Development and validation of equations utilizing lamb vision system output to predict lamb carcass fabrication yields

This study was performed to validate previous equations and to develop and evaluate new regression equations for predicting lamb carcass fabrication yields using outputs from a lamb vision system-hot carcass component (LVS-HCC) and the lamb vision system-chilled carcass LM imaging component (LVS-CCC). Lamb carcasses (n = 149) were selected after slaughter, imaged hot using the LVS-HCC, and chilled for 24 to 48 h at -3 to 1 degrees C. Chilled carcasses yield grades (YG) were assigned on-line by USDA graders and by expert USDA grading supervisors with unlimited time and access to the carcasses. Before fabrication, carcasses were ribbed between the 12th and 13th ribs and imaged using the LVS-CCC. Carcasses were fabricated into bone-in subprimal/primal cuts. Yields calculated included 1) saleable meat yield (SMY); 2) subprimal yield (SPY); and 3) fat yield (FY). On-line (whole-number) USDA YG accounted for 59, 58, and 64%; expert (whole-number) USDA YG explained 59, 59, and 65%; and expert (nearest-tenth) USDA YG accounted for 60, 60, and 67% of the observed variation in SMY, SPY, and FY, respectively. The best prediction equation developed in this trial using LVS-HCC output and hot carcass weight as independent variables explained 68, 62, and 74% of the variation in SMY, SPY, and FY, respectively. Addition of output from LVS-CCC improved predictive accuracy of the equations; the combined output equations explained 72 and 66% of the variability in SMY and SPY, respectively. Accuracy and repeatability of measurement of LM area made with the LVS-CCC also was assessed, and results suggested that use of LVS-CCC provided reasonably accurate (R2 = 0.59) and highly repeatable (repeatability = 0.98) measurements of LM area. Compared with USDA YG, use of the dual-component lamb vision system to predict cut yields of lamb carcasses improved accuracy and precision, suggesting that this system could have an application as an objective means for pricing carcasses in a value-based marketing system.     

Yield grades and cutability of carcass beef with and without kidney and pelvic fat

Cut-out data from 2,550 steer carcasses representing British, Continental and Zebu breeding were analyzed to evaluate yield grade classes based on three equations: 1) Ya = 2.5 + .984 AFT + .0084 HCW - .05 REA + .2 KPF; 2) Yb = same as Ya with intercept changed to 3.2 and KPF deleted; 3) Yc = 3.0 + .984 AFT + .0041 HCW - .03 REA, as proposed by USDA in 1984; where AFT = adjusted fat thickness (cm), HCW = hot carcass weight (kg), REA = rib-eye area (cm2), and KPF = kidney and pelvic fat (%). Essentially boneless, closely trimmed (8 mm) roasts and steaks of the four major retail cuts (MRC) were made from one side of each carcass. Cutability was calculated as: Ca, % = 100 (MRC/side) and Cb,c % = 100 (MRC/side, KPF removed). Cutability increased (P less than .01) an average of two percentage points when KPF was removed. In general, removing KPF from the estimation of cutability and changing the coefficients for REA and HCW resulted in a decrease in the number of carcasses yield graded 1 or 4 and an increase in the number of carcasses in yield grade 2. Redistribution of carcasses was greater for Yc than for Yb. Carcasses classified with equation Yc tended (P greater than .05) to have greater cutability in yield grades 1 and 2, and lower (P less than .01) cutability in yield grades 3, 4 and 5.(ABSTRACT TRUNCATED AT 250 WORDS)     

Retail cut yields of Rambouillet wether lambs fed the beta-adrenergic agonist L644,969.

