Genetic parameters for ultrasound and carcass measures of yield and quality among replacement and slaughter beef cattle.

Real time ultrasound (RTU) measures of longissimus muscle area and fat depth were taken at 12 and 14 mo of age on composite bulls (n = 404) and heifers (n = 514). Carcass longissimus muscle area and fat depth, hot carcass weight, estimated percentage lean yield, marbling score, Warner-Bratzler shear force, and 7-rib dissectable seam fat and lean percentages were measured on steers (n = 235). Additive genetic variances for longissimus muscle area were 76 and 77% larger in bulls at 12 and 14 mo than the corresponding estimates for heifers. Heritability estimates for longissimus muscle area were 0.61 and 0.52 in bulls and 0.49 and 0.47 in heifers at 12 and 14 mo, respectively. The genetic correlations of longissimus muscle area of bulls vs heifers were 0.61 and 0.84 at 12 and 14 mo, respectively. Genetic correlations of longissimus muscle area measured in steer carcasses were 0.71 and 0.67 with the longissimus muscle areas in bulls and heifers at 12 mo and 0.73 and 0.79 at 14 mo. Heritability estimates for fat depth were 0.50 and 0.35 in bulls and 0.44 and 0.49 in heifers at 12 and 14 mo, respectively. The genetic correlation of fat depth in bulls vs heifers at 12 mo was 0.65 and was 0.49 at 14 mo. Genetic correlations of fat depth measured in bulls at 12 and 14 mo with fat depth measured in steers at slaughter were 0.23 and 0.21, and the corresponding correlations of between heifers and steers were 0.66 and 0.86, respectively. Live weights at 12 and 14 mo were genetically equivalent (r(g) = 0.98). Genetic correlations between live weights of bulls and heifers with hot carcass weight of the steers were also high (r(g) > 0.80). Longissimus muscle area measured using RTU was positively correlated with carcass measures of longissimus muscle area, estimated percentage lean yield, and percentage lean in a 7-rib section from steers. Measures of backfat obtained using RTU were positively correlated with fat depth and dissectable seam fat from the 7-rib section of steer carcasses. Genetic correlations between measures of backfat obtained using RTU and marbling were negative but low. These results indicate that longissimus muscle area and backfat may be under sufficiently different genetic control in bulls vs heifers to warrant being treated as separate traits in genetic evaluation models. Further, traits measured using RTU in potential replacement bulls and heifers at 12 and 14 mo of age may be considered different from the corresponding carcass traits of steers.     

Predicting carcass composition of beef cattle using ultrasound technology.

We evaluated 20 slaughtered cattle with ultrasound before hide removal to predict fat thickness and ribeye area at the 12th rib for possible use in carcass composition prediction. Carcasses were fabricated into boneless subprimals that were trimmed progressively from 2.54 to 1.27 to .64 cm maximum fat trim levels. Stepwise regression was used to indicate the relative importance of variables in a model designed to estimate the percentage of boneless subprimals from the carcass at different external fat trim levels. Variables included those obtained on the slaughter floor (ultrasound fat thickness and ribeye area; estimated percentage of kidney, pelvic, and heart [KPH] fat; and warm carcass weight) and those obtained from carcasses following 24 h in the chill cooler (actual fat thickness, actual ribeye area, estimated percentage of KPH fat, warm carcass weight, and marbling score). At all different subprimal trim levels, percentage KPH was the first variable to enter the model. In the models using measures taken on the slaughter floor, ultrasound fat thickness was the only other variable to enter the model. Ultrasound fat thickness increased R2 and decreased residual standard deviation (RSD) in models predicting subprimals at 2.54-cm maximum fat trim; however, at 1.27- and .64-cm trim levels, R2 and RSD increased. Models using the same two variables (except actual fat instead of ultrasound) in the cooler were similar to those using data from the slaughter floor. However, as more cooler measurement variables entered the models, R2 increased and RSD decreased, explaining a greater amount of the variation in the equation. Ultrasonic evaluation on the slaughter floor may be of limited application compared with the greater accuracy found in chilled carcass assessment.     

