Evaluation of Precision Livestock Technology and Human Scoring of Nursery Pigs in a Controlled Immune Challenge Experiment

Abstract

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.

Utilizing NUtrack to Access the Activity Levels in Pigs with Varying Degrees of Genetic Potential for Growth and Feed Intake

“…Pigs in this analysis were of the same genetics and housed in the same rooms/pens with the same lighting and stocking density in which the NUtrack system was originally trained on. Furthermore, NUtrack has been shown to show greater specificity and sensitivity than trained human observers while providing continuous coverage and analysis of pig activity [28] that is not feasible for human observers to accomplish in a study of this scale.…”

Enhancing Animal Production through Smart Agriculture: Possibilities, Hurdles, Resolutions, and Advantages

“…These technologies find application in remote monitoring, precision medicine, behavioral monitoring, and safety monitoring. Noteworthy examples include PetPace, a novel pet-related device or service, Tractive, a GPS animal tracking device, and Cowlar, a smart collar tailored for cows [137,138].…”

Estimating genetic parameters of digital behavior traits and their relationship with production traits in purebred pigs

“…In addition, incorporating phenotypes from progeny at the multiplication or commercial level would benefit nucleus level parents and enhance accuracy of the genomic estimated breeding values (GEBV) of the elite animals. As collecting phenotypes can be costly and labor-intensive, automated data collection via digital phenotyping could increase data collection at a low cost and with more precision than human labor [ 10 , 11 ]. Traits that are of interest to capture using digital phenotyping are those that are heritable and that are genetically related to, or that affect an animal’s economically relevant production traits.…”