Evaluation of Precision Livestock Technology and Human Scoring of Nursery Pigs in a Controlled Immune Challenge Experiment.
Eduarda M BortoluzziMikayla J GoeringSara J OchoaAaron J HollidayJared M MummCatherine E NelsonHui WuBenny E MoteEric T PsotaTy B SchmidtMajid Jaberi-DourakiLindsey E HulbertPublished in: Animals : an open access journal from MDPI (2023)
The objectives were to determine the sensitivity, specificity, and cutoff values of a visual-based precision livestock technology (NUtrack), and determine the sensitivity and specificity of sickness score data collected with the live observation by trained human observers. At weaning, pigs (n = 192; gilts and barrows) were randomly assigned to one of twelve pens (16/pen) and treatments were randomly assigned to pens. Sham-pen pigs all received subcutaneous saline (3 mL). For LPS-pen pigs, all pigs received subcutaneous lipopolysaccharide (LPS; 300 μg/kg BW; E. coli O111:B4; in 3 mL of saline). For the last treatment, eight pigs were randomly assigned to receive LPS, and the other eight were sham (same methods as above; half-and-half pens). Human data from the day of the challenge presented high true positive and low false positive rates (88.5% sensitivity; 85.4% specificity; 0.871 Area Under Curve, AUC), however, these values declined when half-and-half pigs were scored (75% sensitivity; 65.5% specificity; 0.703 AUC). Precision technology measures had excellent AUC, sensitivity, and specificity for the first 72 h after treatment and AUC values were >0.970, regardless of pen treatment. These results indicate that precision technology has a greater potential for identifying pigs during a natural infectious disease event than trained professionals using timepoint sampling.
Keyphrases
- endothelial cells
- inflammatory response
- induced pluripotent stem cells
- infectious diseases
- pluripotent stem cells
- escherichia coli
- big data
- machine learning
- immune response
- clinical trial
- intensive care unit
- body composition
- risk assessment
- climate change
- mechanical ventilation
- double blind
- extracorporeal membrane oxygenation
- human health
- high intensity
- data analysis