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Animal Sciences

University of Nebraska - Lincoln

Nursery pigs

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Full-Text Articles in Life Sciences

Utilization Of The NuTrack System To Objectively Evaluate Changes In Active And Passive Behaviors Of Group-Housed Nursery Pigs Exposed To An Endotoxin Challenge, Aaron Holliday May 2024

Utilization Of The NuTrack System To Objectively Evaluate Changes In Active And Passive Behaviors Of Group-Housed Nursery Pigs Exposed To An Endotoxin Challenge, Aaron Holliday

Department of Animal Science: Dissertations, Theses, and Student Research

This study aimed to evaluate the changes in activity of group-housed, newly weaned pigs challenged with lipopolysaccharide (LPS). At weaning, pigs (n = 192, 5.73 ± 1.8 kg) were stratified by sex, litter, and body weight (BW) and randomly assigned to one of three treatments (16 pigs/pen, 4 pens/treatment): 1) Saline-injected (SAL), 2) 50% challenged [50%-LPS) – only half of the pigs in a pen (8 pigs) were challenged with LPS and 3) 100% challenged (100%-LPS) – all pigs in a pen were challenged with LPS. Pigs in the SAL and 32 in the 50%-LPS treatment received a 3.0 …


Utilization Of Depth - Enabled Identification And Tracking System To Identify And Track Individual Pigs And Analyse Individual Pig Activity, Jessica Michelle Lancaster Aug 2018

Utilization Of Depth - Enabled Identification And Tracking System To Identify And Track Individual Pigs And Analyse Individual Pig Activity, Jessica Michelle Lancaster

Department of Animal Science: Dissertations, Theses, and Student Research

Ensuring the health and wellbeing of pigs is of the utmost importance to the swine industry. There is a need for a real-time system that can identify changes in pig activities and activity patterns to accurately identify compromised pigs. The value of a real-time system is the capability to identify compromised pigs prior to observance of visible clinical symptoms by facility personnel. Therefore, a novel computer vision depth-enabled identification and tracking (DeIT) system was evaluated. Evaluation of 10,544 randomly selected frames indicated a 93.9% accuracy rate for identifying pigs’ identity when classified by the system as standing/walking. The accuracy of …