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ANIMAL PRODUCTION |
* USDA, ARS, US Sheep Experiment Station, Dubois, ID 83423;
and
Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg 24061; and
Department of Animal Sciences, The Ohio State University, Columbus 43210
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Abstract |
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 Top Abstract INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Key Words: backfat thickness • carcass yield • longissimus muscle area • sheep • ultrasound
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INTRODUCTION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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). Throughout the marketing chain, lamb buyers (i.e., producers, packers, retailers, and consumers) demand improvements to production efficiency, product yield, carcass composition, and meat quality (TAMRC, 1991; Ward et al., 1995; LeValley et al., 2008). For the industry to remain competitive, it must produce carcasses that meet, or exceed, these buyer demands (Beermann et al., 1995). Ultrasound can afford breeders, producers, and researchers the ability to estimate carcass compositional traits in vivo, and thus contribute knowledge to breeding, management, and marketing decisions.
Certain characteristics of sheep, such as wool, mobile skin, soft fat, and kidney-pelvic fat, may make image acquisition difficult or limit the utility of ultrasound measures (Purchas and Beach, 1981; Edwards et al., 1989; Houghton and Turlington, 1992). However, low relative cost and ease of portability make ultrasound a practical option for future in vivo estimation of carcass composition. Research to validate ultrasound as a predictive tool, using current ultrasound technologies and in diverse populations, may expedite its increased and efficacious use in the sheep industry. Thus, our objectives were to 1) assess the accuracy and repeatability of ultrasound estimates of LM area (LMA), LM depth (LMD), and backfat thickness (BF) at the 12th/13th rib location using statistics established for beef and swine certification programs; 2) describe relationships among and between measures of fatness and muscling and carcass and subprimal yields; and 3) evaluate the effects of increasing LMA and LMD on carcass and subprimal yields and carcass value.
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MATERIALS AND METHODS |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Animals, Experimental Procedures, and Data
This study included 172 F1 wether lambs that were produced as part of a terminal sire breed evaluation. Briefly, Columbia, USMARC-Composite (Leymaster, 1991), Suffolk, and Texel purebred rams (n = 5 to 8 per breed; 29 rams total), sampled from US flocks to represent current US genetics, were single-sire mated to Rambouillet ewes (n = 290). Ewes lambed in March or April 2006, and ram lambs were castrated within 24 h after parturition. Ewes and lambs were herded on sagebrush steppe range beginning in late April and subalpine range beginning in early July. Wethers were weaned at 130 d of age (SD = 5.5 d) at a BW of 39.1 kg (SD = 5.5 kg), transported to a feedlot at the US Sheep Experiment Station headquarters, and provided ad libitum access to a growing-finishing diet. The final finishing diet consisted of 79.6% whole corn, 18.4% supplement pellet, and 2.0% concentrated separator by-product (as-fed basis). Wethers were adapted to the final diet over 6 phases that were used to gradually increase the level of corn while decreasing the level of roughage (i.e., alfalfa pellet). Wethers were assigned randomly within sire to 1 of 3 slaughter groups at targeted mean off-test BW of 54.4, 61.2, and 68.0 kg. However, constraints were imposed on assignments to achieve equal sire representation among slaughter groups, and full-sib wethers were not assigned to the same slaughter group. The number of wethers represented in each slaughter group was 60, 58, and 54, respectively, and the actual mean off-test BW for all wethers was 62.9 kg (SD = 9.5 kg). The mean off-test age for all wethers was 220 d (SD = 23.3 d).
