Relationship of physically separable lean with chemical lean in pig carcasses

This study was conducted to examine the relationships between 'physically separable lean' (carried out by the Kulmbach reference technique) and 'lean' determined by moisture or lipid analysis (called chemical lean). Five major cuts (ham, shoulder, loin, belly and neck), originating from the Hungarian cross-breed 'Hungahyb', were dissected and the weights recorded. The moisture and lipid contents of three tissue groups (lean, intermuscular fatty tissue and remainder) were determined by common laboratory methods. Adequate estimators (predictors) were then developed for the assessment of standardized or non-standardized lean content in the 'boneless cut' (without skin and subcutaneous fatty tissue). It was shown that the concept of moisture-standardized lean is analogous to that of the fat-standardized one. It appears that unbiased estimators could be obtained if the interdependences between the chemical composition (moisture or lipid content) of the lean, the 'residue' (intermuscular fatty tissue + remainder) and that of the 'boneless cut' are included in the respective equations. If these interdependences are neglected and only the corresponding means are used in these equations, biased estimates have been obtained for the standardized or non-standardized lean content in the 'boneless cut'. Difficulties arising at practical application of these concepts are also discussed in this paper.     

Relationships between chemical composition and physically separated tissues of the pig carcass

Data from the physical and chemical dissection analysis of 50 Large White and 50 Hampshire × Large White carcasses, comprising equal numbers of gilts and castrates, slaughtered at 90 kg liveweight, are presented. The right-hand side of each carcass was dissected into lean, fat and bone and the combined tissues were then minced and chemically analysed for moisture, protein, ether extract and ash. Statistical relationships between the two methods of carcass analysis, except those between bone and ash, were not influenced by sex or breed type. Overall regression equations, i.e. ignoring sex and breed type, for the prediction of percentage lean from moisture, protein and ether extract percentages of the carcasses, had residual standard deviations of 1·26, 1·78 and 1·11, respectively, and corresponding values for the prediction of percentage carcass fat were 1·05, 1·68 and 0·74. Residual standard deviations for predicting percentages of moisture and protein in the carcass from percentage lean content were 1·07 and 0·46 and that for the prediction of percentage ether extract from fat percentage of the carcass was 1·20. Corresponding relationships between bone and ash percentages of the carcass were less satisfactory for predictive purposes.     

Dietary energy and protein effects on partitioning of carcass components in beef cattle

This study evaluated carcass and wholesale cut composition of 20 Angus steers fed two levels of protein (LP = 8% versus HP = 14%) at two levels of energy intake (LE = 1·96 versus HE = 2·67 Mcal ME) at 6·35 kg head⁻¹ d⁻¹ dry matter intake for 238 d using a factorial arrangement (n = 5/diet). The left side of each carcass was physically separated into wholesale cuts and each cut was, in turn, physically separated into the lean, subcutaneous fat, intermuscular fat, bone portions and cavity fat when applicable. Intramuscular fat for the entire side was chemically determined using only the separated lean tissue component. Energy was the greatest source of variation (P < 0·05) on carcass and wholesale cut composition: HE was associated with more total carcass fat (32·4 versus 23·9%) and less lean (56·7 versus 60·2%) and bone (17·9 versus 20·1%) than LE. Protein by energy level interactions (P < 0·05) were observed for carcass subcutaneous fat and carcass lean in addition to brisket subcutaneous fat, round subcutaneous fat and bone. The HP:HE group had the least carcass lean and the most subcutaneous fat followed by the LP:HE group, LP:LE and then HP:LE. This was also the trend for the wholesale cut composition. These results suggest that fat deposition in cattle can be significantly and favorably reduced in wholesale cuts by adjusting the relative balance of dietary protein and energy.     

The accuracy of predicting carcass composition of three different pig genetic lines by dual-energy X-ray absorptiometry

The accuracy of dual energy X-ray absorptiometry (DXA) for predicting carcass composition was evaluated by applying this technology to 95 half-carcasses of gilts from three genetic lines of widely varying composition. The DXA measurements of total weight, fat and lean masses and bone mineral content were used to predict the dissected lean, fat, bone and weight of the major primal cuts and the overall carcass. The study showed that it is not necessary to correct, or rather adjust, the prediction equations between genetic lines, given the small decrease in the prediction error (less than 1.43%). Except for the prediction for loin bone weight, the results showed that incorporating more than one of the predictive variables derived from DXA or from direct carcass measurements into the regression models was not justified in terms of prediction accuracy. The best predictions were those for half-carcass weight and primal cut weights (R² > 0.95). The prediction of dissected lean ranked second in accuracy (R² > 0.85), with the exception of the belly. The equations using DXA measurements provide good estimation (R² > 0.70) of the weight of fat in the carcass and primal cuts. However, DXA showed moderate accuracy (R² < 0.66) in predicting bone weight, although greater accuracy was attained for loin bone weight using a two-variable prediction model.     

