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

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 < 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.     

The relationship between ultrasound measurements and carcass fat thickness and longissimus muscle area in beef cattle

Five hundred thirty-four steers were evaluated over a 2-yr period to determine the accuracy of ultrasonic estimates of carcass 12th-rib fat thickness (CFAT) and longissimus muscle area (CLMA). Within 5 d before slaughter, steers were ultrasonically measured for 12th-rib fat thickness (UFAT) and longissimus muscle area (ULMA) using an Aloka 500V real-time ultrasound machine equipped with a 17.2-cm, 3.5-MHz linear transducer. Overall, correlation coefficients between ultrasound and carcass fat and longissimus muscle area were 0.89 and 0.86, respectively. Correlations for UFAT with CFAT were similar between years (0.86 and 0.90), whereas the relationship between ULMA and CLMA was stronger in yr 1 (r = 0.91; n = 282) than in yr 2 (r = 0.79; n = 252). Differences between ultrasonic and carcass measurements were expressed on both an actual (FDIFF and RDIFF) and absolute (FDEV and RDEV) basis. Mean FDIFF and RDIFF indicated that ultrasound underestimated CFAT by 0.06 cm and overestimated CLMA by 0.71 cm2 across both years. Overall mean FDEV and RDEV, which are indications of the average error rate, were 0.16 cm and 3.39 cm2, respectively. Analysis of year effects revealed that FDIFF, FDEV, and RDEV were greater (P < 0.01) in magnitude in yr 1. Further analysis of FDEV indicated that leaner (CFAT < 0.51 cm) cattle were overestimated and that fatter (CFAT > 1.02 cm) cattle were underestimated with ultrasound. Similarly, steers with small CLMA (< 71.0 cm2) were overestimated, and steers with large CLMA (> 90.3 cm2) were underestimated. The thickness of CFAT had an effect (P < 0.05) on the error of UFAT and ULMA measurements, with leaner animals being more accurately evaluated for both traits. Standard errors of prediction (SEP) adjusted for bias of ultrasound measurements were 0.20 cm and 4.49 cm2 for UFAT and ULMA, respectively. Differences in SEP were observed for ULMA, but not UFAT, by year. These results indicate that ultrasound can be an accurate estimator of carcass traits in live cattle when measurements are taken by an experienced, well-trained technician, with only small differences in accuracy between years.     

Prediction of retail product and trimmable fat yields from the four primal cuts in beef cattle using ultrasound or carcass data

The most widely used system to predict percentage of retail product from the four primal cuts of beef is USDA yield grade. The purpose of this study was to determine whether routine ultrasound measurements and additional rump measurements could be used in place of the carcass measurements used in the USDA yield grade equation to more accurately predict the percentage of saleable product from the four primals. This study used market cattle (n = 466) consisting of Angus bulls, Angus steers, and crossbred steers. Live animal ultrasound measures collected within 7 d of slaughter were 1) scan weight (SCANWT); 2) 12th- to 13th-rib s.c. fat thickness (UFAT); 3) 12th- to 13th-rib LM area (ULMA); 4) s.c. fat thickness over the termination of the biceps femoris in the rump (URFAT; reference point); 5) depth of gluteus medius under the reference point (URDEPTH); and 6) area of gluteus medius anterior to the reference point (URAREA). Traditional carcass measures collected included 1) HCW; 2) 12th-to 13th-rib s.c. fat thickness (CFAT); 3) 12th- to 13th-rib LM area (CLMA); and 4) estimated percentage of kidney, pelvic, and heart fat (CKPH). Right sides of carcasses were fabricated into subprimal cuts, lean trim, fat, and bone. Weights of each component were recorded, and percentage of retail product from the four primals was expressed as a percentage of side weight. A stepwise regression was performed using data from cattle (n = 328) to develop models to predict percentage of retail product from the four primals based on carcass measures or ultrasound measures, and comparisons were made between the models. The most accurate carcass prediction equation included CFAT, CKPH, and CLMA (R2 = 0.308), whereas the most accurate live prediction equation included UFAT, ULMA, SCANWT, and URAREA (R2 = 0.454). When these equations were applied to a validation set of cattle (n = 138), the carcass equation showed R2 = 0.350, whereas the ultrasound data showed R2 = 0.460. Ultrasound measures in the live animal were potentially more accurate predictors of retail product than measures collected on the carcass.     