Twenty Rambouillet wether lambs were given ad libitum access to a diet with (BAA, n = 10) or without (control, n = 10) 1 ppm of the beta-adrenergic agonist L644,969. Lambs were fed to a constant slaughter weight end point of 54.5 kg. Carcasses were fabricated to yield bone-in and boneless cuts that were trimmed progressively to 1.27, .64, .32, and .00 cm of s.c. fat remaining. Addition of BAA did not affect growth traits. Actual and adjusted fat thickness, body wall thickness, and percentage of kidney-pelvic fat did not differ between control and BAA lambs. However, BAA increased longissimus muscle area, longissimus muscle depth, and leg score while decreasing USDA yield grade. The BAA increased carcass conformation scores and decreased flank lean color scores. No other carcass quality measurements were affected by BAA. Addition of BAA did not affect overall carcass yields of bone-in retail cuts. However, BAA increased overall carcass yields of boneless retail cuts regardless of fat trim level. The BAA increased bone-in leg yield. Yield of boneless sirloin, bone-in loin and boneless loin were not affected by BAA. For these cuts, the percentage change from the control was highly dependent on fat trim level. There was no difference in short-cut, shank-off, semiboneless leg yield between control and BAA. Addition of BAA did not affect yield of bone-in rack regardless of fat trim level. However, BAA greatly increased yield of boneless ribeye. The BAA did not affect yield of bone-in or boneless shoulder.(ABSTRACT TRUNCATED AT 250 WORDS)     

Real-time augmentation of USDA yield grade application to beef carcasses using video image analysis

In two phases, this study assessed the ability of two video image analysis (VIA) instruments, VIASCAN and Computer Vision System (CVS), to augment assignment of yield grades (YG) to beef carcasses to 0.1 of a YG at commercial packing plant speeds and to test cutout prediction accuracy of a YG augmentation system that used a prototype augmentation touchpanel grading display (designed to operate commercially in real-time). In Phase I, beef carcasses (n = 505) were circulated twice at commercial chain speeds (340 carcasses per hour) by 12 on-line USDA graders. During the first pass, on-line graders assigned a whole-number YG and a quality grade (QG) to carcasses as they would normally. During the second pass, on-line graders assigned only adjusted preliminary yield grades (APYG) and QG to carcasses, whereas the two VIA instruments measured the longissimus muscle area (LMA) of each carcass. Kidney, pelvic, and heart fat (KPH) was removed and weighed to allow computation of actual KPH percentage. Those traits were compared to the expert YG and expert YG factors. On-line USDA graders' APYG were closely related (r = 0.83) to expert APYG. Instrument-measured LMA were closely related (r = 0.88 and 0.94; mean absolute error = 0.3 and 0.2 YG units, for VIASCAN and CVS, respectively) to expert LMA. When YG were augmented using instrument-measured LMA and computed either including or neglecting actual KPH percentage, YG were closely related (r = 0.93 and 0.92, mean absolute error = 0.32 and 0.40 YG units, respectively, using VIASCAN-measured LMA; r = 0.95 and 0.94, mean absolute error = 0.24 and 0.34 YG units, respectively, using CVS-measured LMA) to expert YG. In Phase II, augmented YG were assigned (0.1 of a YG) to beef carcasses (n = 290) at commercial chain speeds using VIASCAN and CVS to determine LMA, whereas APYG and QG were determined by online graders via a touch-panel display. On-line grader YG (whole-number), expert grader YG (to the nearest 0.1 of a YG), and VIASCAN- and CVS-augmented YG (to the nearest 0.1 of a YG) accounted for 55, 71, 60, and 63% of the variation in fabricated yields of closely trimmed subprimals, respectively, suggesting that VIA systems can operate at current plant speeds and effectively augment official USDA application of YG to beef carcasses.     

Evaluation of the E+V video image analysis system as a predictor of pork carcass meat yield

