AIMC Topic: Milk

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Machine Learning-Assisted Liquid Crystal Optical Sensor Array Using Cysteine-Functionalized Silver Nanotriangles for Pathogen Detection in Food and Water.

ACS applied materials & interfaces Dec 12, 2024
The challenge of rapid identification of bacteria in food and water still persists as a major health problem. To tackle this matter, we have developed a single-probe liquid crystal (LC)-based optical sensing platform for the differentiation of five c...
Bacteria Food Microbiology Metal Nanoparticles Machine Learning Cysteine Liquid Crystals Silver Milk Water Microbiology
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Methodology for quality risk prediction for milk powder production plants with domain-knowledge-involved serial neural networks.

Food chemistry Nov 17, 2024
In dairy enterprises, predicting product quality attributes that are influenced by operating parameters is a major task. To reduce quality loss in production, a prediction-based quality control method is proposed in this study. In particular, a seria...
Neural Networks, Computer Animals Cattle Quality Control Dairying Milk Powders
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Milk adulteration identification using hyperspectral imaging and machine learning.

Journal of dairy science Nov 8, 2024
Milk adulteration poses a global concern, with developing countries facing higher risks due to unsatisfactory monitoring systems and policies. Surprisingly, this common issue has often been overlooked in many countries. Contrary to popular belief, ad...
Hyperspectral Imaging Cattle Food Contamination Milk Machine Learning Animals
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Predicting Lactobacillus delbrueckii subsp. bulgaricus-Streptococcus thermophilus interactions based on a highly accurate semi-supervised learning method.

Science China. Life sciences Oct 14, 2024
Lactobacillus delbrueckii subsp. bulgaricus (L. bulgaricus) and Streptococcus thermophilus (S. thermophilus) are commonly used starters in milk fermentation. Fermentation experiments revealed that L. bulgaricus-S. thermophilus interactions (LbStI) su...
Animals Milk Computational Biology Lactobacillus delbrueckii Supervised Machine Learning Fermentation Streptococcus thermophilus
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Dielectric spectroscopy technology combined with machine learning methods for nondestructive detection of protein content in fresh milk.

Journal of food science Oct 11, 2024
To quickly achieve nondestructive detection of protein content in fresh milk, this study utilized a network analyzer and an open coaxial probe to analyze the dielectric spectra of milk samples at 100 frequency points within the 2-20 GHz range, focusi...
Dielectric Spectroscopy Milk Proteins Animals Machine Learning Cattle Algorithms Support Vector Machine Decision Trees Least-Squares Analysis Milk
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Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production.

mSystems Oct 10, 2024
UNLABELLED: The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of micro...
Metagenomics Principal Component Analysis Microbiota Milk Artificial Intelligence Machine Learning Algorithms Animals Food Microbiology
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Cuprospinel decorated biopolymer functionalized CNFs based electrocatalytic platform integrated with grid search optimized neural network for detection of vital amino acid in beverages.

Food chemistry Oct 5, 2024
An electrocatalytic platform based on a novel nanocomposite integrated with a grid search-optimized neural network (GSNN) was proposed for intelligent sensing of tryptophan. The cuprospinel-decorated chitosan-functionalized carbon nanofibers (CuFeO/C...
Neural Networks, Computer Nanofibers Biopolymers Fruit and Vegetable Juices Milk Tryptophan Catalysis Copper Solanum lycopersicum Beverages Electrodes Nanocomposites Oxidation-Reduction Animals Electrochemical Techniques Carbon Limit of Detection Chitosan
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Comparison of a machine learning model with a conventional rule-based selective dry cow therapy algorithm for detection of intramammary infections.

Journal of dairy science Sep 28, 2024
We trained machine learning models to identify IMI in late-lactation cows at dry-off to guide antibiotic treatment, and compared their performance to a rule-based algorithm that is currently used on dairy farms in the United States. We conducted an o...
Cattle Lactation Milk Algorithms Female Animals Machine Learning Mastitis, Bovine
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Machine learning supported single-stranded DNA sensor array for multiple foodborne pathogenic and spoilage bacteria identification in milk.

Food chemistry Sep 6, 2024
Ensuring food safety through rapid and accurate detection of pathogenic bacteria in food products is a critical challenge in the food supply chain. In this study, a non-specific optical sensor array was proposed for the identification of multiple pat...
Animals Food Microbiology Cattle Milk Biosensing Techniques DNA, Single-Stranded Bacteria Neural Networks, Computer DNA, Bacterial Machine Learning Food Contamination
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Suitability of different machine learning algorithms for the classification of the proportion of grassland-based forages at the herd level using mid-infrared spectral information from routine milk control.

Journal of dairy science Aug 30, 2024
As the call for an international standard for milk from grassland-based production systems continues to grow, so too do the monitoring and evaluation policies surrounding this topic. Individual stipulations by countries and milk producers to market t...
Animal Feed Animals Machine Learning Dairying Lactation Algorithms Grassland Diet Milk Female Cattle
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