S. Leonard, H. Xin, B. Ramirez, John P. Stinn, Somak Dutta, Kai Liu, T. Brown-Brandl
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引用次数: 0
Abstract
HighlightsA calibration procedure was conducted using a Kinect V2 to convert image pixels to physical measurements.A total of 61 sows were observed, and their static and dynamic space usage was measured from depth images.Equations were developed to predict the length, width, and height of sow space usage.Abstract. The amount of space provided to individually housed sows has both financial and animal welfare implications. Many U.S. swine producers use stall dimensions based on recommendations published in the 1980s (length × width × height: 2.13 m × 0.61 m × 1.00 m). Limited empirical data are available concerning the space allocation needed to accommodate modern sows housed in stalls during breeding, gestation, or farrowing. This study used a time-of-flight depth sensor to quantify static and dynamic space usage of 61 modern sows in late gestation. A calibration equation was developed to convert image pixels to physical dimensions. Statistical models were developed to relate the length, width, and height of sow space usage to body weight. The dimensions of sow space usage were then predicted. Results showed that free choice space usage of average (228 kg) sows was 1.96 m × 1.15 m × 0.93 m (length × width × height). For 95th percentile (267 kg) sows, space usage was 2.04 m × 1.12 m × 0.95 m. The width of space usage was primarily attributed to sow body depth when lying recumbent and the dynamic space used for transitioning between postures. These results help to inform future gestating and farrowing sow housing designs. Further work is needed to understand how restrictions on sow space usage may impact sow welfare and production performance, as well as the space needed to perform behaviors such as defecating, feeding, and turning around. Keywords: Animal welfare, Computer vision, Farrowing stall, Gestation stall, Kinect V2, Space allowance.
期刊介绍:
This peer-reviewed journal publishes research that advances the engineering of agricultural, food, and biological systems. Submissions must include original data, analysis or design, or synthesis of existing information; research information for the improvement of education, design, construction, or manufacturing practice; or significant and convincing evidence that confirms and strengthens the findings of others or that revises ideas or challenges accepted theory.