AIMC Topic: Milk
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Determination of milk yield in water buffaloes using multi-class logistic regression and machine learning methods.
Tropical animal health and production
Jul 28, 2025
In this study, Random Forest, Gradient Boosting Machines (GBM), and Support Vector Machines (SVM), Multi-Class Logistic Regression (MCLR) models were comparatively evaluated for the prediction of milk yield in water buffaloes. The study's main purpos...
Association of artificial intelligence-predicted milk yield residuals to behavioral patterns and transition success in multiparous dairy cows.
Journal of dairy science
Jul 16, 2025
Data-driven health monitoring based on milk yield has shown potential to identify health-perturbing events during the transition period. As a proof of principle, we explored the association between the cow's residual milk yield, that is, the differen...
Predicting reticuloruminal pH and subacute ruminal acidosis of individual cows using machine learning and Fourier-transform infrared spectroscopy milk analysis.
Journal of dairy science
Jun 9, 2025
Low reticuloruminal pH (rpH) for a prolonged period could lead to SARA. This disease negatively affects cow health and is associated with monetary losses for the dairy industry. The aim of this study was to predict rpH and SARA separately using diffe...
Use of a priority lane to increase voluntary visits to a milking robot in dairy cows.
Journal of dairy science
Apr 17, 2025
Voluntary visits to the milking robot are the basis of automatic milking system functionality. Therefore, problems arise when cows are undermotivated to visit the robot. Cows with reduced competitive abilities, specifically those that are lame or low...
AI-based forecasting of dynamic behaviors of Ag and ZnO nanoparticles-enhanced milk in an electromagnetic channel with exponential heating: dairy decontamination.
The European physical journal. E, Soft matter
Apr 17, 2025
Electromagnetic plates can be used to heat milk and other dairy products rapidly and uniformly. The use of electromagnetic fields enables precise thermal control, which is crucial for safe pasteurization while retaining the nutritional and sensory qu...
Milk lipidome alterations in first-lactation dairy cows with lameness: A biomarker identification approach using untargeted lipidomics and machine learning.
Journal of dairy science
Apr 16, 2025
Lameness, defined as an impaired gait, impacts cow welfare and performance, compromising future health and production, and increasing culling risk. Untargeted milk lipidomics, together with the use of machine learning methods, have shown promise in i...
Machine Learning-Assisted Portable Dual-Readout Biosensor for Visual Detection of Milk Allergen.
Nano letters
Mar 20, 2025
Beta-lactoglobulin (β-LG), the primary allergen in cow's milk, makes developing a rapid, sensitive, and convenient detection method essential for individuals with allergies. In this study, a graphdiyne-based self-powered electrochemical biosensor has...
Near-infrared spectroscopy assisted by random forest for predicting the physicochemical indicators of yak milk powder.
Food chemistry
Mar 1, 2025
High-efficiency and cost-effective detection of physicochemical indicators is essential for the quality control of yak milk powder. Herein, a rapid and simultaneous detection method based on miniaturized near-infrared (NIR) spectroscopy and chemometr...
Machine Learning-Assisted Chemical Tongues Based on Dual-channel Inclusion Complexes for Rapid Identification of Nonsteroidal Anti-inflammatory Drugs in Food.
ACS sensors
Feb 24, 2025
The improper application of nonsteroidal anti-inflammatory drugs (NSAIDs) presents significant health hazards via vector food contamination. A critical limitation of these traditional existing approaches is their inability to concurrently discern and...
[Validation of a decision tree for selective dry cow therapy of dairy for a digital expert system].
Tierarztliche Praxis. Ausgabe G, Grosstiere/Nutztiere
Feb 18, 2025
In this study, a decision tree derived from scientific literature on selective dry cow therapy (ST), which was developed as a knowledge base for a digital expert system, was evaluated. The decision tree merges algorithmic (based on cell count results...
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