Estimation Of Carcass Composition Research Articles

Linear and nonlinear models for assessing carcass composition using dual X-ray absorptiometry in egg- and meat-type chickens

The objective of this study was to develop appropriate correction equations for dual energy X-ray absorptiometry (DXA) for total carcass composition of live meat- and egg-type chickens. Linear (bivariate linear and multivariate linear) and nonlinear (polynomial, multivariate polynomial, broken-line and Gompertz) equations were used to estimate carcass composition of DXA-scanned birds based on chemical proximate analysis. A total of 288 laying females (10-30 wk of age) and 305 broiler breeder females (4-32 wk of age) were used. The same birds scanned by DXA were dissected and utilized for whole-body proximate chemical analysis for body lean, fat, and mineral content (ash). As indicators of carcass fat and lean, abdominal fat pad and breast muscle weights were also recorded. Models were evaluated using root mean square error (RMSE), Bayesian Information Criterion (BIC), coefficient of determination (R2), Durbin Watson test for autocorrelation (DW), and residuals observation (RES). Model estimations were done separately by strain or combined. Estimations of composition responses fit at least 1 of each linear and nonlinear models for the egg- and meat-type chickens on all parameters estimated (P < 0.05). In the egg-type chickens, multivariate linear regression was the best fit for body lean with the lowest RMSE and BIC, and highest R2 whereas body fat, body ash, and breast muscle were best predicted by the multivariate polynomial model. In the meat-type chickens, body lean was best predicted by the multivariate linear model with the lowest RMSE and BIC, and the highest R2 whereas the multivariate polynomial was the most parsimonious model for body fat, body ash, and abdominal fat. Positive autocorrelations were observed in several models tested for body fat, body ash, breast muscle, and abdominal fat pad when both strains were analyzed combined (P < 0.05). In summary, a strain-based correction is recommended to all the parameters, with exception of the BW estimation. Correction equations developed in this study demonstrated that the DXA technique is a reliable alternative to proximate chemical analysis in egg- and meat-type chickens.

602 The impact of time on feed and partial replacement of high-moisture corn with a high-lipid high-fiber pellet on steer performance, visceral organ weight, fat deposition, and carcass composition

The objective of this experiment was to determine the impact of time on feed and the partial replacement of starch with a high-fat, high-fiber by-product based pellet. Angus crossbred steers (n = 97; initial BW 469.3 ± 45.8 kg) were randomly assigned to one of two isocaloric dietary treatments: control (CON; n = 48) steers were fed a finishing diet consisting of 10% haylage, 77% high-moisture corn, 11% soybean meal, and 2% of a salt, vitamin, and mineral pre-mix including monensin; or high-fat, high-fiber pellet (HLHF; n = 49). The HFHF contained 29.8% wheat shorts, 26.2% corn DDGS, 18.8% soy hulls, 19.2% corn gain, and 6% tallow and replaced 30% (DM basis) of the high moisture corn in CON. Steers were randomly assigned to pens equipped with Insentec feeders to record individual feed intake. Steers were randomly split into two blocks in order to facilitate sample collection at the abattoir. On d 1 of the feeding period and every 6 wk thereafter, 10 steers from each treatment were selected at random and slaughtered. Organ and visceral fat weights were recorded, and rib sections were cut into muscle, fat, and bone in order to estimate carcass composition. Data were analyzed as a randomized complete block using PROC MIXED in SAS and included the fixed effects of diet, time on feed, and random effects of pen and block. Contrasts between diet and linear effects of time on fed were used for mean separation and significance was declared at P ≤ 0.05. Steer initial BW did not differ (P ≥ 0.43); however, final BW increased linearly (P < 0.001), but did not differ with dietary treatment (P = 0.55). Overall ADG did no differ with dietary treatment (P = 0.63), but decreased linearly with increasing time on feed (P = 0.015). Empty rumen mass was 12.4 and 11.4 ± 0.24 for CON and HLHF (P = 0.004). Abomasum weight tended to be heavier for HLHF than CON steers (P = 0.06). Carcass traits did not differ with dietary treatment (P > 0.51). Rib dissection indicated that rib section weights of lean, bone, intermuscular, body and subcutaneous fat did not differ with dietary treatment (P ≥ 0.24). Overall these data indicate that partially replacing starch with a high-lipid, high-fiber pellet had limited impacts on growth performance and carcass traits and energy partitioning in steers.