On the off-test date for each slaughter group, a single, trained technician captured, digitized, and saved to a laptop 2 ultrasound images per wether from the left side between the 12th and 13th ribs. Each wether in the slaughter group passed through the scanning chute twice. A single ultrasound image was acquired per pass, and wethers were mingled in a holding pen between passes. The ultrasound device was an Aloka SSD-500V (Corometrics Medical Systems, Wallingford, CT) with a 3.5-MHz, 12.5-cm linear array transducer and standoff (Superflab; Mick Radio-Nuclear Instruments Inc., Mount Vernon, NY). Wool was clipped from the scan site to an approximate length of 3.2 mm using a 6.35-cm, 10-tooth comb (Oster Professional Products, McMinnville, TN), and warm vegetable oil was used as a conductive medium. Settings for the ultrasound device were 90 for overall gain, –25 for near gain, 2.1 for far gain, and focal points F1 and F2. The same technician measured the ultrasound images for LMA, LMD, and BF at the middle of the LM using ImageJ software (v.1.36b, NIH, 2006) after calibration for known pixel dimension and aspect ratio (Figure 1). Depth of LM was recorded as the maximum depth perpendicular to the long axis of the cross section (i.e., LMD measure was not constrained to the C site, which is 40 to 45 mm from the dorsal midline).
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Carcasses were fabricated according to style A of Institutional Meat Purchase Specifications (IMPS; USDA, 1996), and weights of neck, square-cut shoulder (IMPS No. 207), foreshank (IMPS No. 210), breast (IMPS No. 209), rack (IMPS No. 204), loin (IMPS No. 232), and leg (IMPS No. 233A) were recorded. The weight of the residual carcass, consisting of flanks, trotters, gambrel cords, and cutting loss, was calculated as the chilled carcass weight minus the sum of the subprimal cut weights. The weight of the offal, consisting of pelt, digestive tract and digesta, organs, head, and feet, was calculated as BW at slaughter minus the sum of the chilled carcass and kidney-pelvic fat weights. Dressing percentage was calculated as the ratio of chilled carcass weight to BW at slaughter. Gross carcass value was calculated as chilled carcass weight x gross carcass price (Table 1). Boxed carcass value was calculated as the sum, over all cuts, of cut weights x their respective price (Table 1). Pricing data were obtained from the USDA Daily National Lamb Market Summary reported October 1, 2007 (USDA, 2007).
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contains summary statistics for BW, ultrasound and carcass measures of fatness and muscling, and subprimal and carcass yields. Summary statistics are presented only for wethers with a full complement of carcass data; 4 wethers had at least 1 missing data point and were excluded. Data for BW at slaughter, and thus data derived from this measure, were inaccurate for the second slaughter group (i.e., a plank of the scale platform was inadvertently dislodged, and the platform did not always receive the entire load of the animal) and were excluded from all analyses.
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Ultrasound Accuracy and Repeatability.
Ultrasound estimates of BF, LMA, and LMD were evaluated using statistics established for beef and swine certification programs (BIF, 2002; Bates and Christians, 1994) and simple correlations. Certification statistics included SE of prediction, SE of repeatability, and technician bias and were calculated as
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where scanjk is the kth ultrasound estimate on the jth wether; carcassj is the carcass measurement on the jth wether; and n is the number of wethers scanned twice. Data from all 172 wethers were used for this evaluation.
Residual Correlations. Relationships among measures of fatness and muscling, and between measures of fatness and muscling and subprimal and carcass yields, were described using residual correlations after adjustment for 1) breed of sire effects; and 2) breed of sire effects and off-test BW. Residual correlations were calculated using data from 168 wethers. However, residual correlations involving a trait derived from BW at slaughter were calculated using data from only 111 wethers.
Effects of LMA and LMD on Carcass Yield. Weights of subprimal cuts, kidney-pelvic fat weight, offal weight, dressing percentage, and carcass value were described using the linear models
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to estimate effects of LMA and LMD on carcass yield and value after adjustment for off-test BW. Each model was evaluated twice, once using carcass measures of BF and LMA or LMD, and once using ultrasound estimates of BF and LMA or LMD.
To estimate effects of LMA and LMD on subprimal yields and carcass value after adjustment for carcass weight, weights of subprimal cuts and boxed carcass value were described using the linear models
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These models were also evaluated using ultrasound and carcass measures of BF and LMA or LMD.
Covariates (i.e., off-test BW, chilled carcass weight, BF, LMA, and LMD) were expressed as deviations from the covariate trait mean; thus, reported intercept values (µ) are the predicted response at the mean of each covariate. All terms remained in the models regardless of significance. All analyses were performed using R statistical software (v.2.4.0; R Development Core Team, 2006).