Genetic evaluation of beef carcass data using different endpoint adjustments

Carcass data from 6,795 Simmental-sired animals born from 1992 to 2001 were used to determine whether adjustment to a constant age, back-fat, HCW, or marbling score would result in differences in heritability of the carcass traits and, correspondingly, if EPD calculated using those variance components and adjustments would result in sire reranking. The endpoints were age (EPA), backfat (EPF), HCW (EPC), or marbling (EPM). The traits analyzed were 12th-rib backfat (FAT), HCW, marbling (MRB), LM area (LMA), and percentage retail cuts (PRC). The data were analyzed using an animal model, where contemporary group was included as a fixed effect and was composed of slaughter date, sex, and herd. Random effects included in the model were direct genetic and residual. Estimates of heritability ranged from 0.12 to 0.14, 0.32 to 0.34, and 0.26 to 0.27 for FAT, HCW, and LMA, respectively, for the corresponding endpoints. Heritability for MRB was estimated to be 0.27 at all endpoints. For PRC, estimates of heritability were more variable, with estimates of 0.23 +/- 0.05, 0.32 +/- 0.05, 0.21 +/- 0.05, and 0.20 +/- 0.04 for EPA, EPF, EPC, and EPM, respectively. However, because the EPF and EPC adjustments adjust for a component trait of PRC (FAT and HCW, respectively), they may be altering the trait to one different from PRC. Spearman rank correlations between EPD within a trait using EPA compared with the other endpoints were >0.90 (P < 0.01) for FAT, HCW, MRB, and LMA. For PRC, Spearman rank correlations with EPA EPD were 0.73 (P < 0.01), 0.93 (P < 0.01), and 0.95 (P < 0.01) for EPF, EPC, and EPM, respectively. For most traits and endpoints, there was little reranking among sires when alternative endpoints were used. However, adjusting PRC to EPF appears to result in a greater heritability and substantial re-ranking of sires, potentially due to the adjustment changing the trait to one other than PRC.     

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.     

Whole-genome QTL scan for ultrasound and carcass merit traits in beef cattle using Bayesian shrinkage method

Fine mapping of quantitative trait loci (QTL) for 16 ultrasound measurements and carcass merit traits that were collected from 418 hybrid steers was conducted using 1207 SNP markers covering the entire genome. These SNP markers were evaluated using a Bayesian shrinkage estimation method and the empirical critical significant thresholds (α = 0.05 and α = 0.01) were determined by permutation based on 3500 permuted datasets for each trait to control the genome-wide type I error rates. The analyses identified a total of 105 QTLs (p < 0.05) for seven ultrasound measure traits including ultrasound backfat, ultrasound marbling and ultrasound ribeye area and 113 QTLs for seven carcass merit traits of carcass weight, grade fat, average backfat, ribeye area, lean meat yield, marbling and yield grade. Proportion of phenotypic variance accounted for by a single QTL ranged from 0.06% for mean ultrasound backfat to 4.83% for carcass marbling (CMAR) score, while proportion of the phenotypic variance accounted for by all significant (p < 0.05) QTL identified for a single trait ranged from 4.54% for carcass weight to 23.87% for CMAR.     

Genetic and phenotypic relationships of feed intake and measures of efficiency with growth and carcass merit of beef cattle