Dual Energy X-Ray Absorptiometry as a Rapid and Non-Destructive Method for Determination of Lean, Fat and Bone Content in Livestock

ObjectivesTo implement dual energy X-ray absorptiometry (DXA) as a platform technology, calibrations and development of robust equations to attain precision and accuracy are required before using for routine predictions of carcass yields in livestock. This manuscript summarized results of ongoing research where DXA has been used to estimate lean, fat, and bone carcass composition in beef, pork and lamb.Materials and MethodsFrom a wide range of carcasses, a total of 334 beef (230 crossbred finished steers and 104 cows), 212 pork and 155 lamb carcasses were used to build calibration equations within each population. Left carcass sides were scanned with a Lunar iDXA unit and then dissected into lean, fat, and bone and weighed. Partial least square regression was used to carry out the prediction equations for lean, fat and bone values from primal cuts scans (independent) and actual lean, fat and bone obtained through the full dissection (dependent). The predictive ability of the models was evaluated in terms of coefficient of determination (R2) and root mean square error of calibration (RMSE).ResultsThe PLSR results between actual and DXA estimated lean and fat values showed high relationship (R2 > 0.97) across all the species. Within beef, the present results suggest that DXA capacity to estimate carcass composition is independent of maturity. With regard to the bone predictions, PLSR analyses also improved the relationship for bone predictions compared to simple regression models previously developed at this institution or single pass scans for pork and lamb. Observed R2 values for predicting bone were slightly lower than those for lean and fat estimations, particularly in those carcasses with smaller bone sizes such as pork (R2 = 0.889) and lamb (R2 = 0.870).ConclusionThe results suggest that DXA technology can reliably estimate carcass composition in livestock, particularly for lean and fat estimations. Using PLSR analyses, suitable models for research have been developed from main primal scan data. However, further studies to externally validate the prediction accuracy and to obtain calibration curves for specific retail cuts or carcass cut-outs specifications are needed. Prediction accuracies for industry applications using single pass scans will also be needed.

Prediction of carcass composition by ultrasonic measurement and the effect of region and age on ultrasonic measurements

This study aimed to determine the relationship between age characteristics and sheep carcass composition with real time ultrasound. Data was collected from 34 Karayaka ewes and 20 female lambs. Skin and subcutaneous fat thickness, and muscle area, depth and width, were measured between the 12th and 13th thoracic vertebrae and 3rd and 4th lumbar vertebrae. The twenty female lambs were slaughtered to determine the muscle, bone and fat amount in their carcasses. The ultrasound measurements from the two regions were not significantly different (P>0.05). It was also determined with ultrasound that the age of the animal had an effect on subcutaneous fat thickness and skin thickness (P<0.05). In addition, there was a significant positive correlation among the ultrasound measurements in both regions with the carcass measured by dissection, and live weight. The coefficients of determination (R2) ranged from 0.76 to 0.99 in the multiple regression models for carcass composition using ultrasound. In conclusion, the present study suggests that the use of ultrasound skin thickness and muscle area and depth measurements, coupled with live weight, can be used to estimate carcass composition.

Estimation of carcass composition and cut composition from computed tomography images of live growing pigs of different genotypes

The aim of the present work was (1) to study the relationship between cross-sectional computed tomography (CT) images obtained in live growing pigs of different genotypes and dissection measurements and (2) to estimate carcass composition and cut composition from CT measurements. Sixty gilts from three genotypes (Duroc×(Landrace×Large White), Pietrain×(Landrace×Large White), and Landrace×Large White) were CT scanned and slaughtered at 30 kg (n=15), 70 kg (n=15), 100 kg (n=12) or 120 kg (n=18). Carcasses were cut and the four main cuts were dissected. The distribution of density volumes on the Hounsfield scale (HU) were obtained from CT images and classified into fat (HU between −149 and −1), muscle (HU between 0 and 140) or bone (HU between 141 and 1400). Moreover, physical measurements were obtained on an image of the loin and an image of the ham. Four different regression approaches were studied to predict carcass and cut composition: linear regression, quadratic regression and allometric equations using volumes as predictors, and linear regression using volumes and physical measurements as predictors. Results show that measurements from whole animal taken in vivo with CT allow accurate estimation of carcass and cut composition. The prediction accuracy varied across genotypes, BW and variable to be predicted. In general, linear models, allometric models and linear models, which included also physical measurements at the loin and the ham, produced the lowest prediction errors.