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RESULTS |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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illustrate the relationships between ultrasound and carcass measures of BF, LMA, and LMD. Technician bias, SE of prediction, SE of repeatability, and simple correlation with the corresponding carcass measure are also given for each ultrasound measure in Figure 2.
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contains residual correlations among measures of fatness and muscling after adjustment for breed of sire effects and off-test BW. All residual correlations, after adjustment for breed of sire effects, were positive (0.30 
r 0.89) and different from 0 (P < 0.01), and all were within ± 0.12 of unadjusted phenotypic correlations (data not shown). Relationships between BF and muscling (i.e., LMA or LMD) were consistently greater for ultrasound measures than they were for carcass measures. Residual correlations, after adjustment for off-test BW, were smaller than correlations obtained after adjustment for only breed of sire effects. Within a method (i.e., ultrasound or carcass), relationships between LMA and LMD were greater than relationships of the same measure across methods (e.g., rultrasound LMA, ultrasound LMD > rultrasound LMA, carcass LMA). Whereas correlations between BF and LMA or LMD tended to be positive for ultrasound (P < 0.10), these traits were, or tended to be, negatively correlated when measured on the carcass (P < 0.01 and P < 0.10, respectively).
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contains residual correlations between measures of fatness and muscling and subprimal and carcass yields after adjustment for breed of sire effects. All residual correlations, after adjusting for breed of sire effects, were positive (0.23 r 0.82) and different from 0 (P < 0.01), and all were within ± 0.12 of unadjusted phenotypic correlations (data not shown). Carcass LMA, rather than carcass LMD, had greater correlation with all carcass traits except neck weight. This pattern was not apparent when LMA and LMD were measured using ultrasound. Carcass LMA, rather than ultrasound LMA, had greater correlation with all carcass traits except residual carcass weight. Conversely, ultrasound BF, compared with carcass BF, had greater correlation with all carcass traits. Across methods and measures, correlations with subprimal yields were generally greatest for the high-value subprimal cuts (i.e., rack, loin, and leg weights).
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contains residual correlations between measures of fatness and muscling and subprimal and carcass yields after adjustment for off-test BW and breed of sire effects. Adjustment for off-test BW greatly reduced trait correlations, and some became negative, compared with the correlations reported in Table 4
. Residual correlations between LMA and weights of chilled carcass, rack, loin, and leg were moderate (0.22 r 0.47) and different from 0 (P < 0.01) for ultrasound and carcass measures. These traits generally had smaller correlations with LMD than with LMA for ultrasound and carcass measures. Unfavorable relationships, although weak, were detected between kidney-pelvic fat weight and carcass LMA or LMD (r 0.17; P < 0.10), but these relationships were not apparent when LMA and LMD were measured with ultrasound. Kidney-pelvic fat weight had the largest correlation with bodywall thickness, and it was not correlated with ultrasound or carcass BF. Ultrasound BF was positively correlated with rack and loin weights (r = 0.17 and 0.19, respectively; P < 0.05), but not with leg or chilled carcass weights (r = –0.11 and 0.11, respectively; P > 0.10).
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summarizes prediction equations that used off-test BW and ultrasound measures of BF and LMA to estimate weights of subprimal cuts, kidney-fat, and offal. The LMA partial regression coefficients were positive for rack, loin, and leg weights (P < 0.01), and not different from 0 for all other subprimal cut and kidney-pelvic fat weights (P > 0.10). Because these LMA effects were adjusted for off-test BW, the LMA partial regression coefficient for offal weight was necessarily negative (b = –0.1593; P < 0.10). Models that used carcass measures of BF and LMA and models that used LMD instead of LMA (data not shown) were very similar to the models reported in Table 6; residual SE were identical to 2 significant digits and R2 values were within 0.01 for all traits except rack, loin, and leg weights. Carcass measures of BF and LMA or LMD, compared with ultrasound measures, increased model R2 values by an average of 0.02, 0.005, and 0.015, and decreased residual SE by an average of 0.015, 0.005, and 0.04 kg, for rack, loin, and leg weights, respectively. Ultrasound or carcass measures of LMA, compared with LMD, increased model R2 values by an average of 0.01, 0.005, and 0.005, and decreased residual SE by an average of 0.005, 0.005, and 0.011 kg, for rack, loin, and leg weights, respectively.
