Body condition score accuracy and repeatability from evaluation of cull sow digital images at a midwestern harvest facility

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2022-12-22
Authors
Taylor, William E.
Humphrey, Dalton C.
Peyer, B. D.
Brown, Justin T.
Millman, Suzanne T.
Chipman, A. L.
Cassady, C. J.
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Elsevier
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Johnson, Anna
Professor Animal Behavior and Welfare
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Lonergan, Steven
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Stalder, Kenneth
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Animal Science

The Department of Animal Science originally concerned itself with teaching the selection, breeding, feeding and care of livestock. Today it continues this study of the symbiotic relationship between animals and humans, with practical focuses on agribusiness, science, and animal management.

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The Department of Animal Husbandry was established in 1898. The name of the department was changed to the Department of Animal Science in 1962. The Department of Poultry Science was merged into the department in 1971.

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Veterinary Diagnostic and Production Animal Medicine
The mission of VDPAM is to educate current and future food animal veterinarians, population medicine scientists and stakeholders by increasing our understanding of issues that impact the health, productivity and well-being of food and fiber producing animals; developing innovative solutions for animal health and food safety; and providing the highest quality, most comprehensive clinical practice and diagnostic services. Our department is made up of highly trained specialists who span a wide range of veterinary disciplines and species interests. We have faculty of all ranks with expertise in diagnostics, medicine, surgery, pathology, microbiology, epidemiology, public health, and production medicine. Most have earned certification from specialty boards. Dozens of additional scientists and laboratory technicians support the research and service components of our department.
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Objective The objective of this study was to assess accuracy, repeatability, and reproducibility when evaluating cull sow body condition score (BCS) using a digital medium. Materials and Methods Selected digital images were sourced from recorded images of sows brought to a Midwest abattoir. Digital images were collected on 2 separate occasions. Each sample, grouped by capture date, represented a unique scoring session. Scorers (n = 6) with experience at assessing sow body condition used images to assign a BCS to each sow using a 7-point BCS scale. Using applied values, scores were adjusted to the standard 5-point scale. Because scorers assessed individual sows’ body condition from recorded video images, the mode score (BCSMode) was calculated for each sow and considered the gold standard. Scoring distributions, mode scores, individual bias, percent agreement with BCSMode, percent interobserver agreement, Spearman correlations evaluating scorer agreement, repeatability, and reproducibility were calculated. Results and Discussion Scorer bias from the pooled cull sow groups (n = 386 total available video images from 2 separate collections) ranged from −0.25 (±0.5) to 0.51 (±0.9). Spearman correlation coefficients for cull sow BCS measured on all sows for all scores during the second scoring round were lower than those observed in the first round. Additionally, it was observed that repeatability estimates improved from round 1 and round 2 (Rd 1 = 0.74 and Rd 2 = 0.76), and reproducibility slightly decreased between round 1 and round 2 (Rd 1 = 0.52 and Rd 2 = 0.47). These repeatability and reproducibility changes demonstrate that as experience level increases, scorers begin to develop their interpretation of the scale used to assess body condition. In turn, they become more repeatable within themselves but may differ from other scorers. Implications and Applications The ability for scorers to accurately identify low-BCS sows could serve as a cumulative lifetime welfare indicator where harvest facilities could provide valuable BCS feedback on individual sow and group average basis. The accuracy, repeatability, and reproducibility reported in this study suggest that digital images are an effective medium to assess cull sow BCS.
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This is a manuscript of an article published as Taylor, W. E., D. C. Humphrey, B. D. Peyer, A. K. Johnson, J. T. Brown, S. T. Millman, A. L. Chipman, C. J. Cassady, S. M. Lonergan, and K. J. Stalder. "Body condition score accuracy and repeatability from evaluation of cull sow digital images at a midwestern harvest facility." Applied Animal Science 38, no. 6 (2022): 627-638. DOI: 10.15232/aas.2022-02295. Copyright 2022 Elsevier. Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). Posted with permission.
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