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Prediction of retail product weight and percentage using ultrasound and carcass measurements in beef cattle

机译:在牛肉中预测零售产品重量和百分比用牛肉测量

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摘要

Data from 534 steers representing six sire breed groups were used to develop live animal ultrasound prediction equations for weight and percentage of retail product. Steers were ultrasonically measured for 12th-rib fat thickness (UFAT), rump fat thickness (URPFAT), longissimus muscle area (ULMA), and body wall thickness (UBDWALL) within 5 d before slaughter. Carcass measurements included in USDA yield grade (YG) and quality grade calculations were obtained. Carcasses were fabricated into boneless, totally trimmed retail products. Regression equations to predict weight and percentage of retail product were developed using either live animal or carcass traits as independent variables. Most of the variation in weight of retail product was accounted for by live weight (FWT) and carcass weight with R2 values of 0.66 and 0.69, respectively. Fat measurements accounted for the largest portion of the variation in percentage of retail product when used as single predictors (R2 = 0.54, 0.44, 0.23, and 0.54 for UFAT, URPFAT, UBDWALL, and carcass fat, respectively). Final models (P u3c 0.10) using live animal variables included FWT, UFAT, ULMA, and URPFAT for retail product weight (R2 = 0.84) and UFAT, URPFAT, ULMA, UBDWALL, and FWT for retail product percentage (R2 = 0.61). Comparatively, equations using YG variables resulted in R2 values of 0.86 and 0.65 for weight and percentage of retail product, respectively. Results indicate that live animal equations using ultrasound measurements are similar in accuracy to carcass measurements for predicting beef carcass composition, and alternative ultrasound measurements of rump fat and body wall thickness enhance the predictive capability of live animal-based equations for retail yield.
机译:来自534个代表六个SiRe品种组的阉牛的数据用于开发用于零售产品的重量和百分比的活动物超声预测方程。在屠宰前,对于第12肋脂肪厚度(UFAT),臀部脂肪厚度(URPFAT),长杆脂肪厚度(ULPFAT),长杆脂肪厚度(ULPFAT),长杆肌肉区域(ULPWALL),堆纤维厚度(ULPFAL)和体壁厚度(UBDWALL)。获得USDA产量等级(YG)中包含的胴体测量和质量级计算。胴体被制成骨肉,完全修剪的零售产品。使用活的动物或胴体特征作为独立变量,开发了预测零售产品重量和百分比的回归方程。零售产品重量的大部分变化分别由活重(FWT)和胴体重量分别为0.66和0.69的R2值。脂肪测量值占零售产品百分比变化的最大部分,当用作单一预测器时(R2 = 0.54,0.44,0.23和0.54分别用于UFAT,URPFAT,UBDWALL和胴体脂肪)。使用Live Animal Variables的最终模型(P U3C 0.10)包括FWT,UFAT,ULMA和用于零售产品重量的URPFAT(R2 = 0.84)和UFAT,URPFAT,ULMA,UBDWALL和FWT,用于零售产品百分比(R2 = 0.61) 。相比之下,使用YG变量的等式导致R2值分别为0.86和0.65,分别为零售产品的重量和百分比。结果表明,使用超声测量的实时动物方程在预测牛肉组合物预测牛肉组合物的准确性和体壁厚度的替代超声测量,提高了基于动物的零售产量方程的预测能力。

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