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summarizes prediction equations that used off-test BW, BF, and LMA or LMD to estimate dressing percentage and carcass value. Consistency in residual SE and R2 among sets of predictors was less for these traits, compared with traits in Table 6; thus results of all 4 prediction models are shown. Partial regression coefficient estimates of LMA and LMD were always positive, and different from 0 (P < 0.01), for dressing percentage and carcass value. The data plots in Figure 3 illustrate the relationships between ultrasound measures of LMA and dressing percentage, gross carcass value, and boxed carcass value. Partial regression coefficient estimates of BF were also positive for dressing percentage and carcass value, but were only significant (P < 0.10) when measured on the carcass. Residual SE for dressing percentage and carcass value were consistently smaller for models using carcass measures, compared with ultrasound, and consistently smaller for models using LMA, compared with LMD. After accounting for the effects of BF and LMA or LMD, off-test BW had no effect on dressing percentage (P > 0.10).
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and 7, and the importance of these effects on subprimal yields and carcass value was consistent among all sets of predictors. Given our experimental design, we believe it is important to model breed of sire effects in the current analyses; however, results pertaining to these effects are beyond the scope of this report and will not be discussed in detail. The interaction between breed of sire and LMA and LMD was tested for ultrasound and carcass measures, for all dependent variables, and was significant (P 0.05) only for weight of foreshank (data not shown). For all other traits, LMA and LMD partial regression coefficient estimates were not different (P > 0.13) among sire breeds (data not shown). Because the slopes were generally similar across sire breeds, and because we did not intend to make inferences to sire breeds, the interaction term was not included in any of the final models.
Table 8 summarizes prediction equations that used carcass weight and ultrasound measures of BF and LMA to estimate subprimal cut weights and carcass value. Adjustment of LMA effects for carcass weight and BF allowed for a more direct examination of LMA effects on subprimal yields because the sum of LMA partial regression coefficients, across all subprimal cuts, was forced to 0. The signs of the partial regression coefficients indicate that, when LMA increased, a larger proportion of the carcass weight was attributed to rack, loin, and leg weight, and at the expense of neck, shoulder, foreshank, and breast weight. However, except for foreshank weight, the LMA partial regression coefficients were not different from 0 (P > 0.10) for subprimal cut weights or boxed carcass value. When carcass measures were used in the model, LMA partial regression coefficients were positive and different from 0 (P < 0.01) for rack and leg weights (data not shown). Untrimmed rack and loin weights increased with increasing ultrasound BF (P < 0.10), but leg weight decreased (P < 0.001), and there was no effect of ultrasound BF on boxed carcass value (P > 0.10).
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DISCUSSION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Our data indicate that ultrasound can be used to accurately predict LMA, LMD, and BF in sheep, and our predictions were repeatable. Technician bias for LMA approached 0, and was within 1.2 and 0.7 mm for LMD and BF, respectively. After accounting for technician bias, the SE of prediction, assuming normally distributed errors, indicates that 67% of ultrasound estimates of LMA, LMD, and BF were within 1.55 cm2, 2.6 mm, and 1.4 mm, respectively, of the actual carcass measure. Residuals were tested for normality using a Shapiro-Wilk test, and the assumption of normality was accepted for LMA and LMD (P > 0.19), but rejected for BF (P = 0.038; data not shown). The SE of repeatability indicates that 67% of repeat ultrasound estimates were within 1.31 cm2, 2.0 mm, and 0.75 mm for LMA, LMD, and BF, respectively, of the initial ultrasound estimate. The assumption of normality for between-scans residuals, tested using a Shapiro-Wilk test, was accepted for LMA and LMD (P > 0.57), but rejected for BF (P = 0.018; data not shown). We examined the BF accuracy and repeatability residuals using quantile-quantile plots (data not shown), and departures from normality were due to very few (i.e., 5) observations with extreme errors (i.e., deviations 
0.34 and 0.15 cm for accuracy and repeatability, respectively). These few extreme observations caused the distributions of residuals to be leptokurtic; therefore, our estimates of BF accuracy and repeatability (i.e., 1.4 and 0.75 mm, respectively) are conservative. Because of their accuracy and repeatability, our data can be used to correctly rank animals for each trait, thereby facilitating genetic improvement in carcass merit (Robinson et al., 1992).
