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.     

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.     

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.     

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.     

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.     

Effect of hot-fat trimming on factors associated with the subprimal yield of beef carcasses.

Thirty-two crossbred cattle (steers = 17; heifers = 15) exhibiting an ultrasound fat thickness at the 12 to 13th rib region of at least 10 mm were selected from a slaughter shift at a commercial packing plant. After splitting, alternating sides of each carcass were trimmed of 1) subcutaneous fat in excess of 6.4 mm; 2) all kidney, pelvic, and heart fat; and 3) all cod or udder fat and fat in the flank region. Both sides of each carcass were fabricated into subprimals (final trim level of 6.4 mm) according to normal industry procedures. Effect of hot-fat trimming, yield grade (3, 4, and 5), and gender on hot-fat trim, fabrication fat trim, major subprimal, and total subprimal yield of untrimmed and trimmed carcasses were determined. Higher numerical yield grade (YG) corresponded with higher (P less than .05) percentages of hot-fat trim. Hot-fat trimming increased (P less than .05) the difference in fabrication fat trim between steers and heifers and between YG 3 and YG 5. Steers and heifers differed (P less than .05) in percentage of major subprimals and total subprimals when processed conventionally, whereas hot-fat trimming eliminated this difference (P less than .05). Untrimmed YG 3 carcasses had 3.1 and 5.0% higher major subprimal yield (P less than .05) than untrimmed YG 4 and YG 5 carcasses, respectively, whereas hot-fat trimming reduced this difference to 2.5% for YG 4 and to 3.7% for YG 5.(ABSTRACT TRUNCATED AT 250 WORDS)     

On-line prediction of yield grade,longissimus muscle area,preliminary yield grade,adjusted preliminary yield grade,and marbling score using the MARC beef carcass image analysis system

The present experiment was conducted to evaluate the ability of the U.S. Meat Animal Research Center's beef carcass image analysis system to predict calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score under commercial beef processing conditions. In two commercial beef-processing facilities, image analysis was conducted on 800 carcasses on the beef-grading chain immediately after the conventional USDA beef quality and yield grades were applied. Carcasses were blocked by plant and observed calculated yield grade. The carcasses were then separated, with 400 carcasses assigned to a calibration data set that was used to develop regression equations, and the remaining 400 carcasses assigned to a prediction data set used to validate the regression equations. Prediction equations, which included image analysis variables and hot carcass weight, accounted for 90, 88, 90, 88, and 76% of the variation in calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score, respectively, in the prediction data set. In comparison, the official USDA yield grade as applied by online graders accounted for 73% of the variation in calculated yield grade. The technology described herein could be used by the beef industry to more accurately determine beef yield grades; however, this system does not provide an accurate enough prediction of marbling score to be used without USDA grader interaction for USDA quality grading.     

Influence of body condition score on carcass characteristics and subprimal yield from cull beef cows.

Mature beef cows (n = 83) were slaughtered to measure the influence of body condition score (BCS) on carcass characteristics and subprimal yields. All cows were weighed and assigned BCS, based on a 9-point scale, 24 h before slaughter. Cows were slaughtered, and, after a 48-h chilling period, quality and yield grade data were collected on the left side of each carcass. The right side was quartered, fabricated into primal cuts, and weighed. Each primal cut was further processed into boneless subprimal cuts, minor cuts, lean trim, fat, and bone. Cuts were progressively trimmed to 6.4 and 0 mm of external and visible seam fat. Weights were recorded at all stages of fabrication, and subprimal yields were calculated as a percentage of the chilled carcass weight. Live weight, carcass weight, dressing percentage, fat thickness, longissimus muscle area, muscle:bone ratio, and numerical yield grade increased linearly (P = .0001) and predicted cutability and actual muscle-to-fat ratio decreased linearly (P = .0001) as BCS increased from 2 to 8. Carcasses from BCS-8 cows had the most (P<.05) marbling. The percentage of carcasses grading U.S. Utility, or higher, was 16.7, 20.0, 63.6, 43.3, 73.3, 100.0, and 100.0% for cows assigned a BCS of 2, 3, 4, 5, 6, 7, and 8, respectively. At 6.4 mm of fat trim, carcasses from BCS-5 cows had higher (P<.05) shoulder clod yields than carcasses from cows having a BCS of 6, 7, and 8. Carcasses of BCS-2 cows had lower (P<.05) strip loin yields than carcasses from BCS-3, 4, 5, 6, and 7 cows. Top sirloin butt yields were higher (P<.05) for carcasses of BCS-2, 3, 4, and 5 cows than those of BCS-6, 7, or 8 cows. Carcasses from BCS-7 and 8 cows had lower (P<.05) tenderloin and inside round yields than carcasses of BCS-5, or less, cows. At both fat-trim levels, carcasses from BCS-5 cows had higher (P<.05) eye of round yields than cows assigned BCS of 2, 7, or 8. When subprimal cuts were trimmed to 6.4 mm of visible fat, carcasses from BCS-5 cows had higher (P<.05) total lean product yields than cows assigned a BCS of 2, 4, 7, and 8. Regardless of fat trim, total fat yields increased (P = .0001) and total bone yields decreased (P = .0001) linearly as BCS increased from 2 to 8. Although carcasses from BCS-5 and 6 cows had the highest yields of lean product, cattle producers and packers may benefit most by marketing and(or) purchasing BCS-6 cows because a higher percentage of their carcasses had quality characteristics deemed desirable for fabrication into boneless subprimal cuts.     