Cull sow knife-separable lean content evaluation at harvest and lean mass content prediction equation development

The objectives of this study were to develop a prediction equation for carcass knife-separable lean within and across USDA cull sow market weight classes (MWC) and to determine carcass and individual primal cut knife separable lean content from cull sows. There were significant percent lean and fat differences in the primal cuts across USDA MWC. The two lighter USDA MWC had a greater percent carcass lean and lower percent fat compared to the two heavier MWC. In general, hot carcass weight explained the majority of carcass lean variation. Additionally, backfat was a significant variation source when predicting cull sow carcass lean. The findings support using a single lean prediction equation across MWC to assist processors when making cull sow purchasing decisions and determine the mix of animals from various USDA MWC that will meet their needs when making pork products with defined lean:fat content.     

An exploratory observational study to develop an improved method for quantifying beef carcass salable meat yield

Eighty-seven grain-finished steers were harvested, evaluated, and fabricated into wholesale cuts to determine what measured composition indicators most accurately describe the percentage of closely trimmed salable meat yield. Indicators of lean and fat composition present at the cross-section between the 12th and 13th ribs were objectively evaluated using Assess image analysis software. Salable meat yield ranged from 50.18% to 72.92%, trimmable fat yield ranged from 12.87% to 36.69%, and bone yield ranged from 10.07% to 19.21%. Regression models were developed to estimate percentage of total salable meat yield. Composition indicators chosen to predict salable meat yield included hot carcass weight (HCW), perinephric fat weight, longissimus muscle area (LMA), subcutaneous fat thickness (SFT), ratio of LMA to subcutaneous fat area, and ratio of subcutaneous fat depth to HCW. These results indicate that prediction of beef carcass salable meat yield can be improved via modification to current measures used in the USDA yield grade equation and addition of new measures.     

Estimation of Canadian and European lean yields and composition of pig carcasses by dual-energy X-ray absorptiometry

Dual-energy X-ray absorptiometry (DEXA) was used on 110 pig carcasses to estimate fat, lean, bone mineral content and total tissue masses of the major primal cuts and overall carcasses. The DEXA estimations were compared and used to predict the dissected lean, fat (including skin), bone and weight of primal cuts and carcasses, as well as to predict the Canadian and the European lean yields. The best relationships were obtained when predicting the weight of ham (R(2)=0.99), loin (R(2)=0.99), shoulder (R(2)=0.96), belly (R(2)=0.93), half carcass (R(2)=0.98), ham lean (R(2)=0.89), loin lean (R(2)=0.89), shoulder lean (R(2)=0.87), and the meat weight used in the estimation of the Canadian (R(2)=0.92) and the European lean yield (R(2)=0.82). While the weight of fat in the carcass and primal cuts was accurately estimated by DEXA (R(2)>0.72), DEXA carcass composition estimations were less accurate when predicting dissected bone weights (R(2)<0.54).     

Prediction of body composition of Iberian pigs by means bioelectrical impedance

Twelve barrow Iberian pigs with an average weight at slaughter of 109.2kg were used to evaluate bioelectrical impedance procedures to predict the body composition of live pigs. Twelve hours before slaughter pigs were weighed, and a four-terminal body composition analyser (Model BIA-101, RJL Systems, Detroit, MI) was utilized to determine resistance (R(s) in Ω) and reactance (X(c) in Ω). The length values (L in cm) were measured between detector electrodes with a flexible steel tape. Twenty four hours after slaughter the left side of each carcass was separated using a scalpel into fat, lean, bone and skin. Multiple regression equations for estimating lean, fat, bone and skin amounts and lean, fat, bone and skin proportions with respect to slaughter weight were calculated. The live weight (LW) and L independent variables predicted 85.3% and 64.3% of the variability of the lean amount and lean proportion, respectively. The LW, X(c) and L variables accounted for 96% and 91.6% of the variation in fat quantity and fat proportion, respectively. The LW and R(s) accounted for 58.9% of the variation in bone amount, and the same variables predict 79.1% of the variability of bone percentage. The R(s) and L variables explained 68% of the variability of skin quantity and LW, R(s) and X(c) predicted 83.1% of the variation of skin proportion. Results from this experiment indicate that bioelectrical impedance may be of interest for body composition prediction of live Iberian pigs.     