This study was conducted to assess the ability of the VCS2001 (E+V, Oranienburg, Germany) video image analysis system to predict pork carcass composition. Pork carcasses (n = 278) were selected from a commercial packing plant to differ in weight, Fat-O-Meater (FOM) predicted percentage lean, and gender. Carcasses were imaged three times with the VCS2001, chilled overnight, and then sequentially fabricated into boneless subprimals. The VCS2001 accurately predicted the weight of total saleable product (R2 = 0.88, root mean square error [RMSE] = 1.84) and fat-corrected lean (R2 = 0.92, RMSE = 1.66), but autocorrelation existed between dependent and independent variables. The VCS2001 was acceptably accurate and precise in predicting weights of bone-in ham (R2 = 0.83, RMSE = 0.80), bone-in loin (R2 = 0.74, RMSE = 1.17), loin lean (R2 = 0.77, RMSE = 0.82), belly (R2 = 0.78, RMSE = 0.94), sparerib (R2 = 0.55, RMSE = 0.28), and boneless shoulder (R2 = 0.73, RMSE = 0.79). Weights were more accurately predicted than yields (as a percentage of hot carcass weight) of total saleable product (R2 = 0.47, RMSE = 1.97) or total fat-corrected lean (R2 = 0.44, RMSE = 1.89) using VCS2002, and it did not accurately predict percentages of bone-in ham (R2 = 0.45, RMSE = 1.13), ham lean (R2 = 0.32, RMSE = 1.46), bone-in loin (R2 = 0.29, RMSE = 1.36), loin lean (R2 = 0.56, RMSE = 0.90), belly (R2 = 0.43, RMSE = 1.08), sparerib (R2 = 0.08, RMSE = 0.32), or boneless shoulder (R2 = 0.30, RMSE = 0.88). New prediction models and equations were developed using VCS2001 output variables plus hot carcass weight to predict weight of total saleable product (R2 = 0.89, RMSE = 1.72) and fat-corrected lean (R2 = 0.93, RMSE = 1.55) with very minimal increases in accuracy and precision over that achieved using E+V-programmed models and equations. Use of new prediction models and equations marginally improved accuracy and precision of estimations of total saleable product yield (R2 = 0.56, RMSE = 1.81) and fat-corrected lean yield (R2 = 0.57, RMSE = 1.67) over that achieved using E+V-programmed models and equations. The VCS2001 was not able to predict pork carcass composition more accurately than existing technology; therefore, further development is needed to assure commercial viability of this instrument.     

Using current on-line carcass evaluation parameters to estimate boneless and bone-in pork carcass yield as influenced by trim level.

The objective of this study was to develop prediction equations for estimating proportional carcass yield to a variety of external trim levels and bone-in and boneless pork primal cuts. Two hundred pork carcasses were selected from six U.S. pork processing plants and represented USDA carcass grades (25% USDA #1, 36% USDA #2, 25% USDA #3, and 14% USDA #4). Carcasses were measured (prerigor and after a 24 h chill) for fat and muscle depth at the last rib (LR) and between the third and fourth from last rib (TH) with a Hennessy optical grading probe (OGP). Carcasses were shipped to Texas A&M University, where one was randomly assigned for fabrication. Selected sides were fabricated to four lean cuts (ham, loin, Boston butt, and picnic shoulder) then fabricated progressively into bone-in (BI) and boneless (BL) four lean cuts (FLC) trimmed to .64, .32, and 0 cm of s.c. fat, and BL 0 cm trim, seam fat removed, four lean cuts (BLS-OFLC). Total dissected carcass lean was used to calculate the percentage of total carcass lean (PLEAN). Lean tissue subsamples were collected for chemical fat-free analysis and percentage carcass fat-free lean (FFLEAN) was determined. Longissimus muscle area and fat depth also were collected at the 10th and 11th rib interface during fabrication. Regression equations were developed from linear carcass and OGP measurements predicting FLC of each fabrication point. Loin muscle and fat depths from the OPG obtained on warm, prerigor carcasses at the TH interface were more accurate predictors of fabrication end points than warm carcass probe depth obtained at the last rib or either of the chilled carcass probe sites (probed at TH or LR). Fat and loin muscle depth obtained via OGP explained 46.7, 52.6, and 57.1% (residual mean square error [RMSE] = 3.30, 3.19, and 3.04%) of the variation in the percentage of BI-FLC trimmed to .64, .32, and 0 cm of s.c. fat, respectively, and 49.0, 53.9, and 60.7% (RMSE = 2.91, 2.81, and 2.69%) of the variation in the percentage of BL-FLC trimmed to .64, .32, and 0 cm of s.c. fat, respectively. Fat and loin muscle depth from warm carcass OGP probes at the TH interface accounted for 62.4 and 63.5% (RMSE = 3.38 and 3.27%) of the variation in PLEAN and FFLEAN, respectively. These equations provide an opportunity to estimate pork carcass yield for a variety of procurement end point equations using existing on-line techniques.     