Estimation of carcass composition using rib dissection of calf-fed Holstein steers supplemented with zilpaterol hydrochloride

Estimation of carcass composition using rib dissection of calf-fed Holstein steers supplemented with zilpaterol hydrochloride

Intake, digestibility, performance, and carcass traits of beef cattle of different gender

The performance, intake, feed efficiency, and carcass traits of beef cattle from different gender profile were assessed. Fifteen animals (five steers, five spayed heifers, and five intact heifers) with ±250 kg of initial body weight were randomly assigned in individual pens and fed the same diet for 106 days. At the end of the trial, all the animals were slaughtered and the pH, temperature, and weight of the carcass were recorded. The right side of each carcass was then separated into chuck, shoulder, flank sirloin, and round for evaluation of commercial cuts yield. The left carcass sides were ribbed between the 12th and 13th ribs where the rib eye area and fat thickness measurements were taken. The 9th-11th rib section was removed from the left half carcass and then dissected into muscle, fat, and bones in order to estimate carcass composition. Gender had no effect (P > 0.05) on performance, intake, digestibility of dry matter and all the nutrients evaluated, feed efficiency, and carcass characteristics. It can be concluded that steers and heifers (spayed or not) have the same potential to produce beef. From a productive and welfare standpoint, there is no reason to spay heifers.

Estimation of carcass composition by ultrasound measurements in 4 anatomical locations of 3 commercial categories of lamb1

The objectives were to study the relationship between in vivo ultrasound measurements and cold carcass measurements at 4 anatomical points along the backbone of lambs and to determine appropriate regression equations to estimate carcass composition by using ultrasonic measurements at each anatomical point. The lambs (n = 114) used were suckling lambs (BW = 11.09 kg), light lambs (BW = 22.43 kg), and wethers (BW = 32.03 kg), representing a wide range of BW. Measurements of subcutaneous fat and skin thickness and of muscle depth and muscle width were taken over the 10th to 11th and 12th to 13th thoracic vertebrae and over the first to second and third to fourth lumbar vertebrae. These measurements were taken at one-third of the musculus longissimus thoracis et lumborum (LMT) width with the probe perpendicular to the backbone. The left sides of the carcasses were dissected into muscle, fat, and bone. The weight of lean tissue increased (P < 0.001) at a rate of approximately 500 g for each kilogram of carcass weight increase. Pelvic fat weight increased (P < 0.001) slightly with increasing carcass weight (11.8 g), whereas kidney fat and subcutaneous fat showed great gains (P < 0.001; 40.3 and 134.4 g, respectively). Ultrasound LMT width of light lambs remained constant along the backbone, whereas LMT width of suckling lambs and wethers increased (P < 0.001) from the cranial to the caudal direction. Ultrasound LMT depth and fat thickness between the 10th and 11th thoracic vertebrae were greater (P < 0.01) than measurements taken at other backbone locations. The greatest difference between ultrasound and carcass measurements was in LMT width, with differences between ultrasound and carcass measurements always being greater in LMT depth than in fat thickness. Carcass LMT width was more closely correlated with carcass lean than with other tissues, especially at both thoracic locations (r = 0.80 and r = 0.71). In general, skin thickness measured by ultrasound was poorly correlated (from r = 0.19 to r = 0.33) with all carcass tissues because of slight variations in skin thickness. Ultrasound LMT depth was more closely correlated with carcass tissues than was carcass LMT depth (from r = 0.53 for bone to r = 0.71 for lean), whereas ultrasound fat depth and carcass fat depth presented similar correlations (from r = 0.49 for bone to r = 0.72 for intermuscular fat). Regression coefficients for predicting lean were 0.95 to 0.96, for predicting subcutaneous fat were 0.67 to 0.75, for predicting intermuscular fat were 0.81 to 0.84, and for predicting bone were 0.78 to 0.88. This study was not conclusive regarding predicting carcass composition in relation to an optimal anatomical position, given that all the anatomical locations studied allowed accurate regression equations. Body weight was the most important predictor of carcass composition, with a slight improvement in regression equations when using ultrasound. However, ultrasound muscle and fat depths were correlated with carcass muscle and fat depths and with the tissular composition of carcass.