北京地区三元杂交猪胴体的分级优化

为了提高猪胴体分级的准确性,利用计算机视觉技术、图像处理技术及统计分析方法,对已建立的猪胴体分级标准及预测方程进行修订.结果表明:以左半胴体质量、臀中肌横长和臀中肌膘厚预测瘦肉率绝对误差小于4%;同时以瘦肉率、臀中肌膘厚、1/2横长处膘厚及6~7肋处膘厚等特征作为分级主要参数,使分级准确率达90%.将各处膘厚与瘦肉率相结合,并对猪胴体级别根据实际需求进行调整,可使分级工作更加合理,准确性也有提高.     

The use of ultrasound to predict the carcass composition of live Akkaraman lambs

The aim of this study was to measure fat thickness, area and depth of the longissimus dorsi muscle using ultrasonography, to estimate carcass composition in live Akkaraman lambs. Fat thickness, area and depth of the longissimus dorsi muscle between the 12th and 13th ribs were measured in vivo and on the carcass after slaughter, using real time ultrasound in 40 Akkaraman lambs. To estimate the carcass composition, one-half of a carcass was dissected into muscle, fat and bone after slaughter. Overall, correlation coefficients between ultrasound and carcass longissimus dorsi muscle area, depth and fat thickness were 0.82, 0.60 and 0.77, respectively. Estimates of carcass composition for Akkaraman lambs based on LW explained 78%, 82%, 74%, 52%, 75%, 36% and 72% of the variations for muscle, total carcass fat, subcutaneous fat, inter-muscular fat, non-carcass fat, tail fat and bone, respectively. The introduction of UFT, ULMA and ULMD as independent variables in addition to LW in the multiple linear regression equations further improved the variations for total muscle (80%), carcass fat (84%) and bone weight (76%) whereas no improvement was observed for subcutaneous, intermuscular, non-carcass and tail fat. The results showed that in vivo ultrasound fat thickness and measurement of area and depth of the longissimus dorsi muscle in association with live weight could be used to estimate muscle, total body fat and bone weight in Akkaraman lambs.     

The use of seemingly unrelated regression to predict the carcass composition of lambs

The aim of this study was to develop and evaluate models for predicting the carcass composition of lambs. Forty male lambs were slaughtered and their carcasses were cooled for 24 hours. The subcutaneous fat thickness was measured between the 12th and 13th rib and breast bone tissue thickness was taken in the middle of the second sternebrae. Left side of carcasses was dissected and the proportions of lean meat (LMP), subcutaneous fat (SFP), intermuscular fat (IFP), kidney and knob channel fat (KCFP), and bone plus remainder (BP) were obtained. Models were fitted using the seemingly unrelated regression (SUR) estimator which is novel in this area, and compared to ordinary least squares (OLS) estimates. Models were validated using the PRESS statistic. Our results showed that SUR estimator performed better in predicting LMP and IFP than the OLS estimator. Although objective carcass classification systems could be improved by using the SUR estimator, it has never been used before for predicting carcass composition.     

The use of seemingly unrelated regression to predict the carcass composition of lambs

The aim of this study was to develop and evaluate models for predicting the carcass composition of lambs. Forty male lambs were slaughtered and their carcasses were cooled for 24 hours. The subcutaneous fat thickness was measured between the 12th and 13th rib and breast bone tissue thickness was taken in the middle of the second sternebrae. Left side of carcasses was dissected and the proportions of lean meat (LMP), subcutaneous fat (SFP), intermuscular fat (IFP), kidney and knob channel fat (KCFP), and bone plus remainder (BP) were obtained. Models were fitted using the seemingly unrelated regression (SUR) estimator which is novel in this area, and compared to ordinary least squares (OLS) estimates. Models were validated using the PRESS statistic. Our results showed that SUR estimator performed better in predicting LMP and IFP than the OLS estimator. Although objective carcass classification systems could be improved by using the SUR estimator, it has never been used before for predicting carcass composition.     

