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Presentation
Characterization of a machine vision system to assess gestating sow space usage
Agricultural and Biosystems Engineering Conference Proceedings and Presentations
  • Suzanne Leonard, Iowa State University
  • Hongwei Xin, University of Tennessee, Knoxville
  • Tami M. Brown-Brandl, University of Nebraska - Lincoln
  • Brett C. Ramirez, Iowa State University
  • John P. Stinn, Iowa Select Farms
  • Anna Johnson, Iowa State University
  • Kai Liu, City University of Hong Kong
Document Type
Presentation
Conference
ASABE Annual International Meeting
Publication Version
Published Version
Publication Date
1-1-2019
DOI
10.13031/aim.201900782
Conference Title
ASABE Annual International Meeting
Conference Date
July 7–10, 2019
Geolocation
(42.3600825, -71.05888010000001)
Abstract

Physical space allocation for animals is an important consideration when designing animal production facilities. This physical space is defined by the length, width, and height of a volume designated to an individual animal. Animals require static space when stationary, but additional space is needed to perform dynamic postural transitions. Inadequate space to perform basic behaviors and postural adjustments can reduce productivity and welfare. Conversely, excess space introduces inefficiencies, resulting in production losses and unnecessary construction expenses. The most commonly used sow space guidelines were published in the 1980s. Therefore, modern commercial sow’s static and dynamic space requirements must be studied to provide evidence-based guidelines for current producers. Such information can be accurately assessed with the use of time-of-flight depth image sensors. A process to develop calibration equations to convert the depth image pixel measurements into physical dimensions was developed and error was assessed. Sample data collected on structurally sound commercial sows (Landrace × Yorkshire) in late gestation (11-15 weeks) of various parities is described. Length, width, and height of the space utilized by sows were calculated for static positions defined as standing and lateral lying, as well as dynamic sequences defined as standing up and lying down. Results can be used to develop relationships between sow body weight and three dimensional static and dynamic space requirements. This information can be used to inform gestation housing design decisions.

Comments

This presentation is published as Leonard, Suzanne, Hongwei Xin, Tami M. Brown-Brandl, Brett C. Ramirez, John P. Stinn, Anna Johnson, and Kai Liu. "Characterization of a machine vision system to assess gestating sow space usage." ASABE Annual International Meeting. Boston, MA. July 7-10, 2019. Paper No.1900782. DOI: 10.13031/aim.201900782. Posted with permission.

Copyright Owner
American Society of Agricultural and Biological Engineers
Language
en
File Format
application/pdf
Citation Information
Suzanne Leonard, Hongwei Xin, Tami M. Brown-Brandl, Brett C. Ramirez, et al.. "Characterization of a machine vision system to assess gestating sow space usage" Boston, MA(2019) p. 1900782
Available at: http://works.bepress.com/anna_butters-johnson/327/