Accuracy of application of USDA beef quality and yield grades using the traditional system and the proposed seven-grade yield grade system

Beef carcasses (n = 5,542) were evaluated by three USDA on-line graders and compared with the computed expert USDA quality (QG) and yield grades (YG) during 8-h shifts at a major beef-processing facility for a 2-wk period to evaluate the accuracy of applying USDA QG and YG within the traditional five-grade and the proposed seven-grade (segregating YG 2 and 3 into YG 2A, 2B, 3A, and 3B) YG systems. Quality grade distribution of the carcasses was 1.1% Prime, 50.0% Choice, 43.8% Select, and 5.1% No-Roll. Accuracy of applying QG was not affected (P>.05) by changing from the five-grade (91.5%) to either the seven-grade system, when determining only QG (94.3%), or the seven-grade system, when determining QG and YG (95.0%). Calculated expert YG successfully segregated carcasses into their respective YG, but on-line graders could not differentiate between YG 4 and 5 in the seven-grade systems. The application of YG in the five-grade system was more accurate (P<.05) than either of the seven-grade systems. A trend existed for on-line graders to undergrade carcasses as the numerical YG increased. Total accuracy of applying YG decreased by 19.4 to 21.8% when switching from the five-grade to the seven-grade system. The segmentation of USDA YG 2 and 3 into YG 2A, 2B, 3A, and 3B resulted in a decrease in the ability of on-line graders to accurately apply the YG.     

An evaluation of the lamb vision system as a predictor of lamb carcass red meat yield percentage

An objective method for predicting red meat yield in lamb carcasses is needed to accurately assess true carcass value. This study was performed to evaluate the ability of the lamb vision system (LVS; Research Management Systems USA, Fort Collins, CO) to predict fabrication yields of lamb carcasses. Lamb carcasses (n = 246) were evaluated using LVS and hot carcass weight (HCW), as well as by USDA expert and on-line graders, before fabrication of carcass sides to either bone-in or boneless cuts. On-line whole number, expert whole-number, and expert nearest-tenth USDA yield grades and LVS + HCW estimates accounted for 53, 52, 58, and 60%, respectively, of the observed variability in boneless, saleable meat yields, and accounted for 56, 57, 62, and 62%, respectively, of the variation in bone-in, saleable meat yields. The LVS + HCW system predicted 77, 65, 70, and 87% of the variation in weights of boneless shoulders, racks, loins, and legs, respectively, and 85, 72, 75, and 86% of the variation in weights of bone-in shoulders, racks, loins, and legs, respectively. Addition of longissimus muscle area (REA), adjusted fat thickness (AFT), or both REA and AFT to LVS + HCW models resulted in improved prediction of boneless saleable meat yields by 5, 3, and 5 percentage points, respectively. Bone-in, saleable meat yield estimations were improved in predictive accuracy by 7.7, 6.6, and 10.1 percentage points, and in precision, when REA alone, AFT alone, or both REA and AFT, respectively, were added to the LVS + HCW output models. Use of LVS + HCW to predict boneless red meat yields of lamb carcasses was more accurate than use of current on-line whole-number, expert whole-number, or expert nearest-tenth USDA yield grades. Thus, LVS + HCW output, when used alone or in combination with AFT and/or REA, improved on-line estimation of boneless cut yields from lamb carcasses. The ability of LVS + HCW to predict yields of wholesale cuts suggests that LVS could be used as an objective means for pricing carcasses in a value-based marketing system.     

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.     