Technical note: the United States Department of Agriculture beef yield grade equation requires modification to reflect the current longissimus muscle area to hot carcass weight relationship

With the adoption of visual instrument grading, the calculated yield grade can be used for payment to cattle producers selling on grid pricing systems. The USDA beef carcass grading standards include a relationship between required LM area (LMA) and HCW that is an important component of the final yield grade. As noted on a USDA yield grade LMA grid, a 272-kg (600-lb) carcass requires a 71-cm(2) (11.0-in.(2)) LMA and a 454-kg (1,000-lb) carcass requires a 102-cm(2) (15.8-in.(2)) LMA. This is a linear relationship, where required LMA = 0.171(HCW) + 24.526. If a beef carcass has a larger LMA than required, the calculated yield grade is lowered, whereas a smaller LMA than required increases the calculated yield grade. The objective of this investigation was to evaluate the LMA to HCW relationship against data on 434,381 beef carcasses in the West Texas A&M University (WTAMU) Beef Carcass Research Center database. In contrast to the USDA relationship, our data indicate a quadratic relationship [WTAMU LMA = 33.585 + 0.17729(HCW) -0.0000863(HCW(2))] between LMA and HCW whereby, on average, a 272-kg carcass has a 75-cm(2) (11.6-in.(2)) LMA and a 454-kg carcass has a 96-cm(2) (14.9-in.(2)) LMA, indicating a different slope and different intercept than those in the USDA grading standards. These data indicate that the USDA calculated yield grade equation favors carcasses lighter than 363 kg (800 lb) for having above average muscling and penalizes carcasses heavier than 363 kg (800 lb) for having below average muscling. If carcass weights continue to increase, we are likely to observe greater proportions of yield grade 4 and 5 carcasses because of the measurement bias that currently exists in the USDA yield grade equation.     

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.     

Economics of callipyge lamb production

This paper examines the economic implications of callipyge (CLPG) lamb production. The price, as it relates to competing meats and excess fat, significantly impact lamb demand, and CLPG genetics improves those factors. The CLPG phenotype does not affect number or weight of lambs weaned or postweaning ADG, but it does improve postweaning feed efficiency by approximately 10%; dressing percentage approximately 7.5%; and yields of wholesale leg (11.8%), loin (4.7%), rack (2.5%), and shoulder (2.3%). Total production costs for a 59-kg lamb are 4% lower in CLPG lambs due to improved feed efficiency. Assuming pelt and offal value pays for slaughter costs, the costs of normal (N) and CLPG carcasses are the same as for live lambs, $81 and $78, respectively; but, due to dressing percentage, the N carcass weighs 29.2 kg and the CLPG carcass, 31.4 kg. Thus, carcass costs for N and CLPG lambs are $2.77/kg and $2.49/kg, respectively. Decreased feed costs, combined with increased carcass and primal cut yields for CLPG lambs, lowers the price required to recover meat costs for leg, loin, rack, and shoulder by 19.7, 14.4, 12.6, and 11.9%, respectively. Successful marketing of CLPG loin and rack depends on the use of one of several postharvest tenderization procedures. Moisture-enhanced pork is accepted by consumers and often sells for a premium; and moisture enhancement may be appropriate for CLPG lamb. The meat cost per kilogram (including a $.10 per kilogram treatment cost) of tenderized and moisture-enhanced CLPG leg, loin, rack, and shoulder containing 10% added water and ingredients would be lowered to $2.51, $4.65, $5.34, and $1.85, respectively. That represents a total of a 20.9% reduction in cost-basis price. When expressed on the basis of increased revenue from the additional yield of cuts at a given market price, the value of CLPG and moisture-enhanced CLPG cuts from a 59-kg lamb would be, respectively, 14.2% and 23.4% higher than for N lamb. Industrywide adoption of CLPG could increase intermediate-run U.S. profits by $109 million, but the actual effects of CLPG attributes, such as a visual appeal, lower fat and cholesterol content, and reduced seam fat, on consumer demand need to be quantified. If accepted by packers and consumers, moisture-enhanced CLPG lamb has the potential to decrease the cost of lamb to consumers and increase lamb industry profitability.     

