Agroscope, Ruminant Research Unit, Route de la Tioleyre 4, 1725 Posieux, Switzerland.
INRAE, Université Clermont Auvergne, Vetagro Sup, UMR Herbivores, 63122 Saint-Genès-Champanelle, France.
Methods. 2021 Feb;186:68-78. doi: 10.1016/j.ymeth.2020.06.014. Epub 2020 Jun 27.
The objective was to compare eight methods for estimation of dairy goat body composition, by calibrating against chemical composition (water, lipid, protein, mineral and energy) measured post-mortem. The methods tested on 20 Alpine goats were body condition score (BCS), 3-dimension imaging (3D) automatic assessment of BCS or whole body scan, ultrasound, computer tomography (CT), adipose cell diameter, deuterium oxide dilution space (DOS) and bioelectrical impedance spectroscopy (BIS). Regressions were tested between predictive variates derived from the methods and empty body (EB) composition. The best equations for estimation of EB lipid mass included BW combined with i) perirenal adipose tissue mass and cell diameter (R = 0.95, residual standard deviation, rSD = 0.57 kg), ii) volume of fatty tissues measured by CT (R = 0.92, rSD = 0.76 kg), iii) DOS (R = 0.91, rSD = 0.85 kg), and iv) resistance at infinite frequency from BIS (R = 0.87, rSD = 1.09 kg). The DOS combined with BW provided the best equation for EB protein mass (R = 0.97, rSD = 0.17 kg), whereas BW alone provided a fair estimate (R = 0.92, rSD = 0.25 kg). Sternal BCS combined with BW provided good estimation of EB lipid and protein mass (R = 0.80 and 0.95, rSD = 1.27 and 0.22 kg, respectively). Compared to manual BCS, BCS by 3D slightly decreased the precision of the predictive equation for EB lipid (R = 0.74, rSD = 1.46 kg), and did not improve the estimation of EB protein compared with BW alone. Ultrasound measurements and whole body 3D imaging methods were not satisfactory estimators of body composition (R ≤ 0.40). Further developments in body composition techniques may contribute for high-throughput phenotyping of robustness.
本研究旨在通过与死后化学组成（水、脂、蛋白、矿物质和能量）的比较，对 8 种估计奶山羊体组成的方法进行校准。在 20 只阿尔卑斯山羊身上测试的方法包括体况评分（BCS）、三维成像（3D）自动评估 BCS 或全身扫描、超声、计算机断层扫描（CT）、脂肪细胞直径、氘稀释空间（DOS）和生物电阻抗谱（BIS）。测试了从这些方法中得出的预测变量与空体（EB）组成之间的回归关系。用于估计 EB 脂质量的最佳方程包括 BW 与 i）肾周脂肪组织质量和细胞直径（R=0.95，残差标准差 rSD=0.57kg）、ii）CT 测量的脂肪组织体积（R=0.92，rSD=0.76kg）、iii）DOS（R=0.91，rSD=0.85kg）和 iv）BIS 无限频率下的电阻（R=0.87，rSD=1.09kg）的组合。DOS 与 BW 的结合为 EB 蛋白质质量提供了最佳方程（R=0.97，rSD=0.17kg），而 BW 单独使用则提供了一个相当准确的估计值（R=0.92，rSD=0.25kg）。胸骨 BCS 与 BW 结合可对 EB 脂类和蛋白质质量进行良好估计（R=0.80 和 0.95，rSD=1.27 和 0.22kg）。与手动 BCS 相比，3D 版 BCS 略微降低了 EB 脂质量预测方程的精度（R=0.74，rSD=1.46kg），与 BW 单独使用相比，对 EB 蛋白质的估计也没有改善。超声测量和全身 3D 成像方法不是体成分的满意估计器（R≤0.40）。体成分技术的进一步发展可能有助于实现稳健性的高通量表型分析。