Use of ultrasound to predict body composition changes in steers at 100 and 65 days before slaughter

Steers from research crossbreeding projects (n = 406) were serially scanned using real-time ultrasound at 35-d intervals from reimplant time until slaughter. Cattle were evaluated for rump fat depth, longissimus muscle area (ULMA), 12th-rib fat thickness (UFAT), and percentage of intramuscular fat (IMF) to determine the ability of ultrasound to predict carcass composition at extended periods before slaughter. Additional background information on the cattle, such as live weight, ADG, breed of sire, breed of dam, implant, and frame score was also used. Carcass data were collected by trained personnel at "chain speed," and samples of the 12th-rib LM were taken for ether extract analysis. Simple correlation coefficients showed positive relationships (P < 0.01) between ultrasound measures taken less than 7 d before slaughter and carcass measures: ULMA and carcass LM area (CLMA, r = 0.66); UFAT and carcass 12th-rib fat thickness (CFAT, r = 0.74); and IMF and carcass numeric marbling score (r = 0.61). The same correlation coefficients for ultrasound measures taken 96 to 105 d before slaughter and carcass values (P < 0.01) were 0.52, 0.58, and 0.63, respectively. Steers were divided into source-verified and nonsource-verified groups based on the level of background information for each individual. Regression equations were developed for the carcass measurements; 46% of the variation could be explained for CLMA and 44% of CFAT at reimplant time, 46% of the variation in quality grade and 42% of the variation in yield grade could be explained. Significant predictors of quality grade were IMF (P < 0.001), natural log of 12th-rib fat thickness (LUFAT, P < 0.001), and ADG (P < 0.01), whereas LUFAT (P < 0.001), ULMA (P < 0.01), live weight (P < 0.001), hip height (P < 0.001), and frame score (P < 0.001) were significant predictors of yield grade. Regressions using ultrasound data taken 61 to 69 d before slaughter showed increasing R2. Live ultrasound measures at reimplant time are a viable tool for making decisions regarding future carcass composition.     

Gluteus medius and rump fat depths as additional live animal ultrasound measurements for predicting retail product and trimmable fat in beef carcasses.

This study was conducted to determine the ability of additional ultrasound measures to enhance the prediction accuracy of retail product and trimmable fat yields based on weight and percentage. Thirty-two Hereford-sired steers were ultrasonically measured for 12th-rib fat thickness, longissimus muscle area, rump fat thickness, and gluteus medius depth immediately before slaughter. Chilled carcasses were evaluated for USDA yield grade factors and then fabricated into closely trimmed, boneless subprimals with 0.32 cm s.c. fat. The kilogram weight of end-point product included the weight of trimmed, boneless subprimals plus lean trim weights, chemically adjusted to 20% fat, whereas the fat included the weight of trimmed fat plus the weight of fat in the lean trim. Prediction equations for carcass yield end points were developed using live animal or carcass measurements, and live animal equations were developed including ultrasound ribeye area or using only linear measurements. Multiple regression equations, with and without ultrasound rump fat thickness and gluteus medius depth, had similar R2 values when predicting kilograms of product and percentages of product, suggesting that these alternative variables explained little additional variation. Final unshrunk weight and ultrasound 12th-rib fat thickness explained most of the variation when predicting kilograms of fat. Rump fat and gluteus medius depth accounted for an additional 10% of the variation in kilograms of fat, compared with the equation containing final weight, ultrasound ribeye area, and ultrasound 12th-rib fat thickness; however, the two equations were not significantly different. Prediction equations for the cutability end points had similar R2 values whether live animal ultrasound measurements or actual carcass measurements were used. However, when ultrasound ribeye area was excluded from live animal predictions, lower R2 values were obtained for kilograms of product (0.81 vs 0.67) and percentages of product (0.41 vs 0.17). Conversely, the exclusion of ultrasound ribeye area had little effect on the prediction accuracy for kilograms of fat (0.75 vs 0.74) and percentage fat (0.50 vs 0.40). These data substantiate the ability of live animal ultrasound measures to accurately assess beef carcass composition and suggest that the alternative ultrasound measures, rump fat and gluteus medius depth, improve the accuracy of predicting fat-based carcass yields.     

