Waltner S S, McNamara J P, Hillers J K, Brown D L
Department of Animal Sciences, Washington State University, Pullman 99164-6320.
J Dairy Sci. 1994 Sep;77(9):2570-9. doi: 10.3168/jds.S0022-0302(94)77198-8.
The objective of the study was to establish and compare equations that would estimate the body fat content of lactating dairy cows from different indirect techniques. The techniques used were body condition scoring, dilution of D2O in body water, and determination of mean fat cell size diameter of the subcutaneous, abdominal, and perirenal depots. Each technique was validated against direct determination of body fat content of the same lactating cows. To apply equations to high producing, lactating dairy cows, cows were from a herd producing more than 9500 kg of FCM/305 d, were lactating, and were in less than average body condition. Eight days prior to slaughter, a single injection of D2O was injected into the jugular vein, and body dilution was followed for 4 d. Cows were scored for body condition on the day of injection and weighed daily for the 4 d prior to slaughter. Samples of subcutaneous, perirenal, and omental adipose depots were taken, and adipocyte size and number were determined. Body fat was not predicted well by D2O space alone, but inclusion of BW did improve the prediction of body fat from this variable. The best equations were derived from use of BW with body condition score or subcutaneous fat cell diameter: observed body fat = -122.1 + .21 x BW + 36.0 x body condition score, and -195.6 + .290 x BW + .927 x subcutaneous fat cell diameter; standard errors of the estimate were 4.6 and 5.5 kg, respectively. Equations using diameters of abdominal and perirenal fat cells gave similar relationships. Equations using all four predictors (live BW, fat cell diameter, condition score, and D2O space) were only slightly improved over these equations. Thus, use of body condition score, adipocyte diameter, and BW in laboratory and field conditions may help in the study and management of the use of body fat in lactating dairy cows.
本研究的目的是建立并比较通过不同间接技术估算泌乳奶牛体脂含量的方程。所使用的技术包括体况评分、重水（D2O）在体内水分中的稀释以及皮下、腹部和肾周脂肪库平均脂肪细胞大小直径的测定。每种技术都通过直接测定相同泌乳奶牛的体脂含量进行了验证。为了将方程应用于高产泌乳奶牛，选取了来自一个产奶量超过9500千克标准乳（FCM）/305天的牛群、处于泌乳期且体况低于平均水平的奶牛。在屠宰前8天，将单次注射的重水注入颈静脉，并跟踪4天的身体稀释情况。在注射当天对奶牛进行体况评分，并在屠宰前4天每天称重。采集皮下、肾周和网膜脂肪库的样本，测定脂肪细胞大小和数量。仅通过重水空间不能很好地预测体脂，但加入体重（BW）确实改善了基于该变量对体脂的预测。最佳方程来自于体重与体况评分或皮下脂肪细胞直径的结合使用：观察到的体脂=-122.1 + 0.21×体重 + 36.0×体况评分，以及-195.6 + 0.290×体重 + 0.927×皮下脂肪细胞直径；估计的标准误差分别为4.6千克和5.5千克。使用腹部和肾周脂肪细胞直径的方程给出了类似的关系。使用所有四个预测因子（活体重、脂肪细胞直径、体况评分和重水空间）的方程相比这些方程仅略有改进。因此，在实验室和现场条件下使用体况评分、脂肪细胞直径和体重可能有助于研究和管理泌乳奶牛体脂的利用情况。