Feed intake and efficiency of growth are economically important traits of beef cattle. This study determined the relationships of daily DMI, feed:gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F) and therefore increases as the efficiency of gain decreases and vice versa, residual feed intake (RFI), and partial efficiency of growth (efficiency of ADG, PEG) with growth and carcass merit of beef cattle. Residual feed intake was calculated from phenotypic regression (RFIp) or genetic regression (RFIg) of ADG and metabolic BW on DMI. An F1 half-sib pedigree file containing 28 sires, 321 dams, and 464 progeny produced from crosses between Alberta Hybrid cows and Angus, Charolais, or Alberta Hybrid bulls was used. Families averaged 20 progeny per sire (range = 3 to 56). Performance, ultrasound, and DMI data was available on all progeny, of which 381 had carcass data. Phenotypic and genetic parameters were obtained using SAS and ASREML software, respectively. Differences in RFIp and RFIg, respectively, between the most and least efficient steers (i.e., steers with the lowest PEG) were 5.59 and 6.84 kg of DM/d. Heritabilities for DMI, F:G, PEG, RFIp, and RFIg were 0.54 +/- 0.15, 0.41 +/- 0.15, 0.56 +/- 0.16, 0.21 +/- 0.12, and 0.42 +/- 0.15, respectively. The genetic (r = 0.92) and phenotypic (r = 0.97) correlations between RFIp and RFIg indicated that the 2 indices are very similar. Both indices of RFI were favorably correlated phenotypically (P < 0.001) and genetically with DMI, F:G, and PEG. Residual feed intake was tendentiously genetically correlated with ADG (r = 0.46 +/- 0.45) and metabolic BW (r = 0.27 +/- 0.33), albeit with high SE. Genetically, RFIg was independent of ADG and BW but showed a phenotypic correlation with ADG (r = -0.21; P < 0.05). Daily DMI was correlated genetically (r = 0.28) and phenotypically (r = 0.30) with F:G. Both DMI and F:G were strongly correlated with ADG (r > 0.50), but only DMI had strong genetic (r = 0.87 +/- 0.10) and phenotypic (r = 0.65) correlations with metabolic BW. Generally, the phenotypic and genetic correlations of RFI with carcass merit were not different from zero, except genetic correlations of RFI with ultrasound and carcass LM area and carcass lean yield and phenotypic correlations of RFI with backfat thickness (P < 0.01). Daily DMI had moderate to high phenotypic (P < 0.01) and genetic correlations with all the ultrasound and carcass traits. Depending on how RFI technology is applied, adjustment for body composition in addition to growth may be required to minimize the potential for correlated responses to selection in cattle.     

Accuracy of predicting weight and percentage of beef carcass retail product using ultrasound and live animal measures

Five hundred thirty-four steers were evaluated over a 2-yr period to develop and validate prediction equations for estimating carcass composition from live animal ultrasound measurements and to compare these equations with those developed from carcass measurements. Within 5 d before slaughter, steers were ultrasonically measured for 12th-rib fat thickness (UFAT), longissimus area (ULMA), rump fat thickness (URPFAT), and body wall thickness (UBDWALL). Carcasses were fabricated to determine weight (KGRPRD) and percentage (PRPRD) of boneless, totally trimmed retail product. Data from steers born in Year 1 (n = 282) were used to develop prediction equations using stepwise regression. Final models using live animal variables included live weight (FWT), UFAT, ULMA, and URPFAT for KGRPRD (R2 = 0.83) and UFAT, URPFAT, ULMA, FWT, and UBDWALL for PRPRD (R2 = 0.67). Equations developed from USDA yield grade variables resulted in R2 values of 0.87 and 0.68 for KGRPRD and PRPRD, respectively. When these equations were applied to steers born in Year 2 (n = 252), correlations between values predicted from live animal models and actual carcass values were 0.92 for KGRPRD, and ranged from 0.73 to 0.76 for PRPRD. Similar correlations were found for equations developed from carcass measures (r = 0.94 for KGRPRD and 0.81 for PRPRD). Both live animal and carcass equations overestimated (P < 0.01) actual KGRPRD and PRPRD. Regression of actual values on predicted values revealed a similar fit for equations developed from live animal and carcass measures. Results indicate that composition prediction equations developed from live animal and ultrasound measurements can be useful to estimate carcass composition.     

