AIMC Topic: Red Meat

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Exploration of the prediction and generation patterns of heterocyclic aromatic amines in roast beef based on Genetic Algorithm combined with Support Vector Regression.

Food chemistry Aug 31, 2024
Heterocyclic aromatic amines (HAAs) are harmful byproducts in food heating. Therefore, exploring the prediction and generation patterns of HAAs is of great significance. In this study, genetic algorithm (GA) and support vector regression (SVR) are us...
Heterocyclic Compounds Amines Cooking Red Meat Hot Temperature Algorithms Animals Cattle Support Vector Machine Meat Meat Products
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Using machine-learning approaches to investigate the volatile-compound fingerprint of fishy off-flavour from beef with enhanced healthful fatty acids.

Meat science Aug 24, 2024
Machine learning classification approaches were used to discriminate a fishy off-flavour identified in beef with health-enhanced fatty acid profiles. The random forest approach outperformed (P < 0.001; receiver operating characteristic curve: 99.8 %,...
Machine Learning Taste Volatile Organic Compounds Red Meat Animals Cattle Fatty Acids
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Carcass traits and morphometry, typification of the Longissimus dorsi muscle and non-carcass components of hair lambs: can biscuit bran completely replace corn? A machine learning approach.

Tropical animal health and production May 13, 2024
Biscuit bran (BB) is a co-product with worldwide distribution, with Brazil as the second largest cookie producer in the world with 1,157,051 tons. We evaluate the impact of completely replacing corn with BB on the characteristics and morphometry of c...
Diet Brazil Meat Machine Learning Animals Male Animal Feed Zea mays Red Meat Body Composition Sheep, Domestic
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Measuring water holding capacity in pork meat images using deep learning.

Meat science Mar 16, 2023
Water holding capacity (WHC) plays an important role when obtaining a high-quality pork meat. This attribute is usually estimated by pressing the meat and measuring the amount of water expelled by the sample and absorbed by a filter paper. In this wo...
Meat Red Meat Pork Meat Deep Learning Water Animals Swine
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Image based beef and lamb slice authentication using convolutional neural networks.

Meat science Oct 12, 2022
Meat adulteration affects customers and the market. Existing meat authentication methods usually rely on special devices, and thus are limited to professional use only. Fake lamb or beef slices made from duck and fat appear in some Chinese hotpot res...
Meat Sheep Ducks Red Meat Neural Networks, Computer Animals Cattle
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Detection of adulteration in mutton using digital images in time domain combined with deep learning algorithm.

Meat science May 16, 2022
A novel method based on digital images in time domain combined with convolutional neural network (CNN) is proposed for discrimination and analysis of the adulterated mutton. For this, 195 sample images during the constant temperature heating process ...
Ducks Red Meat Neural Networks, Computer Animals Deep Learning Food Contamination
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Predicting carcass cut yields in cattle from digital images using artificial intelligence.

Meat science Sep 10, 2021
Deep Learning (DL) has proven to be a successful tool for many image classification problems but has yet to be applied to carcass images. The aim of this study was to train DL models to predict carcass cut yields and compare predictions to more stand...
Body Composition Red Meat Deep Learning Cattle Image Processing, Computer-Assisted Machine Learning Animals
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Rapid and non-destructive spectroscopic method for classifying beef freshness using a deep spectral network fused with myoglobin information.

Food chemistry Feb 23, 2021
A simple, novel, rapid, and non-destructive spectroscopic method that employs the deep spectral network for beef-freshness classification was developed. The deep-learning-based model classified beef freshness by learning myoglobin information and ref...
Food Quality Myoglobin Animals Spectrum Analysis Deep Learning Red Meat Cattle
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Association Between Coffee Intake and Incident Heart Failure Risk: A Machine Learning Analysis of the FHS, the ARIC Study, and the CHS.

Circulation. Heart failure Feb 9, 2021
BACKGROUND: Coronary heart disease, heart failure (HF), and stroke are complex diseases with multiple phenotypes. While many risk factors for these diseases are well known, investigation of as-yet unidentified risk factors may improve risk assessment...
Heart Disease Risk Factors Milk Coffee Proportional Hazards Models Coronary Disease Humans Red Meat Incidence Animals Protective Factors Machine Learning Male Stroke Female Middle Aged Cardiovascular Diseases Heart Failure Aged Diet
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SERS-based lateral flow assay combined with machine learning for highly sensitive quantitative analysis of Escherichia coli O157:H7.

Analytical and bioanalytical chemistry Sep 12, 2020
In the present study, surface-enhanced Raman scattering-based lateral flow assay (SERS-LFA) strips were applied to promptly and sensitively detect Escherichia coli O157:H7 (E. coli O157:H7) to ensure food safety. The SERS nanotags were prepared by co...
Limit of Detection Biosensing Techniques Machine Learning Spectrum Analysis, Raman Milk Animals Red Meat Escherichia coli O157
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