Dual-component video image analysis system (VIASCAN) as a predictor of beef carcass red meat yield percentage and for augmenting application of USDA yield grades

An improved ability to quantify differences in the fabrication yields of beef carcasses would facilitate the application of value-based marketing. This study was conducted to evaluate the ability of the Dual-Component Australian VIASCAN to 1) predict fabricated beef subprimal yields as a percentage of carcass weight at each of three fat-trim levels and 2) augment USDA yield grading, thereby improving accuracy of grade placement. Steer and heifer carcasses (n = 240) were evaluated using VIASCAN, as well as by USDA expert and online graders, before fabrication of carcasses to each of three fat-trim levels. Expert yield grade (YG), online YG, VIASCAN estimates, and VIASCAN estimated ribeye area used to augment actual and expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, and hot carcass weight), respectively, 1) accounted for 51, 37, 46, and 55% of the variation in fabricated yields of commodity-trimmed subprimals, 2) accounted for 74, 54, 66, and 75% of the variation in fabricated yields of closely trimmed subprimals, and 3) accounted for 74, 54, 71, and 75% of the variation in fabricated yields of very closely trimmed subprimals. The VIASCAN system predicted fabrication yields more accurately than current online yield grading and, when certain VIASCAN-measured traits were combined with some USDA yield grade factors in an augmentation system, the accuracy of cutability prediction was improved, at packing plant line speeds, to a level matching that of expert graders applying grades at a comfortable rate.     

Evaluation of the Hennessy grading probe to predict yields of lamb carcasses fabricated to multiple end points.

Lamb carcasses (n = 278) were selected immediately after slaughter and fat thickness was measured with the SP2 Hennessy grading probe (HP) at the interface of the 12th and 13th ribs, 3.8 cm from the backbone. After a 24-h chilling period, carcasses were graded by a USDA grader and probed with the HP to obtain a fat thickness measure on the chilled carcass. One hundred sixty-five carcasses were fabricated into wholesale cuts (.64 cm of external fat trim), and 113 carcasses were fabricated into tray-ready retail cuts (.25 cm of external fat trim). Carcass weight, fat thickness (metal probe), adjusted fat thickness, hot and chilled carcass HP fat measures, as well as kidney and pelvic fat percentage and USDA yield grade, were highly correlated to cutting yield for both fabrication methods. Regression models developed to predict wholesale cut yields using HP or grader-collected measures were similar with respect to predictive accuracy. Fat thickness explained most of the variation in wholesale and tray-ready cut yields among the variables collected by the grader. Kidney and pelvic fat accounted for more of the variation in yield of wholesale cuts during stepwise regression to determine HP equations, but for predicting tray-ready yields, fat thickness taken with the HP accounted for the largest amount of variation. Equations developed to predict tray-ready retail cut yields using the HP or USDA grader-collected carcass measures were similar in the amount of variation explained. Kidney and pelvic fat percentage must be included in equations to maximize predictive accuracy when this depot site is left in carcasses.     

Quantification of saleable meat yield using objective measurements captured by video image analysis technology

Video image analysis (VIA) images from grain-finished beef carcasses [n = 211; of which 63 did not receive zilpaterol hydrochloride (ZIL) and 148 received ZIL before harvest] were analyzed for indicators of muscle and fat to illustrate the ability to improve methodology to predict saleable meat yield of cattle fed and not fed ZIL. Carcasses were processed in large commercial beef processing facilities and were fabricated into standard subprimals, fat, and bone. Images taken by VIA technology were evaluated using computer image analysis software to quantify fat and lean parameters which were subsequently used in multiple-linear regression models to predict percentage of saleable meat yield for each carcass. Prediction models included variables currently quantified by VIA technology such as LM area (LMA), subcutaneous (SC) fat thickness at 75% the length of the LM (SFT75), and intramuscular fat score (IMF). Additional distance and area measures included LM width (LW), LM depth (LD), iliocostalis muscle area (IA), SC fat thickness at 25, 50, and 100% the length of the LM (SFT25, SFT50, SFT100), SC fat area from 25 to 100% the length of the LM (SCFA), and SC fat area adjacent to the 75% length of the LM from the spinous processes (SCFA75). Multiple ratio and product variables were also created from distance and area measures. For carcasses in this investigation, a 6 variable equation (Adj. R(2) = 0.62, MSE = 0.022) was calculated which included coefficients for ZIL treatment, SCFA75, LW, SCFA, SCFA/HCW, and SFT100/HCW. Use of parameters in the U.S. (Adj. R(2) = 0.39, MSE = 0.028) and Canadian [Adj. R(2) = 0.10, root mean square error (MSE) = 0.034] yield grade equations lack the predictability of the newly adapted equations developed for ZIL-fed and non-ZIL-fed cattle. Prediction equations developed in this study indicate that the use of VIA technology to quantify measurements taken at the 12th/13th rib separation could be used to predict saleable meat yield more accurately than those currently in use by U.S. and Canadian grading systems. Improvement in saleable meat yield prediction has the potential to decrease boxed beef variability via more homogeneous classification of carcass fabrication yield.     