The effect of a leptin single nucleotide polymorphism on quality grade, yield grade, and carcass weight of beef cattle

Feedlot producers could optimize the value of cattle in a given market grid if they were able to improve the uniformity of the body composition between cattle among loads. Allelic variation due to a single nucleotide transition (cytosine [C] to thymine [T] transition that results in a Arg25Cys) has been demonstrated to be associated with higher leptin mRNA levels in adipose tissue and increased fat deposition in mature beef, but the effect on economically important carcass traits has not been investigated in either market-ready steers or heifers. Therefore, the objective of this study was to determine the effects of a leptin SNP on the quality grade (QG), yield grade (YG), and weight of beef carcasses. A slaughter trial was conducted using 1,435 crossbred finished heifers and 142 crossbred finished steers as they entered the slaughter facility. Canada QG tended (main effect of genotype P = 0.16, but P < 0.01 for both CC vs. TT and CT vs. TT) to be affected by leptin genotype. Specifically, 7.6 and 7.1% more TT carcasses graded Canada AAA or higher than the CT and CC carcasses, respectively, which supports the suggestion that the leptin SNP is associated with carcass fat. The proportion of carcasses grading Canada YG 1, 2, or 3 was affected (P < 0.01, P = 0.05, and P = 0.02 for YG 1, 2, and 3) by leptin genotype. The proportion of TT carcasses of Canada YG 1 was 12.5 and 15.1% lower than that of CT and CC carcasses, respectively, indicating that rearing animals under the same management and feeding system may result in greater carcass fat and a lower probability of the proportion of carcasses grading YG 1 within certain genotypes. The carcass weights of animals with the CC genotype tended (P = 0.07) to be higher than those of the TT genotype (365.5 vs. 362.3 kg). No significant difference was observed between the TT and CT genotypes in carcass weight. The observed associations between leptin genotype and carcass characteristics may represent an opportunity to genetically identify animals that are most likely to reach specific marketing groups.     

The influence of sex-class, USDA yield grade and USDA quality grade on seam fat trim from the primals of beef carcasses

Beef carcasses (129 steers and 80 heifers) differing in weight, muscling, fatness and marbling score were selected to represent the full spectrum of USDA yield grades; one side was fabricated into boneless primal cuts. Primals were trimmed of all external fat and intermuscular (seam) fat and all components were weighed. Regression equations were developed to predict the percentage of seam fat on an external fat-free primal basis using USDA yield grade (YG), marbling score and a squared function of YG as the independent variables. YG (.77) and marbling score (.67) were highly correlated to seam fat. Heifers tended to have a higher predicted percentage of seam fat than did steers across all YG. Primals from USDA Choice carcasses had approximately 1.0 percentage point more predicted seam fat than did USDA Select primals at the same YG and sex-class. The YG 2.5 heifers had similar proportions of predicted seam fat from primals as YG 3.5 steers, but YG 3.5 heifers tended to have more seam fat than YG 4.5 steers. The same trend was noted between YG 4.5 heifers and YG 5.5 steers, indicating a sex-related deposition of seam fat in fed cattle.     

Foodservice yield and fabrication times for beef as influenced by purchasing options and merchandising styles.

Selected beef subprimals were obtained from fabrication lines of three foodservice purveyors to assist in the development of a software support program for the beef foodservice industry. Subprimals were fabricated into bone-in or boneless foodservice ready-to-cook portion-sized cuts and associated components by professional meat cutters. Each subprimal was cut to generate mean foodservice cutting yields and labor requirements, which were calculated from observed weights (kilograms) and processing times (seconds). Once fabrication was completed, data were analyzed to determine means and standard errors of percentage yields and processing times for each subprimal. Subprimals cut to only one end point were evaluated for mean foodservice yields and processing times, but no comparisons were made within subprimal. However, those traditionally cut into various end points were additionally compared by cutting style. Subprimals cut by a single cutting style included rib, roast-ready; ribeye roll, lip-on, bone-in; brisket, deckle-off, boneless; top (inside) round; and bottom sirloin butt, flap, boneless. Subprimals cut into multiple end points or styles included ribeye, lip-on; top sirloin, cap; tenderloin butt, defatted; shortloin, short-cut; strip loin, boneless; top sirloin butt, boneless; and tenderloin, full, side muscle on, defatted. Mean yields of portion cuts, and mean fabrication times required to manufacture these cuts differed (P < 0.05) by cutting specification of the final product. In general, as the target portion size of fabricated steaks decreased, the mean number of steaks derived from any given subprimal cut increased, causing total foodservice yield to decrease and total processing time to increase. Therefore, an inverse relationship tended to exist between processing times and foodservice yields. With a method of accurately evaluating various beef purchase options, such as traditional commodity subprimals, closely trimmed subprimals, and pre-cut portion steaks in terms of yield and labor cost, foodservice operators will be better equipped to decide what option is more viable for their operation.     