B-mode, real-time ultrasound for estimating carcass measures in live sheep: accuracy of ultrasound measures and their relationships with carcass yield and value

Accuracy and repeatability of live-animal ultrasound measures, and the relationships of these measures with subprimal yields and carcass value, were investigated using data from 172 wethers. Wethers were F(1) progeny from the mating of 4 terminal sire breeds to Rambouillet ewes and were finished in a feedlot to a mean BW of 62.9 kg (SD = 9.5 kg). Before transport to slaughter, LM area, LM depth, and backfat thickness were measured from transverse ultrasound images taken between the 12th and 13th ribs. After slaughter, these measures were taken on each carcass. Carcasses were fabricated into subprimal cuts, and weights were recorded. Ultrasound accuracy and repeatability were assessed using bias, SE of prediction, SE of repeatability, and simple correlations. Relationships among ultrasound and carcass measures, and between these measures and carcass yield and value, were evaluated using residual correlations and linear prediction models. Ultrasound bias approached 0 for LM area, and backfat thickness was overestimated by only 0.69 mm. The SE of prediction and r were 1.55 cm(2) and 0.75 for LM area, and 1.4 mm and 0.81 for backfat thickness, respectively. The SE of repeatability was 1.31 cm(2) and 0.75 mm for LM area and backfat thickness, respectively. At a standardized BW and backfat thickness, wethers with larger LM area and LM depth yielded larger and more valuable carcasses, and these relationships were detectable with ultrasound. For each SD increase in carcass LM area, dressing percentage increased 1.57 percentage points, gross carcass value increased US$5.12, and boxed carcass value increased US$6.84 (P < 0.001). For each SD increase in ultrasound LM area, dressing percentage increased 0.95 percentage points, gross carcass value increased US$3.15, and boxed carcass value increased US$3.86 (P < 0.001). When LM area effects were adjusted for carcass weight, the response in boxed carcass value attributed to disproportionate increases in high-value subprimal cut weights was small. Associations of dressing percentage and carcass value with ultrasound and carcass LM depth were significant (P < 0.01) but smaller than corresponding associations with LM area. These data indicate biological and economical incentives for increasing LM area in wethers, and live-animal ultrasound can provide reliable estimates of carcass measures. These results are applicable to terminal sire breeders and producers who market sheep using carcass-merit pricing systems.     

National cattle evaluation system for combined analysis of carcass characteristics and indicator traits recorded by using ultrasound in Angus cattle

The objectives were to 1) evaluate genetic relationships of sex-specific indicators of carcass merit obtained by using ultrasound with carcass traits of steers; 2) estimate genetic parameters needed to implement combined analyses of carcass and indicator traits to produce unified national cattle evaluations for LM area, subcutaneous fat depth (SQF), and marbling (MRB), with the ultimate goal of publishing only EPD for the carcass traits; and 3) compare resulting evaluations with previous ones. Four data sets were extracted from the records of the American Angus Association from 33,857 bulls, 33,737 heifers, and 1,805 steers that had measures of intramuscular fat content (IMF), LM area (uLMA), and SQF derived from interpretation of ultrasonic imagery, and BW recorded at the time of scanning. Also used were 38,296 records from steers with MRB, fat depth at the 12th to 13th rib interface (FD), carcass weight, and carcass LM area (cLMA) recorded on slaughter. (Co)variance components were estimated with ASREML by using the same models as used for national cattle evaluations by the American Angus Association. Heritability estimates for carcass measures were 0.45 +/- 0.03, 0.34 +/- 0.02, 0.40 +/- 0.02, and 0.33 +/- 0.02 for MRB, FD, carcass weight, and cLMA, respectively. Genetic correlations of carcass measures from steers with ultrasonic measures from bulls and heifers indicated sex-specific relationships for IMF (0.66 +/- 0.05 vs. 0.52 +/- 0.06) and uLMA (0.63 +/- 0.06 vs. 0.78 +/- 0.05), but not for BW at scanning (0.46 +/- 0.07 vs. 0.40 +/- 0.07) or SQF (0.53 +/- 0.06 vs. 0.55 +/- 0.06). For each trait, estimates of genetic correlations between bulls and heifers measured by using ultrasound were greater than 0.8. Prototype national cattle evaluations were conducted by using the estimated genetic parameters, resulting in some reranking of sires relative to previous analyses. Rank correlations of high-impact sires were 0.91 and 0.84 for the joint analysis of MRB and IMF with previous separate analyses of MRB and IMF, respectively. Corresponding results for FD and SQF were 0.90 and 0.90, and for cLMA and uLMA were 0.79 and 0.89. The unified national cattle evaluation for carcass traits using measurements from slaughtered animals and ultrasonic imagery of seed stock in a combined analysis appropriately weights information from these sources and provides breeders estimates of genetic merit consistent with traits in their breeding objectives on which to base selection decisions.     