Online evaluation of a commercial video image analysis system (Computer Vision System) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. United States Department of Agriculture

Objective quantification of differences in wholesale cut yields of beef carcasses at plant chain speeds is important for the application of value-based marketing. This study was conducted to evaluate the ability of a commercial video image analysis system, the Computer Vision System (CVS) to 1) predict commercially fabricated beef subprimal yield and 2) augment USDA yield grading, in order to improve accuracy of grade assessment. The CVS was evaluated as a fully installed production system, operating on a full-time basis at chain speeds. Steer and heifer carcasses (n = 296) were evaluated using CVS, as well as by USDA expert and online graders, before the fabrication of carcasses into industry-standard subprimal cuts. Expert yield grade (YG), online YG, CVS estimated carcass yield, and CVS measured ribeye area in conjunction with expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, hot carcass weight) accounted for 67, 39, 64, and 65% of the observed variation in fabricated yields of closely trimmed subprimals. The dual component CVS predicted wholesale cut yields more accurately than current online yield grading, and, in an augmentation system, CVS ribeye measurement replaced estimated ribeye area in determination of USDA yield grade, and the accuracy of cutability prediction was improved, under packing plant conditions and speeds, to a level close to that of expert graders applying grades at a comfortable rate of speed offline.     

Beef carcass composition of slaughter cattle differing in frame size, muscle score, and external fatness.

Commercial slaughter steers (n = 329) and heifers (n = 335) were selected to vary in slaughter frame size and muscle thickness score, as well as carcass adjusted 12th-rib fat thickness. After collection of USDA carcass grade data, one side of each carcass was fabricated into boneless primals, subprimals, and minor tissue components. Cuts were trimmed to 2.54, 1.27, and .64 cm of external fat, except for the knuckle, tri-tip, and tenderloin, which were trimmed of all fat. Forced four-variable regression equations were used to predict the percentage (chilled carcass weight basis) yield of boneless subprimals at the three fat trim levels as influenced by sex class, frame size, muscle score, and adjusted 12th-rib fat thickness. Independent variables that had the most influence on percentage yield of primals and boneless subprimals were adjusted 12th-rib fat thickness and sex class. Within the same phenotypic group, percentage of trimmable fat increased by 2.32% as 12th-rib fat thickness increased by .75 cm. Estimated percentage yield of the major subprimals from the loin and round tended to be higher or relatively equal for heifer carcasses at all trim levels compared with those subprimals from steer carcasses. Holding frame size, sex class, and fat thickness constant, there was a higher percentage yield of chuck roll, rib eye roll, and strip loin for carcasses from thick-muscled cattle than for those from average- and thin-muscled cattle. Frame size had little effect on percentage yield of boneless subprimals.     

Prediction of yield of retail cuts for native and crossbred Chinese Yellow cattle

Seven hundred and three native and crossbred Chinese Yellow cattle (mean live weight: 523 ± 38 kg) were slaughtered, chilled and segmented. The hot carcass weight (HCW, kg), fat thickness (FT, cm) and rib eye area (REA, cm²) were measured to predict weights and percentages of beef cattle retail cuts. A correlation analysis showed that the HCW and REA were positively correlated with the weights of the total retail cuts (TRC, kg), top grade retail cuts, prime retail cuts and percentage of total carcass weight. A regression analysis indicated that HCW and REA were the best predictors for the weight of total retail cuts (Y = ?16.71 + 0.382 HCW + 0.593 REA), and the HCW explained more of the variation than REA. Meanwhile, HCW and REA accounted for 62% of the variation of percentage of total retail cuts (Y = 43.24 ? 0.025 HCW + 0.170 REA), whereas the REA was more valuable than the HCW. The FT contributed little in estimating weight or percentage of retail cuts.     