Estimation of light lamb carcass composition by in vivo real-time ultrasonography at four anatomical locations1

The objectives of this study were to study the relationship between in vivo ultrasound measurements and cold carcass measurements at 4 anatomical points of the backbone, and to establish regression equations to estimate carcass composition within the cold carcass weight range for Ternasco lambs (8 to 12.5 kg) by using ultrasonic measurements taken at a single location. Measurements of subcutaneous fat and skin thickness and of muscle depth and width were taken over the 10th to 11th and 12th to 13th thoracic vertebrae and the 1st to 2nd and 3rd to 4th lumbar vertebrae. These measurements were taken at 2 and 4 cm from the nearest end of the LM to the backbone and at 1/3 of the LM width with the probe perpendicular to and parallel to the backbone. The left sides of the carcasses were dissected into muscle, fat, and bone. Body weight (22.6 kg) and cold carcass weight (10.8 kg) were representative of Ternasco light lambs. Muscle depth measured at 2 cm, 4 cm, and 1/3 of LM width remained regular, with slight ups and downs along the spine. All the pairs of in vivo ultrasound and cold carcass measurements were significantly different (P<0.05) and had small correlations. All the ultrasound measurements of muscle depth at any location or at any distance to the backbone were less than their equivalent cold carcass measurements, with differences ranging from 0.8 to 5.9 mm. Differences between ultrasound fat thickness + interface (US_FDGI) and cold carcass fat thickness were less than differences between ultrasound fat thickness and cold carcass fat thickness, ranging from -0.9 to -1.0 mm for the former and from -2.1 to -0.5 mm for the latter. The small differences in absolute values between US_FDGI and cold carcass fat thickness suggest that US_FDGI is the best measure of the real fatness level of the lambs. The best prediction equations for muscle, bone, and fat were developed with in vivo ultrasound data measured at the 1st to 2nd lumbar vertebrae perpendicularly to the backbone, but they had limited predictive value. To predict the muscle content of carcass, BW and muscle depth were included, and they explained 59% of variation. Fifty-one percent of total fat was predicted by BW and fat thickness, whereas only 17% of the variation in bone was predicted by 2 fat-related variables. The BW of lambs was an important predictor to improve regression equations but ultrasound measurements were the most important variables when a narrow range of BW was used.

The value of in vivo real time ultrasonography in assessing loin muscularity and carcass composition of rabbits

Sixty nine growing rabbits were scanned over the lumbar region using a real time ultrasonography (RTU) machine to estimate loin muscularity and carcass composition. Longissimus thoracis et lumborum muscle (LM) depth, width and area were taken. Animals were weighed (LW), slaughtered and carcass composition was determined. Equivalent measurements to those taken by RTU in vivo were taken on the carcass and muscularity indices were calculated on carcass and in vivo. Simple correlations between the two types of measurements were determined and carcass composition was estimated by simple and multiple regressions. The LW varied from 1200 to 3410 g. The simple correlations between carcass and in vivo RTU LM measurements were high ( P < 0.001) and the LM area was the trait with the highest correlation ( r = 0.92). Simple correlations between muscularity indices measured by RTU and in carcass were significant ( P < 0.001). In vivo RTU measurements explained a large amount of the variation of the carcass meat weight (MW) and bone weight ( r 2 range from 0.49 to 0.77; P < 0.001). Using multiple regression equations to estimate carcass composition, the best fit was obtained with the LW and one or more in vivo RTU measurement. The LW explained 90.6% of the variation of MW in the carcass. In vivo RTU is able to estimate loin muscularity and carcass composition of rabbits with accuracy. The usefulness of in vivo RTU and LW to predict carcass composition of rabbits using multiple regressions was also shown.