Prediction of mature cow carcass composition from live animal measurements

Two trials were conducted with mature cows to develop prediction equations for estimating carcass composition from live animal measurements. Trial 1 involved 82 animals that were used to develop these equations. Subjective criteria (frame and condition scores) also were utilized along with live weight in development of prediction equations. Equations using subjective independent variables predicting energy and carcass tissue weights apparently were slightly more variable in precision (R2 = .69 to .91) than those developed with objective variables (R2 = .74 to .90). Equations predicting percent compositions from subjective variables had lower coefficients of determination (R2 = .49 to .76) than those developed with objective variables (R2 = .63 to .83). Forty-one animals similar to those used in Trial 1 served as a test group in Trial 2. Measured carcass composition was regressed on composition predicted by equations developed in Trial 1. These equations generally had slopes and intercepts with confidence intervals that included 0 and 1, respectively, indicating that most of the prediction equations were unbiased. This work indicates that carcass composition can be predicted from both objective and subjective measurements, with some accuracy and precision.     

Use of mononuclear leukocyte insulin receptor characteristics as predictors of carcass composition in heifers and steers

Total insulin specific binding (IB) and the number and affinity of insulin receptors on mononuclear leukocytes (MNL) were used to predict carcass composition of heifers and steers. Dependent variables were kidney fat, body cavity fat, s.c. fat, intermuscular fat, lean and bone. Independent variables were parameters that could be measured on the live animal, including insulin receptor characteristics, age, shrunk weight, breed and carcass s.c. rib fat thickness (SUB). All carcass fat characteristics and IB were greater for heifers than for steers, but the ability to predict either heifer or steer carcass fat characteristics was not improved by inclusion of IB in prediction equations. However, the number of low-affinity insulin receptors on MNL contributed significantly to the prediction of all heifer carcass characteristics except bone. Carcass s.c. rib fat thickness also entered the prediction equations for all heifer carcass characteristics except kidney fat. In the prediction of heifer kidney fat, the only significant independent variable was the number of low-affinity insulin receptors on MNL (R2 = .38). Carcass characteristics of steers were better predicted by SUB than were heifer carcass characteristics, and insulin receptor characteristics, when added to steer equations that contained SUB, improved R2 by .10 or less. Our results suggest that insulin receptor characteristics will be most useful in the prediction of carcass characteristics of heifers where there is a poor relationship between quantity of s.c. fat and other carcass fat depots.     

Prediction of Future Carcass Traits in Stocker Cattle at the Conclusion of Grazing

Prediction of eventual carcass traits in stocker cattle at the conclusion of grazing could be useful for culling, co-mingling of animals, feedlot pen assignments, and making management decisions in the feedyard. Ultrasound measures of 12th to 13th rib longissimus area (ULA) and fat thickness (UFAT), and off-pasture BW (OPBW) were collected from yearling cattle (n = 261) at the conclusion of grazing in two experiments that evaluated stocking rate and grazing management effects on rye (Secale cereale L.) annual ryegrass (Lolium multiflorum Lam.) pastures. Carcasss data were subsequently recorded at harvest following feedyard finishing to a visual 1-cm backfat. Correlations were analyzed to determine relationships between carcass traits and ULMA, UFAT, body condition measure (BCM), and OPBW. Ultrasound measures, breed type (BRDT; n = 4), gender (steers and heifers), and feedlot days on feed (DOF) were evaluated in multiple regression models to determine whether these variables influence eventual carcass percentage retail product, kilograms retail product (KRP), hot carcass weight (HCW), and marbling score. Ultrasound FAT and BCM were negatively correlated with percentage retail product, KRP, and HCW and were positively correlated with marbling score. All reduced regression models had R² values of between 0.15 and 0.63, and models with inputs of UFAT and OPBW consistently had the numerically greatest R² values and least RMSE. Multiple regression analyses indicated that prediction of carcass traits from stocker cattle ultrasonic measurements at the conclusion of grazing were possible, but improvement in the models will be necessary to reduce error and improve reliability.     