Genetic evaluation of growth in a multibreed beef cattle population using random regression-linear spline models

The objective of this study was to examine the feasibility of using random regression-spline (RR-spline) models for fitting growth traits in a multibreed beef cattle population. To meet the objective, the results from the RR-spline model were compared with the widely used multitrait (MT) model when both were fit to a data set (1.8 million records and 1.1 million animals) provided by the American Gelbvieh Association. The effect of prior information on the EBV of sires was also investigated. In both RR-spline and MT models, the following effects were considered: individual direct and maternal additive genetic effects, contemporary group, age of the animal at measurement, direct and maternal heterosis, and direct and maternal additive genetic mean effect of the breed. Additionally, the RR-spline model included an individual direct permanent environmental effect. When both MT and RR-spline models were applied to a data set containing records for weaning weight (WWT) and yearling weight (YWT) within specified age ranges, the rankings of bulls' direct EBV (as measured via Pearson correlations) provided by both models were comparable, with slightly greater differences in the reranking of bulls observed for YWT evaluations (>or=0.99 for BWT and WWT and >or=0.98 for YWT); also, some bulls dropped from the top 100 list when these lists were compared across methods. For maternal effects, the estimated correlations were slightly smaller, particularly for YWT; again, some drops from the top 100 animals were observed. As in regular MT multibreed genetic evaluations, the heterosis effects and the additive genetic effects of the breed could not be estimated from field data, because there were not enough contemporary groups with the proper composition of purebred and crossbred animals; thus, prior information based on literature values had to be included. The inclusion of prior information had a negligible effect in the overall ranking for bulls with greater than 20 birth weight progeny records; however, the effect of prior information for breeds or groups poorly represented in the data was important. The Pearson correlations for direct and maternal WWT and YWT ranged from 0.95 to 0.98 when comparing evaluations of data sets for which the out-of-range age records were removed or retained. Random regression allows for avoiding the discarding of records that are outside the usual age ranges of measurement; thus, greater accuracies are achieved, and greater genetic progress could be expected.     

Morphological assessment of beef cattle according to carcass value

In this paper we present an assessment function devised for bulls of a beef breed according to the specific market requirements of their carcasses. The procedure is completely repeatable since it is based on the measurements in centimeters of only 3 lengths of live animals plus an estimation of the curvature of the round profile. To derive this assessment, we used Artificial Intelligence tools based on Support Vector Machines (SVM). They allowed us to learn the estimations of the experts of the Association of Breeders (ASEAVA) about the value of carcasses of the animals in the sense that the score returned by the assessment function (on a scale 0–100) is higher for bulls with more valuable carcasses. Additionally, we studied the growth of bulls in order to adjust the assessments to a constant age of 365 days.     

Comparison of real-time ultrasound and other live measures to carcass measures as predictors of beef cow energy stores.