The United States does not have a national certification program for ultrasound in sheep, but we believe that one should be established with sheep-specific validation criteria because trait means and variability differ among species. Because of these differences among species, direct comparisons of our accuracy and repeatability statistics with validation criteria established for beef and swine national certification programs are largely inappropriate. However, we scaled the beef (BIF, 2002) and swine (Bates and Christians, 1994) validation criteria for approximate trait means of 1.14 cm for BF and 80.6 cm2 for LMA in cattle (Van Vleck et al., 2007), and 1.74 cm for BF and 43.3 cm2 for LMA in pigs (Chen et al., 2002). When scaled, the maximum allowable SE of prediction for BF were approximately 22% of the trait means for beef and swine, and the maximum allowable SE of prediction for LMA were approximately 9.6 and 7.5% of the trait means for beef and swine, respectively. Our SE of prediction in lambs were 21 and 9.7% of the trait means for BF and LMA, respectively. We could find only one other report of SE of prediction estimates for sheep in the United States (Tait et al., 2005). Their SE of prediction for BF ranged from 1.2 to 1.3 mm for 3 technicians, compared with our 1.4 mm, and their SE of prediction for LMA ranged from 1.92 to 2.18 cm2, compared with our 1.55 cm2.
Most reports on using ultrasound to estimate corresponding carcass measures in sheep are limited to correlations, which are not used in the beef and swine certification programs. Correlations are of limited value because trait variability influences their magnitude, and they are not direct measures of precision and accuracy. Correlations for LMA, LMD, and BF in our study were slightly greater than those reported for sheep with similar trait variability (Banks et al., 2001; Tait et al., 2005).
Figure 2 illustrates a tendency for ultrasound to overestimate carcass measures in lean or light-muscled wethers and underestimate carcass measures in fat or heavy-muscled wethers. This tendency reduced trait variation for ultrasound measures, compared with carcass measures. However, coefficients for regression of carcass measures on ultrasound estimates were not greater than 1 (P > 0.05; data not shown) for LMA, LMD, or BF. Similar over- and underestimations from ultrasound have been reported for beef cattle (Greiner et al., 2003) and pigs (Moeller and Christian, 1998).
Effects of LMA and LMD on Carcass Yield
Our data indicate that wethers with larger LMA, at a standardized BW and BF, will yield carcasses with greater dressing percentage and greater value, and these relationships are detectable with live-animal ultrasound. Increasing ultrasound LMA by 1 SD (i.e., 2.01 cm2), independently of BW and ultrasound BF, resulted in an increase in dressing percentage of 0.95 percentage points, an increase in gross carcass value of US$3.15, and an increase in boxed carcass value of US$3.86. Predictions using carcass LMA support the relationships between ultrasound LMA and carcass yield and value; that is, the observed relationships were not simply artifacts of ultrasound. Increasing carcass LMA by 1 SD (i.e., 2.33 cm2), independently of BW and carcass BF, resulted in an increase in dressing percentage of 1.57 percentage points, an increase in gross carcass value of US$5.12, and an increase in boxed carcass value of US$6.84. Thus, there are biological and economic incentives for increasing LMA in wethers. Additionally, there is an incentive to improve the accuracy of ultrasound estimates. Compared with our accuracy, perfect ultrasound estimates (i.e., identical to corresponding carcass measures) would detect more LMA variation and thus would provide more accurate predictions of carcass yield and value.