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.

Evaluation of Video Image Analysis (VIA) technology to predict meat yield of sheep carcasses online under abattoir conditions

Accurate estimates of carcass composition and eating quality are critical to the introduction and the success of a value-based marketing system (VBMS) and to help address increased consumer demands for leaner meat with higher quality. Currently in the UK, carcass composition is assessed by a subjective carcass classification system based on the EUROP conformation system, and a visual assessment of fat cover using a numeric fat score (“MLC Scoring”) (Anderson, 2003). Objective, image analysis based systems to classify carcasses into current classification categories have been studied (Allen and Finnery, 2000) and are in use in the beef industry in the EU. However, the introduction of automatic technologies such as VIA may also have considerable potential for prediction of lean meat yield of the carcass. There is growing interest in the possibility of developing payment criteria which are based on carcass meat yield. Therefore, the present research project investigated the potential of VIA technology to predict meat yield in terms of saleable meat yield (SMY), saleable primal meat yield (SPMY) and the carcass components leg, chump, loin and shoulder in lamb.

Sheep carcass composition estimated from Longissimus thoracis et lumborum muscle volume measured by in vivo real-time ultrasonography

The use of Longissimus thoracis et lumborum muscle (LM) volume measured in vivo by real-time ultrasonography (RTU) to estimate carcass composition was evaluated in 47 female sheep. Animals were scanned over six sites (7th, 9th, 11th and 13th thoracic vertebrae and 2nd and 4th lumbar vertebrae). After slaughter carcass weight (CW) and composition by dissection were determined. RTU volume measurements were calculated by multiplying the LM area at each site by the vertebra lengths. Equivalent measurements to those taken in vivo were obtained on the carcass using a digital camera and image analysis. The correlation between LM volume measured by RTU and in the carcass was high for all scans. LM volume was better in predicting carcass muscle than carcass fat. Lower determination coefficients were obtained between LM volume and carcass tissues expressed in % of CW. The best estimates of carcass tissues weights and proportions were obtained using the LM volume between the 2nd and the 4th lumbar vertebrae for all tissues. Multiple regression equations were fitted using live weight (LW) and LM volume to predict carcass composition. For all tissues, the best fit was obtained with two, three or four independent variables and the stepwise procedure was consistent in selecting LW to establish the prediction equations. Weights and proportions of muscle, subcutaneous fat, intermuscular fat and total fat were accurately predicted. These results indicate that Longissimus thoracis et lumborum muscle volume measured in vivo by RTU can be used to predict sheep carcass composition (muscle and fat).

An evaluation of methods used to estimate carcass composition of common eiders Somateria mollissima

Abstract To examine how endogenous reserves may influence avian life history, it is often necessary to quantify carcass composition. However, proximate analyses are expensive, time-consuming and difficult to perform under field conditions. Consequently, carcass composition is often estimated from easily measured data. We evaluate methods of estimating carcass composition of the common eider duck Somateria mollissima. We measured, dissected and completed proximate analyses of 92 eiders. Predictive models were derived using multiple regressions of 70 birds, while the remaining 22 were used as an independent test of the models. Each model's accuracy was evaluated by comparing estimates against known values of protein and lipids, using root mean square error (RMSE). Abdominal and leg fat pad mass were highly correlated with total lipid (r = 0.92), and body mass was highly correlated with total protein (r = 0.80). Models that used body mass, fat depots and/or muscle group data were the most accurate (lipids ad...