Dual X-ray absorptiometry accurately predicts carcass composition from live sheep and chemical composition of live and dead sheep

Fifty merino wethers (liveweight range from 44 to 81kg, average of 58.6kg) were lot fed for 42d and scanned through a dual X-ray absorptiometry (DXA) as both a live animal and whole carcass (carcass weight range from 15 to 32kg, average of 22.9kg) producing measures of total tissue, lean, fat and bone content. The carcasses were subsequently boned out into saleable cuts and the weights and yield of boned out muscle, fat and bone recorded. The relationship between chemical lean (protein+water) was highly correlated with DXA carcass lean (r(2)=0.90, RSD=0.674kg) and moderately with DXA live lean (r(2)=0.72, RSD=1.05kg). The relationship between the chemical fat was moderately correlated with DXA carcass fat (r(2)=0.86, RSD=0.42kg) and DXA live fat (r(2)=0.70, RSD=0.71kg). DXA carcass and live animal bone was not well correlated with chemical ash (both r(2)=0.38, RSD=0.3). DXA carcass lean was moderately well predicted from DXA live lean with the inclusion of bodyweight in the regression (r(2)=0.82, RSD=0.87kg). DXA carcass fat was well predicted from DXA live fat (r(2)=0.86, RSD=0.54kg). DXA carcass lean and DXA carcass fat with the inclusion of carcass weight in the regression significantly predicted boned out muscle (r(2)=0.97, RSD=0.32kg) and fat weight, respectively (r(2)=0.92, RSD=0.34kg). The use of DXA live lean and DXA live fat with the inclusion of bodyweight to predict boned out muscle (r(2)=0.83, RSD=0.75kg) and fat (r(2)=0.86, RSD=0.46kg) weight, respectively, was moderate. The use of DXA carcass and live lean and fat to predict boned out muscle and fat yield was not correlated as weight. The future for the DXA will exist in the determination of body composition in live animals and carcasses in research experiments but there is potential for the DXA to be used as an online carcass grading system.     

USDA yield grades and various carcass traits as predictors of carcass composition

Twenty-five carcasses from each of three breedtypes (Brahman, Angus and Brahman × Angus) were physically separated into fat, lean and bone. Several muscles from the round and the femur were used to derive equations to predict carcass composition and muscle-to-bone ratio. The femur (as a percentage of the carcass) was shown to predict percentage carcass bone with 90% accuracy. All of the muscles studied were highly related to total carcass lean but the percentage of carcass as M. biceps femoris was the best single muscle indicator of carcass lean of the muscles studied. More variation in carcass lean could be accounted for by a multiple regression equation, involving all four muscles studied, than by any single muscle. M. biceps femoris-to-femur ratio was found to predict carcass muscle-to-bone ratio with a high degree of accuracy. The USDA yield grades were found to be reliable indicators of carcass composition. A two-variable equation involving adjusted fat thickness and biceps femoris accounted for 88·6% of the variation (RSD = 1/·64) in percentage of carcass as separable lean.     

Pork carcass grading: A comparison of the New Zealand Hennessy Grading Probe and the Danish Fat-O-Meater

The left sides from 224 pork carcasses were probed for fat thickness and muscle depth at four locations (last rib, and between the third and fourth, fourth and fifth, and fifth and sixth ribs posterior to the last rib) and at three positions (5, 7 and 9 cm off the dorsal mid-line) using the Hennessy Grading Probe (GP) and the Fat-O-Meater (FOM). In addition, fat thickness was recorded at the loin (8 cm off the dorsal mid-line) using both instruments, and the caliper of the FOM was used to measure fat thickness at three positions over the medial face of the M. gluteus medius on the dorsal mid-line of the carcass. All pork sides were cut into five North American primals which were subsequently separated into fat, bone and lean to define percentage lean yield. The range in warm carcass weight and percentage lean yield varied from 58·5 to 94·5 kg and from 29·60 to 48·91%, respectively. The two probes differed little in precision for the prediction of percentage lean yield. Measurements taken with the GP and FOM between the third and fourth, and fourth and fifth last ribs gave the lowest residual errors. Position of measurements (5, 7 or 9 cm) had little effect on the relationship between lean yield and fat thickness or fat thickness and muscle depth. Addition of a second measurement fat thickness or muscle depth, provided only minor improvement in precision for the prediction of percentage lean yield over that of a single fat thickness measurement. The results suggest that, for grading systems using percentage lean yield as a basis, both the GP and FOM would provide similar precision, and that the choice of an instrument would then depend more on its durability and performance under commercial conditions.     