Carcass traits, cut yields, and compositional end points in high-lean-yielding pork carcasses: effects of 10th rib backfat and loin eye area

Pork carcasses (n = 133) were used to investigate the influence of carcass fatness and muscling on composition and yields of pork primal and subprimal cuts fabricated to varying levels of s.c. fat. Carcasses were selected from commercial packing plants in the southeastern United States, using a 3 x 3 factorial arrangement with three levels of 10th rib backfat depth (< 2.03, 2.03 to 2.54, and > 2.54 cm) and three levels of loin eye area (LEA; < 35.5, 35.5 to 41.9, and > 41.9 cm2). Sides from the selected carcasses were shipped to the University of Georgia for carcass data collection by trained USDA-AMS and University of Georgia personnel and fabrication. Sides were fabricated to four lean cuts (picnic shoulder, Boston butt, loin, and ham) and the skinned belly. The four lean cuts were further fabricated into boneless cuts with s.c. fat trim levels of 0.64, 0.32, and 0 cm. The percentages of four lean cuts, boneless cuts (four lean cuts plus skinned, trimmed belly) at 0.64, 0.32, and 0 cm s.c. fat, fat-free lean, and total fat were calculated. Data were analyzed using a least squares fixed effects model, with the main effects of 10th rib backfat and LEA and their interaction. Fatness and muscling traits increased (P < 0.05) as 10th rib backfat and LEA category increased, respectively. However, fat depth measures were not affected greatly by LEA category, nor were muscling measures greatly affected by backfat category. The percentage yield of cuts decreased (P < 0.05) as backfat category increased. Cut yields from the picnic shoulder, Boston butt, and belly were not affected (P > 0.05) by LEA category, whereas the yield of boneless loin and ham increased (P < 0.05) as LEA category increased. Compositionally, the percentage of four lean cuts, boneless cuts at varying trim levels, and fat-free lean decreased incrementally (P < 0.05) as backfat depth increased, whereas parentage total fat and USDA grade increased (P < 0.05) as backfat depth increased. As LEA increased, percentage boneless cuts trimmed to 0.32 and 0 cm s.c. fat and fat-free lean increased and total fat decreased; however, the difference was only significant in the smallest LEA category. Collectively, these data show that decreased carcass fatness plays a greater role in increasing primal and subprimal cut yields and carcass composition than muscling even in lean, heavily muscled carcasses.     

Ultrasonic, needle, and carcass measurements for predicting chemical composition of lamb carcasses

Three groups (n = 147) of New Zealand mixed breed lambs averaging 170 d of age and 31.7 kg in weight were killed after a diet of pasture to determine whether the total depth of soft tissues over the 12th rib 11 cm from the dorsal midline (GR) could be measured in live lambs with sufficient accuracy to warrant its use as a selection tool for breeding flock replacements. Relationships among live and carcass measurements and carcass chemical composition also were determined. An ultrasonic measurement of GR in the live lambs was a more accurate predictor of carcass GR (r = .87) and percentage carcass fat (r = .80) than was a measurement of GR made with a needle (r = .80 and .67, respectively). Both measurements were sufficiently accurate to permit culling of over-fat lambs from breeding flock replacement prospects. The best single indicator of percentage carcass fat (r = .87) was a shoulder fat measurement, followed closely by carcass GR (r = .85). Both were superior to USDA yield grade for estimating carcass chemical composition in these young, lightweight lambs. These two measurements also were most highly related to percentage carcass protein (r = -.78 and r = -.77, respectively). These results indicate possibilities for improving the method of evaluating the composition of U. S. lamb carcasses.     

Yield grade and carcass weight effects on the cutability of lamb carcasses fabricated into innovative style subprimals.

Lamb carcass (n = 100) were selected from USDA yield grades (YG) 2, 3, and 4 and carcass weight (CW) groups 20.4 to 24.9, 25.0 to 29.5, and 29.6 to 34.0 kg. Lamb carcass were fabricated into semiboneless and boneless subprimals and trimmed to three s.c. fat trim levels: .64, .25, and .00 cm of fat remaining. Innovative subprimals were fabricated and yields were calculated for the subprimals and dissectible components (lean, bone, connective tissue, external fat, and seam fat) from each of the various subprimals. Carcass weight as a main effect in a two-way analysis of variance did not account for a significant amount of the variation in yield among trimmed subprimals or the percentage of the dissectible components, but USDA YG was a significant main effect in determining variation in yield for many of the subprimals or dissectible components. Muscle seaming of shoulders and legs and removal of excessive tails on the loin and rack resulted in a majority of the seam fat being removed from these cuts. Dissection data clearly showed that seam fat is a major component of rack and shoulder cuts and with increasing fatness or higher numerical yield grade there are clearly increased amounts of this depot. Increased trimming of external fat magnifies and draws more attention to the amount of seam fat remaining. Production of heavy, lean lambs would be more useful in an innovative type of program because of the larger-sized muscles. Heavy, fat lambs would not be as useful because of their decreased yields and excess seam fat located in cuts that cannot be muscled-seamed because of the loss of retail cut integrity. Seam fat was highly correlated to percentage of kidney and pelvic fat and to external fat thickness and with USDA yield grade but was not strongly correlated to carcass weight.     