Thirty-nine mature cows were divided into three condition groups on the basis of their subcutaneous fat thickness as determined by real-time ultrasound. A representative animal from each group was measured and slaughtered. The remaining cows with each group were stratified evenly into two groups with one group fed to gain weight and the other to lose weight. Several ultrasound and other live measures were taken every 4 wk and two animals per subgroup were randomly slaughtered. Carcass data were collected and one side of each carcass was boned, ground, mixed, and subsampled for fat and protein determination. Four regression equations were generated to predict percentage of fat (FAT), percentage of protein (PROT), total fat (TOTFAT), total protein (TOTPROT), total calories (CAL), CAL per live weight (CAL/WT), yield grade (YG), and marbling (MARB). The first equation used all live measures (SUB), the second equation used only objective live measures (OBJ), the third equation incorporated traditional live measures (EAS), and the fourth equation used only carcass data (CAR). Adjusted R-squares of the most appropriate equation using the SUB, OBJ, EAS, and CAR measurements were .82, .73, .82, and .82 for FAT; .82, .57, .61, and .66 for PROT; .89, .87, .86, and .85 for TOTFAT; .95, .95, .93, and .74 for TOTPROT; .93, .92, .91, and .90 for CAL; .83, .78, .83, and .82 for CAL/WT; .86, .86, .78, and .93 for YG; and .75, .70, .74, and .74 for MARB, respectively. It seems that condition score or ultrasound with other objective live measures is as accurate in predicting cow composition as carcass measures.     

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.     

Genetic and phenotypic relationships of feeding behavior and temperament with performance, feed efficiency, ultrasound, and carcass merit of beef cattle

Feeding behavior and temperament may be useful in genetic evaluations either as indicator traits for other economically relevant traits or because the behavior traits may have a direct economic value. We determined the variation in feeding behavior and temperament of beef cattle sired by Angus, Charolais, or Hybrid bulls and evaluated their associations with performance, efficiency, and carcass merit. The behavior traits were daily feeding duration, feeding head down (HD) time, feeding frequency (FF), and flight speed (FS, as a measure of temperament). A pedigree file of 813 animals forming 28 paternal half-sib families with about 20 progeny per sire was used. Performance, feeding behavior, and efficiency records were available on 464 animals of which 381 and 302 had records on carcass merit and flight speed, respectively. Large SE reflect the number of animals used. Direct heritability estimates were 0.28 +/- 0.12 for feeding duration, 0.33 +/- 0.12 for HD, 0.38 +/- 0.13 for FF, and 0.49 +/- 0.18 for FS. Feeding duration had a weak positive genetic (r(g)) correlation with HD (r(g) = 0.25 +/- 0.32) and FS (r(g) = 0.42 +/- 0.26) but a moderate negative genetic correlation with FF (r(g) = -0.40 +/- 0.30). Feeding duration had positive phenotypic (r(p)) and genetic correlations with DMI (r(p) = 0.27; r(g) = 0.56 +/- 0.20) and residual feed intake (RFI; r(p) = 0.49; r(g) = 0.57 +/- 0.28) but was unrelated phenotypically with feed conversion ratio [FCR; which is the reciprocal of the efficiency of growth (G:F)]. Feeding duration was negatively correlated with FCR (r(g) = -0.25 +/- 0.29). Feeding frequency had a moderate to high negative genetic correlation with DMI (r(g) = -0.74 +/- 0.15), FCR (r(g) = -0.52 +/- 0.21), and RFI (r(g) = -0.77 +/- 0.21). Flight speed was negatively correlated phenotypically with DMI (r(p) = -0.35) but was unrelated phenotypically with FCR or RFI. On the other hand, FS had a weak negative genetic correlation with DMI (r(g) = -0.11 +/- 0.26), a moderate genetic correlation with FCR (r(g) = 0.40 +/- 0.26), and a negative genetic correlation with RFI (r(g) = -0.59 +/- 0.45). The results indicate that behavior traits may contribute to the variation in the efficiency of growth of beef cattle, and there are potential correlated responses to selection to improve efficiency. Feeding behavior and temperament may need to be included in the definition of beef cattle breeding goals, and approaches such as the culling of unmanageable cattle and the introduction of correct handling facilities or early life provision of appropriate experiences to improve handling will be useful.     

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.     