Using live estimates and ultrasound measurements to predict beef carcass cutability

Commercial slaughter steers (n = 329) and heifers (n = 335) were selected to vary in frame size, muscle score, and carcass fat thickness to study the effectiveness of live evaluation and ultrasound as predictors of carcass composition. Three trained personnel evaluated cattle for frame size, muscle score, fat thickness, longissimus muscle area, and USDA quality and yield grade. Live and carcass real-time ultrasound measures for 12th-rib fat thickness and longissimus muscle area were taken on a subset of the cattle. At the time of slaughter, carcass ultrasound measures were taken at "chain speed." After USDA grade data were collected, one side of each carcass was fabricated into boneless primals/subprimals and trimmed to .64 cm of external fat. Simple correlation coefficients showed a moderately high positive relationship between 12th rib fat thickness and fat thickness measures obtained from live estimates (r = .70), live ultrasound (r = .81), and carcass ultrasound (r = .73). The association between estimates of longissimus muscle area and carcass longissimus muscle area were significant (P < .001) and were higher for live evaluation (r = .71) than for the ultrasonic measures (live ultrasound, r = .61; carcass ultrasound, r = .55). Three-variable regression equations, developed from the live ultrasound measures, explained 57% of the variation in percentage yield of boneless subprimals, followed by live estimates (R2 = .49) and carcass ultrasound (R2 = .31). Four-variable equations using frame size, muscle score, and selected fat thickness and weight measures explained from 43% to 66% of the variation for the percentage yield of boneless subprimals trimmed to .64 cm. Live ultrasound and(or) live estimates are viable options for assessing carcass composition before slaughter.     

Commercial adaptation of ultrasonography to predict pork carcass composition from live animal and carcass measurements.

Live animal and carcass data were collected from market barrows and gilts (n = 120) slaughtered at a regional commercial slaughter facility to develop and test prediction equations to estimate carcass composition from live animal and carcass ultrasonic measurements. Data from 60 animals were used to develop these equations. Best results were obtained in predicting weight and percentage of boneless cuts (ham, loin, and shoulder) and less accuracy was obtained for predicting weight and ratio of trimmed, bone-in cuts. Independent variables analyzed for the live models were live weight, sex, ultrasonic fat at first rib, last rib, and last lumbar vertebra, and muscle depth at last rib. Independent variables for the carcass models included hot carcass weight, sex of carcass, and carcass ultrasonic measurements for fat at the first rib, last rib, last lumbar vertebra, and muscle depth at last rib. Equations were tested against an independent set of experimental animals (n = 60). Equations for predicting weight of lean cuts, boneless lean cuts, fat-standardized lean, and percentage of fat-standardized lean were most accurate from both live animal and carcass measurements with R2 values between .75 and .88. The results from this study, under commercial conditions, suggest that although live animal or carcass weight and sex were the greatest contributors to variation in carcass composition, ultrasonography can be a noninvasive means of differentiating value, especially for fat-standardized lean and weight of boneless cuts.     

Evaluation of carcass, live, and real-time ultrasound measures in feedlot cattle: II. Effects of different age end points on the accuracy of predicting the percentage of retail product, retail product weight, and hot carcass weight

Data from 970 feedlot steers and bulls were used to evaluate effects of different age end points on the accuracy of prediction models for percentage of retail product, retail product weight, and hot carcass weight. Cattle were ultrasonically scanned three to five times for fat thickness, longissimus muscle area, and percentage of intramuscular fat. Live animal measures of body weight and hip height were also taken during some of the scan sessions. Before development of prediction equations, live and ultrasound data were adjusted to four age end points using individual animal regressions. Age end points represented mean age at slaughter (448 d), mean age at the second-to-last scan before slaughter (414 d), mean age at the third-to-last scan before slaughter (382 d), and an age end point of 365 d. Ultrasound and live animal measures accounted for a large proportion of the variation in the dependent variables regardless of the age end point considered. For all three traits, final models based on independent variables adjusted to earlier ages of 365 and 382 d showed better or at least similar model R2 and root mean square errors than those based on independent variables adjusted to a mean slaughter age of 448 d. Validation of the models using independent data from 282 steers resulted in a mean across-age rank correlation coefficient of .78, .88, and .83 between actual and predicted values of the percentage of retail product, hot carcass weight, and retail product weight, respectively. Mean across-age rank correlation of breeding values for the corresponding traits were .92, .89, and .82. The results of this study suggest that live and ultrasound traits measured as early as 365 d could be used to predict end product traits as accurately as similar measures made before slaughter at age 448 d.     