Estimates of subprimal yields from beef carcasses as affected by USDA grades, subcutaneous fat trim level, and carcass sex class and type.

One hundred beef carcasses were selected to represent the mix of cattle slaughtered across the United States. Selection criteria included breed type (60% British/continental European, 20% Bos indicus, and 20% dairy carcasses), sex class (beef and Bos indicus: 67% steers, 33% heifers; dairy: 100% steers), USDA quality grade (4% Prime, 53% Choice, and 43% Select), USDA yield grade (10% YG 1, 43% YG 2, 40% YG 3, and 7% YG 4), and carcass weight (steers: 272.2 to 385.6 kg, heifers: 226.8 to 340.2 kg). One side of each carcass was fabricated into boneless subprimals and minor cuts following Institutional Meat Purchase Specifications. After fabrication, subprimals were trimmed progressively of fat in .64-cm increments beginning with a maximum of 2.54 cm and ending with .64 cm. Linear regression models were developed for each individual cut, including fabrication byproduct items (bone, fat trim) to estimate the percentage yield of those cuts reported by USDA Market News. Strip loin, top sirloin butt, and gooseneck rounds from heifers tended to have a higher percentage yield at the same USDA yield grade than the same cuts from steers, possibly resulting from increased fat deposition on heifers. Percentage of fat trimmed from dairy steers was 2 to 3% lower than that from other sex-class/carcass types; however, due to increased percentage of bone and less muscle, dairy steers were lower-yielding. Fat trimmed from carcasses ranged from 7.9 to 15.6% as the maximum trim level decreased from 2.54 to .64 cm.     

Effects of zilpaterol hydrochloride on retail yields of subprimals from beef and calf-fed Holstein steers

Retail cutting tests were conducted on subprimals from cattle fed zilpaterol hydrochloride (ZH) to determine if the improved carcass composition and red meat yield resulting from ZH feeding would translate into increased retail yields of ready-to-cook products. As part of a 3-phase study, selection of carcasses from Holstein steers was done once (fall 2008), followed by the collection of carcasses from beef-type steers on 2 separate occasions (beef study I: summer 2009; beef study II: spring 2010). Each of the 3 groups of steers was assigned previously to 1 of 2 treatments, treated (fed 8.3 mg/kg of ZH for 20 d) or control (not fed ZH). All steers were slaughtered and carcasses were fabricated in commercial beef-processing establishments. Only those carcasses grading USDA Choice or higher were used. Five subprimals were used for both the calf-fed Holstein study (n = 546 subprimals) and beef study I (n = 576 subprimals): beef chuck, chuck roll; beef chuck, shoulder clod; beef round, sirloin tip (knuckle), peeled; beef round, top round; and beef round, outside round (flat). Seven subprimals were used in beef study II (n = 138 subprimals): beef chuck, chuck roll; beef round, sirloin tip (knuckle), peeled; beef round, top round; beef round, eye of round; beef loin, strip loin, boneless; beef loin, top sirloin butt, boneless; and beef loin, tenderloin. A simulated retail market environment was created, and 3 retail meat merchandisers prepared retail cuts from each subprimal so salable yields and processing times could be obtained. Differences in salable yields were found for the calf-fed Holstein steer chuck rolls (96.54% for ZH vs. 95.71% for control; P = 0.0045) and calf-fed Holstein steer top rounds (91.30% for ZH vs. 90.18% for control; P = 0.0469). However, other than heavier subprimals and an increased number of retail cuts obtained, total salable yields measured on a percentage basis and processing times were mostly unaffected by ZH. Cutability advantages of feeding ZH are achieved primarily in the carcass-to-subprimal conversion rather than in the subprimal-to-retail conversion.