Nutzung des Ultraschalls in der Schlachtleistungsprüfung und Zuchtwertschätzung für Schafe

Abstract. Title of the paper: Using of Ultrasound for estimation of carcass composition and prediction of breeding value for sheep’s In Thuringia the subjective visual conformation scores of carcasses for blade (BL), leg (K), back (R), fat overlay (OF) and kidney fat (NF) were added by ultrasonic muscle (USK) and fat (USF) depths of living lambs. Heritabilitity estimates were carried out on 2654 slaughtered and 3228 living and ultrasonic-tested Merinolongwool lambs. Estimates of the subjective conformation scores were very low with 0.178 (BL); 0.143 (K); 0.165 (R) and 0.118 (OF). Slightly higher heritabilities could be estimated for NF (0.234), USK (0.26) and USF (0.174). The genetic correlations between conformation scores for muscle on one hand and OF and USF on the other hand were between 0.313 and 0.848. In contrast, the genetic correlation between USK on one hand and OF and USF on the other hand was rA = 0.022 and rA = −0.110, respectively). This may increase efficiency of breeding . By means of selection differences, it is recommended to use USK instead of blade and back, and USF instead of fat overlay in selection index.

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

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

Age at puberty, total fat and conjugated linoleic acid content of carcass, and circulating metabolic hormones in beef heifers fed a diet high in linoleic acid beginning at four months of age.

In the current study, we hypothesized that diets high in linoleic acid would increase conjugated linoleic acid (CLA) tissue content, reduce adiposity and leptin production, and result in an increase in the age at puberty in heifers. Heifers were weaned and blocked by body weight (heavy, n = 10, and light, n = 10) and allocated randomly within block to receive isocaloric and isonitrogenous diets with either added fat (HF, n = 10) or no added fat (C, n = 10) from 4 mo of age until post-pubertal slaughter. Whole sunflower seed (55% oil; 70% linoleic acid) was used as the fat source in HF diets and provided 5% added fat from the start of the study until heifers weighed 250 +/- 8 kg, at which time added fat was increased to 7% of dry matter until slaughter. Body weights were recorded weekly, and blood samples were collected weekly for total cholesterol and hormone analyses. Puberty was confirmed based on serum concentrations of progesterone and ultrasonographic confirmation of corpora lutea. Heifers were slaughtered at 325 +/- 10 d of age, and longissimus muscle between the 9th and 11th rib was collected and analyzed to estimate carcass composition. Subcutaneous and kidney, pelvic, and heart fat were collected at slaughter for fatty acid analyses. The HF heavy group tended (P < 0.10) to reach puberty later than all other groups, and one HF light heifer did not reach puberty during the study. Linoleic acid and cis-9, trans-11 CLA tissue contents were higher (P < 0.03) in HF heifers than controls, but neither total carcass fat nor percentage of dry matter differed by dietary group, although the percentage of protein tended (P < 0.10) to be lower in HF heifers. Mean serum concentrations of leptin did not differ due to diet; however, leptin increased (P < 0.01) linearly as puberty approached. Circulating concentrations of growth hormone and insulin-like growth factor I increased or remained relatively constant between wk 2 to 10 of feeding, and then declined (P < 0.01) until the onset of puberty. Serum IGF-I was lower (P < 0.01) in heifers receiving the HF diet. Mean serum concentrations of insulin and total cholesterol increased (P < 0.01) with time in both groups, but only total cholesterol was increased by the HF diet (P < 0.05). Results indicate that diets high in linoleic acid fed to growing beef heifers beginning early in life have little or no effect on total carcass fat, circulating leptin, or age at puberty despite measurable increases in CLA accumulation.

Growth and carcass composition of second-cross lambs. 1. Effect of sex and growth path on pre- and post-slaughter estimates of carcass composition