Determination of saleable product in finished cattle and beef carcasses utilizing bioelectrical impedance technology

Two experiments were performed to develop prediction equations of saleable beef and to validate the prediction equations. In Exp. 1, 50 beef cattle were finished to typical slaughter weights, and multiple linear regression equations were developed to predict kilograms of trimmed boneless, retail product of live cattle, and hot and cold carcasses. A four-terminal bioelectrical impedance analyzer (BIA) was used to measure resistance (Rs) and reactance (Xc) on each animal and processed carcass. The IMPS cuts plus trim were weighed and recorded. Distance between detector terminals (Lg) and carcass temperature (Tp) at time of BIA readings were recorded. Other variables included live weight (BW), hot carcass weight (HCW), cold carcass weight (CCW), and volume (Lg2/Rs). Regression equations for predicting kilograms of saleable product were [11.87 + (.409 x BW) - (.335 x Lg) + (.0518 x volume)] for live (R2 = .80); [-58.83 + (.589 x HCW) - (.846 x Rs) + (1.152 x Xc) + (.142 x Lg) + (2.608 x Tp)] for hot carcass (R2 = .95); and [32.15 + (.633 x CCW) + (.33 x Xc) - (.83 x Lg) + (.677 x volume)] for cold carcass (R2 = .93). In Exp. 2, 27 beef cattle were finished in a manner similar to Exp. 1, and the prediction equations from Exp. 1 were used to predict the saleable product of these animals. The Pearson correlations between actual saleable product and the predictions based on live and cold carcass data were .91 and .95, respectively. The Spearman and Kendall rank correlations were .95 and .83, respectively, for the cold carcass data. These results provide a practical application of bioelectrical impedance for market-based pricing. They complement previous studies that assessed fat-free mass.     

Prediction of empty body components in steers by urea dilution

Empty body composition of 68 mixed-breed and 50 Angus steers was determined by chemical analysis of the right half-carcass and entire noncarcass fraction of each steer. Chemical composition was used to develop prediction equations for empty body protein (EBPRO) and fat (EBFAT) in steers using urea space (US) and body weight measurements. Previous research showed a significant positive correlation between empty body water (EBH2O) and urea space in these steers. For all steers studied, the percentage of EBH2O ranged from 44.8 to 69.2 (mean = 56.0), the percentage of EBPRO ranged from 14.1 to 19.8 (mean = 17.0) and the percentage of EBFAT ranged from 6.1 to 38.1 (mean = 22.1). The best predictions obtained were multiple regression equations with actual weight of body components as dependent variables and US and empty body weight (EB) as independent variables. Urea space alone was a poor predictor of EBFAT, but US improved predictions based on live weight (LW) or EB alone. Coefficients of determination for the best predictions of percentage of composition were not as high as coefficients of determination for the best predictions of actual weight of body components. These data suggest that US measurements can be used to predict empty body composition of live steers, but this may require repeated measurements and an independent estimate of EB from LW for greatest accuracy.     

Genetic evaluation of carcass yield using ultrasound measures on young replacement beef cattle

Live weight and ultrasound measures of fat thickness and longissimus muscle area were available on 404 yearling bulls and 514 heifers, and carcass measures of weight, longissimus muscle area, and fat thickness were available on 235 steers. Breeding values were initially estimated for carcass weight, longissimus muscle area, and fat thickness using only steer carcass data. Breeding values were also estimated for weight and ultrasound muscle area and fat thickness using live animal data from bulls and heifers, with traits considered sex-specific. The combination of live animal and carcass data were also used to estimate breeding values in a full animal model. Breeding values from the carcass model were less accurate and distributed more closely around zero than those from the live data model, which could at least partially be explained by differences in relative amounts of data and in phenotypic mean and heritability. Adding live animal data to evaluation models increased the average accuracy of carcass trait breeding values 91, 75, and 51% for carcass weight, longissimus muscle area, and fat thickness, respectively. Rank correlations between breeding values estimated with carcass vs live animal data were low to moderate, ranging from 0.16 to 0.43. Significant rank changes were noted when breeding values for similar traits were estimated exclusively with live animal vs carcass data. Carcass trait breeding values estimated with both live animal and carcass data were most accurate, and rank correlations reflected the relative contribution of carcass data and their live animal indicators. The addition of live animal data to genetic evaluation of carcass traits resulted in the most significant carcass trait breeding value accuracy increases for young replacements that had not yet produced progeny with carcass data.     

