction of the TVB-N content of salmon samples.

Food research international (Ottawa, Ont.) May 27, 2024
Total volatile basic nitrogen (TVB-N) serves as a crucial indicator for evaluating the freshness of salmon. This study aimed to achieve accurate and non-destructive prediction of TVB-N content in salmon fillets stored in multiple temperature settings...
Salmon Nitrogen Seafood Animals Spectroscopy, Near-Infrared Support Vector Machine Least-Squares Analysis Spectrum Analysis, Raman Temperature
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Deep learning models with optimized fluorescence spectroscopy to advance freshness of rainbow trout predicting under nonisothermal storage conditions.

Food chemistry May 22, 2024
This study established long short-term memory (LSTM), convolution neural network long short-term memory (CNN_LSTM), and radial basis function neural network (RBFNN) based on optimized excitation-emission matrix (EEM) from fish eye fluid to predict fr...
Food Storage Neural Networks, Computer Oncorhynchus mykiss Spectrometry, Fluorescence Animals Deep Learning Seafood
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Machine learning to predict the relationship between Vibrio spp. concentrations in seawater and oysters and prevalent environmental conditions.

Food research international (Ottawa, Ont.) May 10, 2024
Vibrio parahaemolyticus and Vibrio vulnificus are bacteria with a significant public health impact. Identifying factors impacting their presence and concentrations in food sources could enable the identification of significant risk factors and preven...
Machine Learning Temperature Vibrio parahaemolyticus Food Microbiology Seafood Animals Food Contamination Shellfish Ostreidae Vibrio vulnificus Vibrio Seawater
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Development of machine learning-based shelf-life prediction models for multiple marine fish species and construction of a real-time prediction platform.

Food chemistry Apr 10, 2024
At least 10 million tons of seafood products are spoiled or damaged during transportation or storage every year worldwide. Monitoring the freshness of seafood in real time has become especially important. In this study, four machine learning algorith...
Electronic Nose Seafood Food Storage Machine Learning Fishes Animals Temperature Gas Chromatography-Mass Spectrometry
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Deep learning-assisted smartphone-based portable and visual ratiometric fluorescence device integrated intelligent gel label for agro-food freshness detection.

Food chemistry Feb 4, 2023
Here, a smartphone-assisted dual-color ratiometric fluorescence smart gel label-based visual sensing platform was constructed for real-time evaluation of the freshness of agro-food based on the biogenic amines responses. Green-emission fluorescence c...
Smartphone Carbon Deep Learning Fluorescent Dyes Hydrogels Seafood Quantum Dots Limit of Detection
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Convolutional neural network-based portable computer vision system for freshness assessment of crayfish (Prokaryophyllus clarkii).

Journal of food science Nov 14, 2022
Developing novel techniques for freshness assessment are of the utmost importance in yield and trade of aquatic products. The crayfish (Prokaryophyllus clarkii) is one of the most popular freshwater products in China, and its food safety should be a ...
Seafood Astacoidea Neural Networks, Computer Animals China
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Multivariate versus machine learning-based classification of rapid evaporative Ionisation mass spectrometry spectra towards industry based large-scale fish speciation.

Food chemistry Oct 17, 2022
Detection and prevention of fish food fraud are of ever-increasing importance, prompting the need for rapid, high-throughput fish speciation techniques. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has quickly established itself as a powerf...
Animals Machine Learning Mass Spectrometry Seafood Fishes Spectrum Analysis
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Nondestructive and multiplex differentiation of pathogenic microorganisms from spoilage microflora on seafood using paper chromogenic array and neural network.

Food research international (Ottawa, Ont.) Oct 17, 2022
Non-destructive detection of human foodborne pathogens is critical to ensuring food safety and public health. Here, we report a new method using a paper chromogenic array coupled with a machine learning neural network (PCA-NN) to detect viable pathog...
Shewanella putrefaciens Humans Neural Networks, Computer Seafood Food Safety Machine Learning Product Packaging
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Effect of short-term frozen storage on taste of gonads of female Eriocheir sinensis and the classification of taste quality combined with sensory evaluation and fuzzy logic model.

Food chemistry Jan 10, 2022
To investigate the taste quality of gonads of Eriocheir sinensis during frozen storage, the difference in overall taste profile was determined by electronic tongue, and the contents of free amino acids and 5'-Nucleotides were measure. The results sho...
Seafood Fuzzy Logic Female Gonads Electronic Nose Taste Decapoda Animals
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