The increase in carcass value per unit of LMA increase is attributed primarily to an increase in dressing percentage, and a much lesser extent to disproportionate increases in high-value subprimal cut weights (i.e., rack, loin, and leg). Boxed carcass value, adjusted for BW and BF, increased US$3.86 and US$6.84 per SD increase in ultrasound and carcass LMA, respectively. These LMA regression coefficient estimates reflect increases in carcass value due jointly to an increase in dressing percentage and to disproportionate increases in high-value subprimal cuts. Adjusting boxed carcass value for chilled carcass weight and BF isolates the effect of disproportionate increases in high-value subprimal cuts. By doing so, boxed carcass value increased only US$0.56 (P = 0.18) and US$1.72 (P < 0.001; data not shown) per SD increase in ultrasound and carcass LMA, respectively.
Similar relationships with carcass yield and value were observed when LMD was used as the measure of carcass muscling, and there are biological and economic incentives for increasing LMD in wethers. Increasing ultrasound LMD by 1 SD (i.e., 0.295 cm), independently of BW and ultrasound BF, resulted in an increase in dressing percentage of 0.93 percentage points, an increase in gross carcass value of US$2.23, and an increase in boxed carcass value of US$2.57. Increasing carcass LMD by 1 SD (i.e., 0.363 cm), independently of BW and ultrasound BF, resulted in an increase in dressing percentage of 1.32 percentage points, an increase in gross carcass value of US$3.98, and an increase in boxed carcass value of US$4.95. Most of the increase in carcass value per unit increase of LMD was likewise attributed to an increase in dressing percentage. Boxed carcass value increased only US$0.21 (P = 0.62) and US$0.84 (P = 0.04) per SD increase in ultrasound and carcass LMD, respectively, when adjusted for chilled carcass weight and BF (data not shown).
Several studies to evaluate the utility of LMA or LMD as predictors of carcass composition have been reported. Conclusions drawn from these studies vary widely across methods to assess LMA or LMD, methods to assess composition, experimental populations, and statistical models. Scientists that adjusted carcass yield or composition for the effect of BW have generally found that LMD contributes significantly to prediction equations (Berg et al., 1996; Wolf et al., 2006), although LMA was not a good predictor of chemical composition (Leymaster et al., 1985). In studies where carcass yield or composition was adjusted for carcass weight, results have been inconsistent. Brady et al. (2003) and Hopkins and Fogarty (1998) found that the LMA measure contributed significantly to the prediction of carcass and subprimal yield, and this is consistent with the current study for carcass LMA. However, in other studies in which carcass yield or composition was adjusted for carcass weight, LMA and LMD measures did not contribute significantly to the prediction equations (Jones et al., 1992; Berg et al., 1997). Our data indicate that LMA and LMD effects were greater for overall carcass size than for subprimal cut proportions, and this coincides with the inconsistencies in the literature when carcass weight was modeled as a covariate. Regardless of these mixed findings, genetic selection using ultrasound measures of muscling and fatness has improved body composition in sheep populations, and these measures have been incorporated into various national genetic improvement programs (for review, see Stanford et al., 1998).
The effects of LMA and LMD on carcass yield and value in the current study were evaluated on untrimmed carcasses and subprimal cuts, and not on yields of dissected or chemical lean. We have, however, adjusted these effects for BF, and several studies have shown that the BF measure is a reliable indicator of overall carcass fatness. Correlations between BF and weight of carcass fat and carcass chemical fat composition were 0.55 and 0.72, respectively (Ramsey et al., 1991; Wolf et al., 2006), and the BF measure contributed significantly to predictions of fat trim weights and proportions and carcass chemical fat composition (Leymaster et al., 1985; Jones et al., 1992; Wolf et al., 2006). Thus, we believe that the LMA- or LMD-specific effects on carcass yield reported herein are reflective of increases in lean tissue mass. Also, because the mean yield grade in our population was 2.8, we believe our predictions for gross carcass value have reference to typical US slaughter lambs.