Leptin as a predictor of carcass composition in beef cattle

Our objective was to determine if serum concentrations of leptin could be used to predict carcass composition and merit in feedlot finished cattle. Two different groups of crossbred Bos taurus steers and heifers were managed under feedlot conditions near Miles City, MT. The first group consisted of 88 1/2 Red Angus, 1/4 Charolais, and 1/4 Tarentaise composite gene combination steers (CGC) harvested at the ConAgra processing facility in Greeley, CO. The second group (Lean Beef Project; LB) consisted of 91 F2 steers and heifers born to Limousin, Hereford, or Piedmontese by CGC F1 cows crossed to F1 bulls of similar breed composition and harvested at a local processing facility in Miles City, MT. Blood samples were collected approximately 24 h before harvest (CGC) or approximately 3 d before and at harvest (LB). No differences in serum concentrations of leptin were detected (P > 0.10) between Hereford, Limousin, or Piedmontese F2 calves nor between LB steers and heifers. Positive correlations (P < 0.01) existed between serum leptin and marbling score (r = 0.35 and 0.50), fat depth measured between the 12th and 13th rib (r = 0.34 and 0.46), kidney, pelvic, and heart fat (KPH) (r = 0.42 and 0.46), and quality grade (r = 0.36 and 0.49) in CGC and LB cattle, respectively. Serum leptin was also positively correlated with calculated yield grade for CGC steers (r = 0. 19; P = 0. 10) and LB cattle (r = 0.52; P < 0.01). Longissimus area was not correlated with serum leptin in CGC steers (r = 0.12; P > 0.10). However, a negative correlation existed between longissimus area and serum leptin in the LB cattle (r = -0.45; P < 0.01). Serum concentrations of leptin were significantly associated with carcass composition (marbling, back fat depth, and KPH fat) and quality grade in both groups of cattle studied and may provide an additional indicator of fat content in feedlot cattle.     

Genetic evaluation of carcass traits in Simmental-sired cattle at different slaughter end points

Our objectives were to estimate genetic parameters for carcass traits and evaluate the influence of slaughter end point on estimated breeding values (BV). Data provided by the American Simmental Association were divided into three sets: 1) 9,604 records of hot carcass weight (CW) and percentage retail cuts (PRC), 2) 6,429 records of CW, PRC, and marbling score (MS), and 3) 1,780 records of CW, PRC, MS, fat thickness (FT), and longissimus muscle area (LMA). Weaning weights (WW) from animals with carcass data and from their weaning contemporaries were used. Data were analyzed with a multiple-trait animal model and REML procedures to estimate genetic parameters and BV on an age-, CW-, MS-, or FT-constant basis. The model for carcass traits included fixed contemporary group and covariates for breed, heterozygosity, and slaughter end point and random additive direct genetic and residual effects. Weaning weight was preadjusted for founder effects, direct and maternal heterosis, age of dam, and age of calf. The model for WW included fixed contemporary group and random additive direct genetic, maternal genetic, maternal permanent environment, and residual effects. Heritabilities from data set 1 were 0.34 for CW and 0.25 for PRC on an age-constant basis and 0.25 for PRC on a CW end point. Heritabilities for data set 2 were 0.35, 0.24, and 0.36 for CW, PRC, and MS, respectively, on an age-constant basis. Data set 2 heritabilities were 0.25 for PRC and 0.34 for MS on a CW-constant basis and 0.33 for CW and 0.25 for PRC at a constant MS end point. Heritabilities on an age-constant basis for data set 3 were as follows: CW, 0.32; PRC, 0.09; MS, 0.12; FT, 0.10; and LMA, 0.26. Heritability estimates for data set 3 on a CW-, MS-, and FT-constant basis were similar to those on an age-constant basis. Heritabilities were 0.12 for PRC, 0.12 for MS, 0.14 for FT, and 0.22 for LMA on a CW-constant basis; 0.30 for CW, 0.09 for PRC, 0.10 for FT, and 0.28 for LMA at a constant MS end point; and 0.33, 0.17, 0.13, and 0.29 for CW, PRC, MS, LMA on a FT-constant basis. Genetic correlations among traits varied across groups and end points but suggested that it should be possible to select for improved lean yield without sacrificing quality grade. Correlations were calculated among BV computed at different end points. Adjustment to various end points resulted in some changes in BV and reranking of sires, especially for PRC; however, the number of records available had a larger influence than slaughter end point.