Herring W O, Kriese L A, Bertrand J K, Crouch J
University of Missouri, Columbia 65211, USA.
J Anim Sci. 1998 Feb;76(2):364-70. doi: 10.2527/1998.762364x.
Eighty-one crossbred steers were used to evaluate four commercially available ultrasound systems that predict intramuscular fat. The software systems represented included Animal Ultrasound Services, Inc., Ithaca, NY; CPEC, Oakley, KS; Critical Vision, Inc., Atlanta, GA (CVIS); and Classic Ultrasound Equipment, Tequesta, FL. Systems were evaluated using marbling scores and percentage ether extractable fat of the longissimus muscle. Before statistical analyses, system predictions were corrected for the respective system's average deviation between the prediction and carcass measurement. The absolute difference between system prediction and percentage ether extract (EEADIFF) or marbling score (MADIFF) converted to ether extract by regression was analyzed with a model accounting for effects of system, technician within system, animal, and animal x system. Steers with USDA marbling scores less than Small00 were assigned to a low marbling class, and all others were assigned to a second class. Data were then analyzed with a subsequent model including marbling class. For EEADIFF in the first model, system, animal, and system x animal were significant (P < .001). For MADIFF, technician within system (P < .05) and all other effects (P < .001) were significant. In the second model, system x marbling class was significant (P < .05) for EEADIFF and approached significance for MADIFF (P = .17). Least squares means for EEADIFF indicated that the systems were more precise measuring animals in the low marbling class. Finally, the CPEC and CVIS systems were the most precise for predicting intramuscular fat.
选用81头杂交阉牛来评估四种市售的用于预测肌内脂肪的超声系统。所代表的软件系统包括纽约伊萨卡的动物超声服务公司;堪萨斯州奥克利的CPEC;佐治亚州亚特兰大的Critical Vision公司(CVIS);以及佛罗里达州特凯斯塔的经典超声设备公司。使用大理石花纹评分和背最长肌的乙醚可提取脂肪百分比对各系统进行评估。在进行统计分析之前,对系统预测值进行校正,以消除各系统预测值与胴体测量值之间的平均偏差。通过一个考虑系统、系统内技术人员、动物以及动物×系统效应的模型,分析系统预测值与乙醚提取物百分比(EEADIFF)或通过回归转换为乙醚提取物的大理石花纹评分(MADIFF)之间的绝对差值。美国农业部大理石花纹评分小于Small00的阉牛被归为低大理石花纹等级,其他所有阉牛被归为第二个等级。然后使用包含大理石花纹等级的后续模型对数据进行分析。对于第一个模型中的EEADIFF,系统、动物以及系统×动物效应显著(P < 0.001)。对于MADIFF,系统内技术人员效应(P < 0.05)以及所有其他效应(P < 0.001)显著。在第二个模型中,对于EEADIFF,系统×大理石花纹等级效应显著(P < 0.05),对于MADIFF接近显著(P = 0.17)。EEADIFF的最小二乘均值表明,各系统在测量低大理石花纹等级的动物时更为精确。最后,CPEC和CVIS系统在预测肌内脂肪方面最为精确。