The US sheep industry has been plagued with excessively fat lambs because efforts to increase slaughter weights, which are largely driven by economic factors, have outpaced efforts to improve carcass composition (Beermann et al., 1995). When untrimmed carcass weight is the sole determinant of value, our data clearly indicate that wethers with greater BF produce higher-yielding and therefore more valuable carcasses. In the current study, residual correlation between LMA and BF, adjusted for BW and breed of sire effects, was negative for carcass measures (r = –0.24; P < 0.01), and not different from 0 for ultrasound measures (r = 0.13; P > 0.10). Similar results have been reported; phenotypic and genetic correlations between BF and LMA were positive when measured on live animals (r = 0.51 and 0.40, respectively), but slightly negative when measured on carcasses (r = –0.02 and –0.09, respectively; Safari et al., 2005). We have no apparent explanation for the difference in relationships for carcass and ultrasound measures. However, because BF and LMA do not exhibit a tightly coupled, unfavorable relationship, improvement in carcass composition at heavier slaughter weights is likely achievable.
Our data indicate that the LMA measure was superior to the LMD measure as a predictor of carcass yield and value, regardless of method of assessment (i.e., ultrasound or carcass), although residual correlations between measures were 0.75 (P < 0.01) for both methods. The superiority of LMA in our data set was attributed to more trait variability for LMA (CV = 13% for ultrasound, 15% for carcass), compared with LMD (CV = 9% for ultrasound, 11% for carcass), and slightly greater residual correlations with carcass weight and weights of high-value subprimal cuts. In a review of genetic parameter estimates, trait variation for LMA was greater than for LMD when measured on the carcass, but the opposite was true when measured on the live animal (Safari et al., 2005). Nevertheless, we believe that, when accurately estimated, the 2-dimensional LMA measure yields more information about LM size than would the one-dimensional LMD measure.
We acknowledge, however, that the LMD measure may be easier to obtain, and perhaps preferable to the LMA measure, when factors such as transducer length and frequency, wool removal, measurement throughput, and technician training are considered. Additionally, heritability estimates for measures taken on the live animal were greater for LMD than LMA (Safari et al., 2005), thus response to genetic selection could be greater for LMD. However, our understanding is that heritability estimates reported for live-animal LMA are largely derived using indirect measures of LMA, which assume elliptical properties about the muscle shape, and not on a direct measure of muscle area from delineating the muscle perimeter as was done in this study. Thus, these heritability estimates for LMA may be biased downward because of limited measurement accuracy (Falconer and Mackay, 1996). When measured on the carcass, heritability estimates for LMA were greater than for LMD (Safari et al., 2005). Further research on the estimates of genetic parameters for ultrasound data in US production systems is warranted.
Applications
The US sheep industry is challenged with improving the yield and composition of lamb carcasses, and in vivo tools that estimate carcass yield and composition can benefit the industry. Research that assesses the reliability of ultrasound and evaluates the relationships between ultrasound measures and carcass yield and value can provide important knowledge for sheep breeders and producers. We believe the current data justify the increased use of live-animal ultrasound in terminal lamb production. Also, a national ultrasound certification program for sheep may increase the efficacious use of ultrasound in the US sheep industry by providing 1) technician training; 2) established and standardized validation criteria; and 3) a forum for the dissemination of information on current ultrasound technologies, research results, and validated technicians.
The increase in gross carcass value reported in the current study reflects expected additional gross income for producers who market lambs using a carcass-merit pricing system. Producers who market lambs on a carcass basis may have an economic incentive for using rams with greater genetic merit for LMA. Additionally, rams with high EPD for ultrasound LMA should have increased value. Using the phenotypic variance in the current report (i.e., 4.04 cm2), and assuming a heritability of 0.4, a ram that is 2 additive genetic SD above the mean would have an ultrasound LMA EPD of +1.27 cm2. Progeny of this high EPD ram, compared with the average EPD ram, should generate an increase in gross income approaching US$300 for every 150 lambs marketed.
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Footnotes |
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2 The authors acknowledge T. Kellom, M. Williams, T. Northcutt, and the USSES operations staff for animal procedures and data collection; and D. O’Diam, A. Radunz, J. Gevin, K. Brueggemeier, and A. Naber for slaughter and fabrication procedures and data collection.
3 Corresponding author: gregory.lewis{at}ars.usda.gov
Received for publication December 28, 2007. Accepted for publication June 6, 2008.
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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