Prediction of carcass composition by impedance spectroscopy in lambs of similar weight

Previous research on impedance measurements for the prediction of carcass composition was predominantly carried out on animals that varied widely in body weight, breed, or sex. The high accuracy for the estimated lean or fat mass was mainly obtained by including the body weight in the regression equations. The objective of this study was the prediction of carcass composition in lambs of similar weight. We used 70 male German Merino Mutton lambs and 70 male German Blackheaded Mutton lambs with 35 and 45kg live weight each. Impedance measurements with different electrode placements were carried out in vivo and on carcasses 20min and 24h postmortem. The carcass composition was ascertained by dissection of the left carcass side into lean, fat, and bone. R(2)-values for prediction of lean mass by impedance and body weight ranged between 0.11 and 0.71 within breeds and weight groups and between 0.84 and 0.89in the total material. Lean percentage was estimated with R(2)=0.18-0.48 within breeds and weight groups. The corresponding values for the total material varied from 0.23 to 0.37. We conclude that the impedance method is not suitable for the prediction of lean or fat percentage, neither in lambs of similar weight nor in heterogeneous animals.     

Electromagnetic scanning to estimate carcass lean content of Taiwan native broilers

To estimate lean content of Taiwan native broiler carcasses accurately, objectively and rapidly, electrical conductivity measurements of broiler carcasses and other relative factors (carcass weight, length and temperature) were used in multiple linear regression analysis for lean prediction. Forty native broiler carcasses, with average market weight 2477.5±465.5 g, were scanned through a 10 MHz electromagnetic field created by an electromagnetic scanner (SA-3203) to measure the total body electrical conductivity (TOBEC) index. After scanning, each broiler carcass was separated into wing, breast, leg and back. Each primal cut was dissected into lean, fat and bone. The weight, length, temperature and TOBEC index of broiler carcass were significantly correlated with lean weight of broiler carcass (P<0.001). Regression analysis for lean estimation with carcass weight, length, temperature and TOBEC index showed higher coefficient of determination (R(2)=0.968) and lower coefficient of variation (CV=4.178) with an equation using beheaded carcass weight, temperature and TOBEC index as variables.     

The estimation of sheep carcass composition from fat and muscle thickness measurements taken by probes

Three trials, involving a total of 290 lambs, were carried out to examine the precision of probed fat and muscle measurements for estimating carcass composition in classification and grading schemes. The measurement positions and probes were not always the same in different trials but common measurements provided the basis for comparison between trials. Residual standard deviations (sd) for the prediction of carcass lean percentage averaged over trials are referred to in this Summary. Residual standard deviation for prediction from carcass weight was 3·5. The visual fat assessment currently used in the national Sheep Carcase Classification Scheme, operated by MLC, contributed significantly to the prediction (residual standard deviation = 3·0) but was less precise than a visual assessment of carcass subcutaneous fat content to the nearest percentage unit (SF(e)) (residual standard deviation = 2·6). Fat thickness measurements taken over the M. longissimus at the 12th rib with the Danish optical probe, a simple steel rule or the pig version of the Hennessy Grading Probe (HGP), showed similar precision to the classification fat class. An M. longissimus thickness measurement taken by the HGP did not add significantly to the precision. Probe fat measurements added significantly to the precision achieved with visual fat assessments (residual standard deviation with classification fat class = 2·8; residual standard deviation with SF(e) = 2·5). There would be advantages, therefore, in using both a visual fatness assessment and fat measurements in classification.     

Validation of the EUROP system for lamb classification in Norway; repeatability and accuracy of visual assessment and prediction of lamb carcass composition

The EUROP classification system is based on visual assessment of carcass conformation and fatness. The first objective was to test the EUROP classification repeatability and accuracy of the national senior assessors of the system in Norway. The second objective was to test the accuracy of the trained and certified abattoir EUROP classifiers in Norway relative to EU Commission's supervising assessors. The third and final objective was to test the accuracy of the EUROP classification system, as assessed by the National senior assessors, for prediction of lean meat, fat and bone percentage and lean meat in relation to bone ratio. The results showed that the repeatability and accuracy of the national senior assessors was good, achieving high correlations both for conformation and fatness. For the abattoir assessors, there were some systematic differences compared to EU Commission's assessors, but these differences were within limits accepted by EU Commission. The relationship between abattoir and national senior assessors was good, with only small systematic differences. This may suggest that there also is a systematic difference between the national senior assessors of the system and EU Commission's assessors. The EUROP system predicted lean meat percentage poorly (R(2)=0.407), with a prediction error for 3.027% lean. For fat and bone percentage, the results showed a fairly good prediction of fat percentage, but poorer for bone percentage, R(2)=0.796 and R(2)=0.450, respectively. The prediction error for fat and bone percentage was 2.300% and 2.125%, respectively. Lean: bone ratio was predicted poorly (R(2)=0.212), with a prediction error of 0.363 lean: bone ratio.