Girardie Océane, Bonneau Mathieu, Billon Yvon, Bailly Jean, David Ingrid, Canario Laurianne
UMR1388 GenPhySE, INRAE, Université de Toulouse, INPT, Castanet-Tolosan, France.
UR0143 ASSET, INRAE, Petit-Bourg, France.
Front Vet Sci. 2023 Jan 9;9:1051284. doi: 10.3389/fvets.2022.1051284. eCollection 2022.
An activity pattern describes variations in activities over time. The objectives of this study are to automatically predict sow activity from computer vision over 11 days peripartum and estimate how sow behavior influences piglet's performance during early lactation. The analysis of video images used the convolutional neural network (CNN) YOLO for sow detection and posture classification of 21 Large White and 22 Meishan primiparous sows housed in individual farrowing pens. A longitudinal analysis and a clustering method were combined to identify groups of sows with a similar activity pattern. Traits under study are as follows: (i) the distribution of time spent daily in different postures and (ii) different activities while standing. Six postures were included along with three classes of standing activities, i.e., eating, drinking, and other, which can be in motion or not and root-pawing or not. They correspond to a postural budget and a standing-activity budget. Groups of sows with similar changes in their budget over the period (D-3 to D-1; D0 and D1-D7) were identified with the k-means clustering method. Next, behavioral traits (time spent daily in each posture, frequency of postural changes) were used as explanatory variables in the Cox proportional hazards model for survival and in the linear model for growth. Piglet survival was influenced by sow behavior on D-1 and during the period D1-D7. Piglets born from sows that were standing and doing an activity other than drinking and eating on D-1 had a 26% lower risk of dying than other piglets. Those born from sows that changed posture more frequently on D1-D7 had a 44% lower risk of dying. The number of postural changes, which illustrate sow restlessness, influenced piglet growth in the three periods. The average daily gain of piglets born from sows that were more restless on D1-D7 and that changed posture more frequently to hide their udder on D0 decreased by 22 and 45 g/d, respectively. Conversely, those born from sows that changed posture more frequently to hide their udder during the period of D1-D7 grew faster (+71 g/d) than the other piglets. Sow restlessness at different time periods influenced piglet performance.
活动模式描述了活动随时间的变化情况。本研究的目的是通过计算机视觉在围产期的11天内自动预测母猪的活动，并估计母猪行为对泌乳早期仔猪性能的影响。视频图像分析使用卷积神经网络（CNN）YOLO对饲养在单独产仔栏中的21头大白初产母猪和22头梅山初产母猪进行检测和姿势分类。采用纵向分析和聚类方法来识别具有相似活动模式的母猪群体。所研究的特征如下：（i）每天在不同姿势下花费的时间分布，以及（ii）站立时的不同活动。包括六种姿势以及三类站立活动，即进食、饮水和其他活动，这些活动可以处于运动状态或静止状态，也可以有或没有拱刨行为。它们分别对应姿势预算和站立活动预算。使用k均值聚类方法识别了在该时间段（产前3天至产前1天；分娩当天和产后1至7天）内预算变化相似的母猪群体。接下来，行为特征（每天在每种姿势下花费的时间、姿势变化频率）被用作Cox比例风险模型中仔猪存活情况的解释变量，以及线性模型中仔猪生长情况的解释变量。仔猪存活情况受母猪在产前1天和产后1至7天行为的影响。在产前1天站立并进行除饮水和进食以外其他活动的母猪所产仔猪死亡风险比其他仔猪低26%。在产后1至7天姿势变化更频繁的母猪所产仔猪死亡风险低44%。姿势变化次数反映了母猪的不安程度，在三个时间段内对仔猪生长均有影响。在产后1至7天更不安且在分娩当天更频繁地改变姿势以隐藏乳房的母猪所产仔猪的平均日增重分别降低了22克/天和45克/天。相反，在产后1至7天更频繁地改变姿势以隐藏乳房的母猪所产仔猪比其他仔猪生长得更快（快71克/天）。不同时间段母猪的不安程度会影响仔猪的性能。