Prediction of swine carcass composition by total body electrical conductivity (TOBEC)

An experiment was conducted to determine prediction equations that used readings for total body electrical conductivity (TOBEC) in the model for estimation of total fat-free lean and total fat weight in the pork carcass. Ultrasound measurements of live hogs were used to select 32 gilts that represented a range in weight, muscling, and fatness. The TOBEC readings were recorded on warm carcass sides, chilled carcass sides, and the untrimmed ham from the left carcass side. Physical dissection and chemical analyses determined fat-free lean and fat weight of the carcass. All of the ham tissues were analyzed separately from the remainder of the carcass tissues to incorporate ham measurements for prediction of total fat-free lean and total fat weight in the entire carcass. Prediction equations were developed using stepwise regression procedures. An equation that used a warm carcass TOBEC reading in the model was determined to be the best warm TOBEC equation (R2 = 0.91; root mean square error = 0.81). A three-variable equation that used chilled carcass TOBEC reading, chilled carcass temperature, and carcass length in the model was determined to be the best chilled TOBEC equation (R2 = 0.93; root mean square error = 0.73). A four-variable equation that included chilled carcass side weight, untrimmed ham TOBEC reading, ham temperature, and fat thickness beneath the butt face of the ham in the model was determined to be the best equation overall (R2 = 0.95; root mean square error = 0.65). The TOBEC and the fat-free lean weight of the ham are excellent predictors of total carcass fat-free lean weight.     

Weaning,yearling, and preharvest ultrasound measures of fat and muscle area in steers,bulls, and heifers

Longissimus muscle area and fat thickness were measured following weaning, at yearling, and prior to harvest using real-time ultrasound, and corresponding carcass measurements were recorded 3 to 7 d following the preharvest scan in composite steers (n = 116, 447 +/- 19 d), bulls (n = 224, 521 +/- 11 d), and heifers (n = 257,532 +/- 12 d). Although fat deposition was limited in bulls and heifers from weaning to yearling, coefficients of variation ranged from 8.46 to 13.46% for muscle area, and from 27.55 to 38.95% for fat thickness, indicating that significant phenotypic variance exists across genders. Residual correlations, adjusted for the effects of year of birth, gender, and age at measurement, were high and ranged from 0.79 to 0.87 among ultrasound and carcass measures of muscle area. Residual correlations among ultrasound and carcass measures of fat thickness were also high, ranging from 0.64 to 0.86. Weaning and/or yearling ultrasound muscle area yielded similarly accurate predictions of carcass muscle area. Yearling ultrasound fat thickness accounted for 13% more of the observed variance in carcass fat thickness than the weaning ultrasound measure in single-trait prediction models. When both weaning and yearling ultrasound measures were used to predict carcass fat thickness, partial R2 values were 0.15 and 0.61 for weaning and yearling ultrasound fat thickness, respectively. The difference between predicted and carcass measures with respect to muscle area (fat thickness) was less than 6.45 cm2 (2.5 mm) for 80.2 to 88.9% (90.3 to 95%) of animals. Preharvest ultrasound measures yielded standard errors of prediction of less than 4.95 cm2 for muscle area and 1.51 mm or less for fat thickness. These results indicate that ultrasound measures taken between weaning and yearling provide accurate predictors of corresponding carcass traits in steers, bulls, and heifers.     

An evaluation of the USDA standards for feeder cattle frame size and muscle thickness

