Physiologie, Environnement, Génétique pour l'Animal et les Systèmes d'Elevage (PEGASE), INRAE, Institut Agro, 35590, Saint Gilles, France.
Physiologie, Environnement, Génétique pour l'Animal et les Systèmes d'Elevage (PEGASE), INRAE, Institut Agro, 35590, Saint Gilles, France.
J Dairy Sci. 2022 May;105(5):4508-4519. doi: 10.3168/jds.2021-21337. Epub 2022 Feb 25.
Three-dimensional (3D) imaging offers new possibilities in animal phenotyping. Here, we investigated how this technology can be used to study the morphological changes that occur in dairy cows over the course of a single lactation. First, we estimated the individual body weight (BW) of dairy cows using traits measured with 3D images. To improve the quality of prediction, we monitored body growth (via 3D imaging), gut fill (via individual dry matter intake), and body reserves (via body condition score) throughout lactation. A group of 16 Holstein cows-8 in their first lactation, 4 in their second lactation, and 4 in their third or higher lactation-was scanned in 3D once a month for an entire lactation. Values of morphological traits (e.g., chest depth or hip width) increased continuously with parity, but cows in their first lactation experienced the largest increase during the monitoring period. Values of partial volume, estimated from point of shoulder to pin bone, predicted BW with an error of 25.4 kg (R = 0.92), which was reduced to 14.3 kg when the individual effect of cows was added to the estimation model. The model was further improved by the addition of partial surface area (from point of shoulder to pin bone), hip width, chest depth, diagonal length, and heart girth, which increased the R of BW prediction to 0.94 and decreased root mean square error to 22.1 kg. The different slopes for individual cows were partly explained by body condition score and morphological traits, indicating that they may have reflected differences in body density among animals. Changes in BW over the course of lactation were mostly due to changes in growth, which accounted for around two-thirds of BW gain regardless of parity. Body reserves and gut fill had smaller but still notable effects on body composition, with a higher gain in body reserves and gut fill for cows in their first lactation compared with multiparous cows. This work demonstrated the potential for rapid and low-cost 3D imaging to facilitate the monitoring of several traits of high interest in dairy livestock farming.
三维(3D)成像在动物表型研究中提供了新的可能性。在这里,我们研究了这项技术如何用于研究奶牛在单个泌乳期内发生的形态变化。首先,我们使用 3D 图像测量的特征来估计奶牛的个体体重(BW)。为了提高预测质量,我们在整个泌乳期内监测了身体生长(通过 3D 成像)、肠道充盈(通过个体干物质摄入)和体储备(通过体况评分)。一组 16 头荷斯坦奶牛-8 头处于第一泌乳期,4 头处于第二泌乳期,4 头处于第三泌乳期或更高泌乳期-在整个泌乳期内每月进行一次 3D 扫描。形态特征值(例如,胸深或髋宽)随胎次连续增加,但处于第一泌乳期的奶牛在监测期间经历了最大的增加。从肩点到骨盆骨的部分体积值,用 25.4 公斤的误差(R = 0.92)预测 BW,当将奶牛的个体效应添加到估计模型中时,误差降低到 14.3 公斤。通过添加部分表面积(从肩点到骨盆骨)、髋宽、胸深、对角线长度和胸围,该模型进一步得到了改进,这增加了 BW 预测的 R 至 0.94,并将均方根误差降低至 22.1 公斤。不同奶牛的斜率差异部分由体况评分和形态特征解释,这表明它们可能反映了动物之间的体密度差异。泌乳期内 BW 的变化主要归因于生长的变化,无论胎次如何,生长变化约占 BW 增加的三分之二。体储备和肠道充盈对体成分有较小但仍显著的影响,处于第一泌乳期的奶牛体储备和肠道充盈增加幅度高于多胎奶牛。这项工作证明了快速、低成本的 3D 成像技术在监测奶牛养殖中几个高关注度性状方面具有潜力。