Prediction of retail beef yield and fat content from live animal and carcass measurements in Nellore cattle1

Abstract

Data from 156 Nellore males were used to develop equations for the prediction of retail beef yield and carcass fat content, expressed as kilograms and as a percentage, from live animal and carcass measurements. Longissimus muscle area and backfat and rump fat thickness were measured by ultrasound up to 5 d before slaughter and fasted live weight was determined 1 d before slaughter. The same traits were obtained after slaughter. The carcass edible portion (CEP in kg and CEP% in percentage; n = 116) was calculated by the sum of the edible portions of primal cuts: hindquarter, forequarter, and spare ribs. Trimmable fat from the carcass boning process, with the standardization of about 3 mm of fat on retail beef, was considered to be representative of carcass fat content. Most of the variation in CEP was explained by fasted live weight or carcass weight (R(2) of 0.92 and 0.96); the same occurred for CEP% (R(2) of 0.15 and 0.13), and for CEP, the inclusion of LM area and fat thickness reduced the equation bias (lower value of Mallow's Cp statistics). For trimmable fat, most variation could be explained by weight or rump fat thickness. In general, the equations developed from live animal measurements showed a predictive power similar to the equations using carcass measurements. In all cases, the traits expressed as kilograms were better predicted (R(2) of 0.39 to 0.96) than traits expressed as a percentage (R(2) of 0.08 to 0.42).

Sample size and prediction of weight and yield of individual cuts from Braford steers pistol hindquarters

“…The addition of ULMA and UFAT variables to the regressions of PHW and RW on live measures did not result in large increases in R 2 but did lead to reduced lack of fit (C p ≈ p) and reduced residual variance. Equations of FQW and PHW with carcass measures as independent variables fit better based on R 2 , C p , and RMSE than equations with live measures as in-found fat depth to be an important predictor of FAT (Perkins et al, 1992;Robinson et al, 1992;Bergen et al, 2005;Sakamoto et al, 2014). The discrepancy between the present study and those conducted previously may be due to the relative leanness of the cattle in this study.…”

“…This is again expected, as HQRTP is a substantial portion of HCW. Previous studies have found fat depth measured with ultrasound to be an important predictor of HQRTP (Greiner et al, 2003;Tarouco et al, 2007;Silva et al, 2012;Sakamoto et al, 2014). In the present study, a positive relationship was observed between HQRTP and UFAT, demonstrating that the first variable increases as consequence of the increase of the second.…”

“…In the present study, a positive relationship was observed between HQRTP and UFAT, demonstrating that the first variable increases as consequence of the increase of the second. Studies in which the amount of subcutaneous fat are high, the sign of coefficients are negative in relation to the amount of HQRTP (Silva et al, 2012;Sakamoto et al, 2014), as well as the amount of wholesale retail product (Greiner et al, 2003;Sakamoto et al, 2014). However, when the subcutaneous fat are low, the sign of coefficient change for a positive influence for HQRTP (0.150) as demonstrated by Tarouco et al (2007).…”

“…There is also interest in yield (composition) of the carcass and retail product. Despite longstanding recognition of the inadequacy of percentages as measures of composition (Weil, 1962;Miller and Weil, 1963;Dinkel et al, 1965;Sakamoto et al, 2014;Huerta-Leidenz et al, 2018), such practice has been commonplace in studies similar to this one. Here, use of regression on SBW or HCW with variation in the deviations from the regression is advocated as being indicative of differences among animals in composition.…”

Carcass and meat traits of feedlot Nellore bulls fed different dietary energy sources

“…The carcass cuts were divided into hindquarter, forequarter, and spare ribs (Yokoo et al, 2003). Only the left carcass side was used for measurement of the cuts and the records were multiplied by two to obtain the result for the whole carcass (Sakamoto et al, 2014). The hot carcass yield (CY) was calculated using the following equation: CY = hot carcass weight /FLW × 100.…”