This study was conducted to determine the live weights at which large-, medium-, and small-framed feeder steers and heifers attain a degree of finish associated with a carcass quality grade of low Choice and to examine the relationship of feeder cattle muscle thickness to carcass yield grade traits. Feeder steers (n = 401) and heifers (n = 463) representing three age classes (calf, yearling, long yearling) were selected randomly at a commercial feedlot to exhibit wide ranges in frame size and muscularity. Individual weights were recorded and a panel of five experienced evaluators scored each animal for frame size, muscle thickness, and flesh condition. The cattle were finished on a high-concentrate finishing diet and harvested at an estimated carcass fat thickness of 10 mm. Final weights and USDA carcass grade data were collected for all cattle. Frame size scores effectively predicted finished weight at a marbling end point of Small(00) for both heifers (r2 = 0.89, SE = 16 kg) and steers (r2 = 0.94, SE = 13 kg). For heifers, the Small/Medium and Medium/ Large frame score intersects corresponded to live weights of 460 kg and 520 kg, respectively. For steers, the Small/Medium and Medium/Large frame score lines corresponded to live weights of 504 kg and 577 kg, respectively. These weights were greater than weights specified in the 1979 USDA grade standards. Evaluations of feeder cattle muscling, based on 1979 USDA Standards, were associated (P < 0.05) with differences in longissimus muscle area but were not related (P = 0.08) to differences in numerical carcass yield grades. An alternative muscle thickness classification scheme, involving the use of four thickness classes, was effective for stratifying feeder cattle according to eventual differences (P = 0.004) in carcass yield grade. Our findings suggest that USDA feeder cattle grade standards developed in 1979 are no longer adequate for describing today's population of feeder cattle.     

Evaluation of alternative measures of pork carcass composition

Carcass and live measurements of 203 pigs representing seven genetic populations and four target live weights (100, 114, 128, and 152 kg) were used to evaluate alternative measures of carcass composition. Measures of carcass lean (fat tissue-free lean, FFLM; lipid-free soft tissue, LFSTIS; and dissected lean in the four lean cuts, DL), fat (total carcass fat tissue, TOFAT), and lipid mass (soft tissue lipid, STLIP) were evaluated. Overall, LFSTIS was 22.8% greater than FFLM (47.8 vs 38.9 kg) and TOFAT was 30% greater than STLIP (38.5 vs 29.6 kg). The allometric growth coefficients relative to carcass weight were different for the measures: b = 0.776, 0.828, 0.794, 1.37, and 1.49 for FFLM, LFSTIS, DL, TOFAT, and STLIP, respectively. At 90 kg carcass weight, the predicted growth of FFLM, LFSTIS, TOFAT, and STLIP was 0.314, 0.420, 0.553, and 0.446 kg/kg increase in carcass weight. The difference between FFLM and LFSTIS, representing nonlipid components of the carcass fat tissue, was greater for barrows than for gilts (9.2 vs 8.6 kg). Lipid-free soft tissue mass was predicted more accurately from carcass or live animal measurements than FFLM with smaller relative RSD (4.6 vs 6.5% of their mean values). The alternative measures of carcass composition were evaluated as predictors of empty body protein (MTPRO) and lipid (MTLIP) mass. Empty body protein was predicted with similar accuracy (R2 = 0.74 to 0.81) from either DL, FFLM, LFSTIS, or ribbed carcass measurements. Empty body lipid was predicted more accurately from TOFAT (R2 = 0.92) or STLIP (R2 = 0.93) than ribbed carcass measurements (R2 = 0.88). Although the alternative measures of lean mass (LFSTIS vs FFLM) and lipid mass (TOFAT vs STLIP) were highly related to each other (r = 0.93 to 0.98), they had different relative growth rates (allometric coefficients) and thus cannot be predicted as linear functions of the similar alternative variable without significant weight group biases. From the 100- to 152-kg target weight groups, gilts gained 12.9% greater FFLM and 12.1% greater MTPRO but only 4.4% greater LFSTIS than barrows. Fat-free lean mass is more precise as a measure of muscle growth and as a predictor of lysine requirements. Lipid-free soft tissue can be obtained more quickly and predicted more accurately from carcass or live animal measurements.     

