AIMC Topic: Red Meat

Clear Filters Showing 11 to 20 of 33 articles

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...
Animals Meat Red Meat Pork Meat Swine Deep Learning Water
View on PubMed DOI

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...
Ducks Red Meat Meat Neural Networks, Computer Sheep Animals Cattle
View on PubMed DOI

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 ...
Food Contamination Neural Networks, Computer Animals Ducks Deep Learning Red Meat
View on PubMed DOI

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...
Deep Learning Cattle Image Processing, Computer-Assisted Machine Learning Animals Body Composition Red Meat
View on PubMed DOI

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...
Animals Myoglobin Spectrum Analysis Deep Learning Red Meat Cattle Food Quality
View on PubMed DOI

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...
Proportional Hazards Models Coronary Disease Red Meat Milk Coffee Protective Factors Middle Aged Diet Incidence Stroke Heart Failure Heart Disease Risk Factors Animals Humans Male Machine Learning Cardiovascular Diseases Female Aged
View on PubMed DOI

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...
Machine Learning Animals Biosensing Techniques Spectrum Analysis, Raman Milk Escherichia coli O157 Red Meat Limit of Detection
View on PubMed DOI

Trace elements and machine learning for Brazilian beef traceability.

Food chemistry Jul 4, 2020
Brazilian livestock with a herd of more than 215 million animals is distributed over a vast area of 160 million hectares, leading the country to the first position in the world beef exports and second in beef production and consumption. Animals risen...
Neural Networks, Computer Machine Learning Trace Elements Animals Ecosystem Cattle Brazil Red Meat
View on PubMed DOI

Rapid detection of adulteration of minced beef using Vis/NIR reflectance spectroscopy with multivariate methods.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 14, 2020
High economic returns induce the continuous occurrence of meat adulteration. In this study, visible/near-infrared (Vis/NIR) reflectance spectroscopy with multivariate methods was used for the rapid detection of adulteration in minced beef. First, the...
Cattle Support Vector Machine Food Contamination Animals Spectroscopy, Near-Infrared Principal Component Analysis Neural Networks, Computer Meat Red Meat
View on PubMed DOI

Prediction of marbling score and carcass traits in Korean Hanwoo beef cattle using machine learning methods and synthetic minority oversampling technique.

Meat science Nov 12, 2019
Pricing of Hanwoo beef in the Korean market is primarily based on meat quality, and particularly on marbling score. The ability to accurately predict marbling score early in the life of an animal is extremely valuable for producers to meet the requir...
Cattle Reproducibility of Results Image Processing, Computer-Assisted Red Meat Animals Machine Learning Food Quality Ultrasonography Republic of Korea
View on PubMed DOI
Popular Topics
Recent Journals