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Changes in Tail Posture Detected by a 3D Machine Vision System Are Associated with Injury from Damaging Behaviours and Ill Health on Commercial Pig Farms

PLoS ONE(2021)SCI 3区

SRUC | Innovent Technol Ltd | Garth Pig Practice Ltd

Cited 9|Views19
Abstract
To establish whether pig tail posture is affected by injuries and ill health, a machine vision system using 3D cameras to measure tail angle was used. Camera data from 1692 pigs in 41 production batches of 42.4 (±16.6) days in length over 17 months at seven diverse grower/finisher commercial pig farms, was validated by visiting farms every 14(±10) days to score injury and ill health. Linear modelling of tail posture found considerable farm and batch effects. The percentage of tails held low (0°) or mid (1–45°) decreased over time from 54.9% and 23.8% respectively by -0.16 and -0.05%/day, while tails high (45–90°) increased from 21.5% by 0.20%/day. Although 22% of scored pigs had scratched tails, severe tail biting was rare; only 6% had tail wounds and 5% partial tail loss. Adding tail injury to models showed associations with tail posture: overall tail injury, worsening tail injury, and tail loss were associated with more pigs detected with low tail posture and fewer with high tails. Minor tail injuries and tail swelling were also associated with altered tail posture. Unexpectedly, other health and injury scores had a larger effect on tail posture- more low tails were observed when a greater proportion of pigs in a pen were scored with lameness or lesions caused by social aggression. Ear injuries were linked with reduced high tails. These findings are consistent with the idea that low tail posture could be a general indicator of poor welfare. However, effects of flank biting and ocular discharge on tail posture were not consistent with this. Our results show for the first time that perturbations in the normal time trends of tail posture are associated with tail biting and other signs of adverse health/welfare at diverse commercial farms, forming the basis for a decision support system.
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要点】:本研究使用3D机器视觉系统检测商业养猪场猪只尾部姿态的变化,发现与损伤行为和健康问题有关,创新性地提出了尾部姿态变化可作为判断猪只福利状况的指标。

方法】:采用3D摄像头测量猪只尾部角度的机器视觉系统,收集了17个月内7个不同商业养猪场1692只猪的摄像头数据,并通过每隔14天访问农场对猪只的损伤和健康情况进行评分来验证。

实验】:通过线性建模分析发现农场和批次之间存在显著差异。随着时间的推移,低位尾部姿态(0°)和中等位姿(1-45°)的比例下降,而高位姿态(45-90°)的比例增加。添加尾部损伤到模型中发现,尾部损伤与尾部姿态有关:整体尾部损伤、尾部损伤加重和尾部缺失都与低位尾部姿态的猪只增多和高位尾部姿态的猪只减少有关。轻微尾部损伤和尾部肿胀也与尾部姿态的变化有关。结果还显示,其他健康和损伤评分对尾部姿态的影响更大 - 当围栏内更大比例的猪只出现跛行或由社会攻击行为引起的损伤时,观察到更多的低位尾部姿态。耳朵损伤与高位尾部姿态减少有关。这些发现支持低位尾部姿态可能是猪只福利状况的一般指标的观点。然而,背部咬伤和眼部分泌物对尾部姿态的影响与这一观点不一致。这是首次显示,养猪场商业猪只尾部姿态的正常时间趋势的变化与尾部咬伤和其他健康/福利不良迹象有关,为决策支持系统提供了依据。