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.     

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

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

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.     

Online prediction of beef tenderness using a computer vision system equipped with a BeefCam module

Four experiments were conducted in two commercial packing plants to evaluate the effectiveness of a commercial online video image analysis (VIA) system (the Computer Vision System equipped with a BeefCam module [CVS BeefCam]) to predict tenderness of beef steaks using online measurements obtained at chain speeds. Longissimus muscle (LM) samples from the rib (Exp. 1, 2, and 4) or strip loin (Exp. 3) were obtained from each carcass and Warner-Bratzler shear force (WBSF) was measured after 14 d of aging. The CVS BeefCam output variable for LM area, adjusted for carcass weight (cm2/kg), was correlated (P < 0.05) with WBSF values in all experiments. The CVS BeefCam lean color measurements, a* and b*, were effective (P < 0.05) in all experiments for segregating carcasses into groups that produced LM steaks differing in WBSF values. Fat color measurements by CVS BeefCam were usually ineffective for segregating carcasses into groups differing in WBSF values; however, in Exp. 4, fat b* identified a group of carcasses that produced tough LM steaks. Quality grade factors accounted for 3, 18, 21, and 0% of the variation in WBSF among steaks in Exp. 1 (n = 399), 2 (n = 195), 3 (n = 304), and 4 (n = 184), respectively, whereas CVS BeefCam output variables accounted for 17, 30, 19, and 6% of the variation in WBSF among steaks in Exp. 1, 2, 3, and 4, respectively. A multiple linear regression equation developed with data from Exp. 2 accurately classified carcasses in Exp. 1 and 4 and thereby may be useful for decreasing the likelihood that a consumer would encounter a tough (WBSF > 4.5 kg) LM steak in a group classified as "tender" by CVS BeefCam compared with an unsorted population. Online measurements of beef carcasses by use of CVS BeefCam were useful for predicting the tenderness of beef LM steaks, and sorting carcasses using these measurements could aid in producing groups of beef carcasses with more uniform LM steak tenderness.     

Benchmarking carcass characteristics and muscles from commercially identified beef and dairy cull cow carcasses for Warner-Bratzler shear force and sensory attributes

The objective of this study was to benchmark carcasses and muscles from commercially identified fed (animals that were perceived to have been fed an increased plane of nutrition before slaughter) and nonfed cull beef and dairy cows and A-maturity, USDA Select steers, so that the muscles could be identified from cull cow carcasses that may be used to fill a void of intermediately priced beef steaks. Carcass characteristics were measured at 24 h postmortem for 75 carcasses from 5 populations consisting of cull beef cows commercially identified as fed (B-F, n = 15); cull beef cows commercially identified as nonfed (B-NF, n = 15); cull dairy cows commercially identified as fed (D-F, n = 15); cull dairy cows commercially identified as nonfed (D-NF, n = 15); and A-maturity, USDA Select grade steers (SEL, n = 15). Nine muscles were excised from each carcass [m. infraspinatus, m. triceps brachii (lateral and long heads), m. teres major, m. longissimus dorsi (also termed LM), m. psoas major, m. gluteus medius, m. rectus femoris, and m. tensor fasciae latae] and subjected to Warner-Bratzler shear force testing and objective sensory panel evaluation after 14 d of postmortem aging. Carcass characteristics differed (P < 0.05) among the 5 commercially identified slaughter groups for the traits of lean maturity, bone maturity, muscle score, HCW, fat color, subjective lean color, marbling, ribeye area, 12th-rib fat thickness, and preliminary yield grade. Carcasses from commercially identified, fed cull cows exhibited more (P < 0.01) weight in carcass lean than did commercially identified, nonfed cull cows. There was a group x muscle interaction (P = 0.02) for Warner-Bratzler shear force. Warner-Bratzler shear force and sensory overall tenderness values demonstrates that muscles from the SEL group were the most tender (P < 0.01), whereas muscles from the B-NF group were the least tender (P < 0.01). Sensory, beef flavor intensity was similar (P > 0.20) among cull cow carcass groups and more intense (P < 0.01) than the SEL carcass group. Muscles from the SEL group exhibited less (P < 0.01) detectable off-flavor than the cull cow carcass groups, whereas the B-NF group exhibited the most (P < 0.01) detectable off-flavor. Although carcass and muscle quality from commercially identified, fed, cull beef and dairy cows was not similar to A-maturity, USDA Select beef, they did show improvements when compared with nonfed, cull, beef and dairy cow carcasses and muscles.     

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.