Carcass composition was estimated for 2316 second-cross lambs sired by 20 Poll Dorset rams over 2 years. The lambs were separated into ewes or cryptorchids at weaning with half of each sex group grown at a fast rate from weaning to slaughter at 40 kg liveweight for ewes or 48 kg for cryptorchids. The other half of each sex group was grown at a slower rate to the same slaughter weight 10–13 weeks later. Cryptorchids had fat scores about 0.4–1 unit lower and ultrasound C fat depths (45 mm from the mid-line over the 12th rib) about 0.8–1.3 mm less than ewes at the same liveweight. The carcass measures unequivocally showed that at the same carcass weight, fast-growing lambs were fatter than slow-growing lambs in both years and for both sexes. The average differences were 1.5 mm GR (total tissue depth 110 mm from the mid-line of the carcass over the 12th rib) and 1.4 mm C fat depth. Fat measurements on live lambs showed fast-growth cryptorchids were fatter than slow-growth cryptorchids; however, results for ewes were inconclusive. Slow growth to increase leanness needs to be evaluated against prevailing costs of lamb production and seasonal variation in prices. The correlations among and between live measures and carcass measurements of fatness were relatively low. The highest live to carcass R 2 values were ultrasound C fat depth with carcass C fat depth (0.36) and with the AUS-MEAT probe GR (0.34). There is a need to identify the best live lamb predictors of carcass composition.

Estimation of carcass composition by computer image analysis in the cross sections of cross-bred steers

Estimation equations for carcass composition were obtained using the information extracted from the carcass cross section by Computer Image Analysis (CIA). The total kilograms of lean, fat, and bone, and their percentages, were measured on the left side of the carcasses of F1 (cross-bred between Japanese Black and Holstein) steers by physical dissection. Traced data of the cross section between the 5th and 6th ribs (Data set I) and pictures of carcass cross section between the 7th and 8th ribs (Data set II) were subjected to image analysis. Various information on both the individual muscles and the overall outline of the cross section was extracted by the CIA technique. Maximum R2 improvement method of the stepwise procedure was used to choose the best regression equation to estimate carcass composition as total kilograms and percentages of lean, fat, and bone. The data sets were also adjusted for age and the stepwise procedure was also conducted. Coefficients of determination, adjusted for the degrees of freedom (adjusted R2) of the regression equations for estimating carcass composition, were high, i.e., 0.779 to 0.959 for kilograms of lean, fat, and bone, whereas for the percentages of lean, fat, and bone were high, i.e., 0.788 to 0.952, respectively. For the adjusted data, the adjusted R2 for estimating kilograms of lean, fat, and bone with Data sets I and II were 0.729, 0.633, and 0.598, and 0.813, 0.806, and 0.878, respectively, while for the percentages of lean, fat, and bone were 0.793, 0.623, and 0.378, and 0.953, 0.989, and 0.467, respectively. When the estimation equation obtained from the unadjusted Data set I was fitted with the information extracted from Data set II, the correlation coefficients between the values estimated by the equation and the values obtained by physical dissection on carcass composition were high, ranging from 0.70 to 0.92. On the other hand, the correlation coefficients obtained from the adjusted data sets were low. Key words: Estimation equation, computer image analysis, carcass composition, carcass cross section, F1 steers

Estimation of lamb carcass composition using an electronic probe, a visual scoring system and carcass measurements

Sixteen hundred and sixty lambs were used to determine the precision of carcass measurements (fat thickness, muscle thickness, tissue depth) and a visual scoring system for muscle and fat thickness to estimate carcass composition. Measurements of fat (F) and muscle (M) thickness were made in warm and cold carcasses and total tissue depth in warm carcasses only between the 10th and 11th ribs and the 12th and 13th ribs using an electronic probe (Hennessy Grading Probe HGP). F explained 40–64% of the variation in carcass lean and 44–72% of the variation in carcass fat depending on the location and number of measurements and whether they were made on a warm or cold carcass. In most cases when M was added to F there was no increase in the variation explained in composition over that provided by F alone. Total tissue depth measurements differed in precision for the prediction of carcass lean content with the 12th rib being superior to the 10th rib (RSD for 12th rib, 33.2 g kg−1; 10th rib, 36.6 g kg−1). Visual assessment of carcasses for fatness had the lowest precision for the prediction of lean content (RSD, 44.5 g kg−1). Loin eye area and fat thickness measured at the 12th rib had similar precision for the estimation of lean content as probe measurements. It was concluded that probe measurements of F or tissue depth between the 12th and 13th ribs would provide a superior method to the visual assessment of carcass fatness used in this study for classifying lamb carcasses for lean content and would allow carcasses to be graded on the slaughter floor. Key words: Lamb, carcass, grading, Hennessy Grading Probe, composition