AIMC Topic: Animal Husbandry

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Development and validation of machine-learning models for monitoring individual behaviors in group-housed broiler chickens.

Poultry science
Animals' individual behavior is commonly monitored by live or video observation by a person. This can be labor intensive and inconsistent. An alternative is the use of machine learning-based computer vision systems. The objectives of this study were ...

Prediction of growth and feed efficiency in mink using machine learning algorithms.

Animal : an international journal of animal bioscience
The feed efficiency (FE) expresses as the amount of feed required per unit of BW gain. Since feed cost is the major input cost in the mink industry, evaluating of FE is a crucial step for competitiveness of the mink industry. However, the FE measures...

Tracking perching behavior of cage-free laying hens with deep learning technologies.

Poultry science
Providing perches in cage-free (CF) housing offers significant benefits for laying hens, such as improved leg muscle development, bone health, reduced abdominal fat, and decreased fear and aggression. A precise detection method is essential to ensure...

Development of a pig wean-quality score using machine-learning algorithms to characterize and classify groups with high mortality risk under field conditions.

Preventive veterinary medicine
Mortality during the post-weaning phase is a critical indicator of swine production system performance, influenced by a complex interaction of multiple factors of the epidemiological triad. This study leveraged retrospective data from 1723 groups of ...

Machine learning predictive modeling for condemnation risk assessment in antibiotic-free raised broilers.

Poultry science
The condemnation of broiler carcasses in the poultry industry is a major challenge and leads to significant financial losses and food waste. This study addresses the critical issue of condemnation risk assessment in the discarding of antibiotic-free ...

Lipidomics combined with random forest machine learning algorithms to reveal freshness markers for duck eggs during storage in different rearing systems.

Poultry science
The differences in lipids in duck eggs between the 2 rearing systems during storage have not been fully studied. Herein, we propose untargeted lipidomics combined with a random forest (RF) algorithm to identify potential marker lipids based on ultra-...

Monitoring activity index and behaviors of cage-free hens with advanced deep learning technologies.

Poultry science
Chickens' behaviors and activities are important information for managing animal health and welfare in commercial poultry houses. In this study, convolutional neural networks (CNN) models were developed to monitor the chicken activity index. A datase...

Artificial intelligence and porcine breeding.

Animal reproduction science
Livestock management is evolving into a new era, characterized by the analysis of vast quantities of data (Big Data) collected from both traditional breeding methods and new technologies such as sensors, automated monitoring system, and advanced anal...

FEDM: a convolutional neural network based fertilised egg detection model.

British poultry science
1. The production of goose eggs holds significant economic value on a global scale and the quality of fertilised eggs is crucial for the successful hatching and sustained development of the poultry industry. Developing a low-cost fertilised egg ident...

Transforming Poultry Farming: A Pyramid Vision Transformer Approach for Accurate Chicken Counting in Smart Farm Environments.

Sensors (Basel, Switzerland)
Smart farm environments, equipped with cutting-edge technology, require proficient techniques for managing poultry. This research investigates automated chicken counting, an essential part of optimizing livestock conditions. By integrating artificial...