Ractopamine treatment biases in the prediction of pork carcass composition

Carcass and live measurements of 45 barrows were used to evaluate the magnitude of ractopamine (RAC) treatment prediction biases for measures of carcass composition. Barrows (body weight = 69.6 kg) were allotted by weight to three dietary treatments and fed to an average body weight of 114 kg. Treatments were: 1) 16% crude protein, 0.82% lysine control diet (CON); 2) control diet + 20 ppm RAC (RAC16); 3) a phase feeding sequence with 20 ppm RAC (RAC-P) consisting of 18% crude protein (1.08% lysine) during wk 1 and 4, 20% crude protein (1.22% lysine) during wk 2 and 3, 16% crude protein (0.94% lysine) during wk 6, and 16% crude protein (0.82% lysine) during wk 6. The four lean cuts from the right side of the carcasses (n = 15/treatment) were dissected into lean and fat tissue. The other cut soft tissue was collected from the jowl, ribs, and belly. Proximate analyses were completed on these three tissue pools and a sample of fat tissue from the other cut soft tissue. Prediction equations were developed for each of five measures of carcass composition: fat-free lean, lipid-free soft tissue, dissected lean in the four lean cuts, total carcass fat tissue, and soft-tissue lipid mass. Ractopamine treatment biases were found for equations in which midline backfat, ribbed carcass, and live ultrasonic measures were used as single technology sets of measurements. Prediction equations from live or carcass measurements underpredicted the lean mass of the RAC-P pigs and underpredicted the lean mass of the CON pigs. Only 20 to 50% of the true difference in fat-free lean mass or lipid-free soft-tissue mass between the control pigs and pigs fed RAC was predicted from equations including standard carcass measurements. The soft-tissue lipid and total carcass fat mass of RAC-P pigs was overpredicted from the carcass and live ultrasound measurements. Prediction equations including standard carcass measurements with dissected ham lean alone or with dissected loin lean reduced the residual standard deviation and magnitude of biases for the three measures of carcass leanmass. Prediction equations including the percentage of lipid of the other cut soft tissue improved residual standard deviation and reduced the magnitude of biases for total carcass fat mass and soft-tissue lipid. Prediction equations for easily obtained carcass or live ultrasound measures will only partially predict the true effect of RAC to increase carcass leanness. Accurate prediction of the carcass composition of RAC-fed pigs requires some partial dissection, chemical analysis, or alternative technologies.     

Genetic parameters for carcass traits and their live animal indicators in Simmental cattle

The objective of this study was to estimate parameters required for genetic evaluation of Simmental carcass merit using carcass and live animal data. Carcass weight, fat thickness, longissimus muscle area, and marbling score were available from 5,750 steers and 1,504 heifers sired by Simmental bulls. Additionally, yearling ultrasound measurements of fat thickness, longissimus muscle area, and estimated percentage of intramuscular fat were available on Simmental bulls (n = 3,409) and heifers (n = 1,503). An extended pedigree was used to construct the relationship matrix (n = 23,968) linking bulls and heifers with ultrasound data to steers and heifers with carcass data. All data were obtained from the American Simmental Association. No animal had both ultrasound and carcass data. Using an animal model and treating corresponding ultrasound and carcass traits separately, genetic parameters were estimated using restricted maximum likelihood. Heritability estimates for carcass traits were 0.48 +/- 0.06, 0.35 +/- 0.05, 0.46 +/- 0.05, and 0.54 +/- 0.05 for carcass weight, fat thickness, longissimus muscle area, and marbling score, respectively. Heritability estimates for bull (heifer) ultrasound traits were 0.53 +/- 0.07 (0.69 +/- 0.09), 0.37 +/- 0.06 (0.51 +/- 0.09), and 0.47 +/- 0.06 (0.52 +/- 0.09) for fat thickness, longissimus muscle area, and intramuscular fat percentage, respectively. Heritability of weight at scan was 0.47 +/- 0.05. Using a bivariate weight model including scan weight of bulls and heifers with carcass weight of slaughter animals, a genetic correlation of 0.77 +/- 0.10 was obtained. Models for fat thickness, longissimus muscle area, and marbling score were each trivariate, including ultrasound measurements on yearling bulls and heifers, and corresponding carcass traits of slaughter animals. Genetic correlations of carcass fat thickness with bull and heifer ultrasound fat were 0.79 +/- 0.13 and 0.83 +/- 0.12, respectively. Genetic correlations of carcass longissimus muscle area with bull and heifer ultrasound longissimus muscle area were 0.80 +/- 0.11 and 0.54 +/- 0.12, respectively. Genetic correlations of carcass marbling score with bull and heifer ultrasound intramuscular fat percentage were 0.74 +/- 0.11 and 0.69 +/- 0.13, respectively. These results provide the parameter estimates necessary for genetic evaluation of Simmental carcass merit using both data from steer and heifer carcasses, and their ultrasound indicators on yearling bulls and heifers.