Prediction Of Carcass Composition Research Articles

Estimation of in vivo body composition of Iberian pigs using bioelectric impedance and ultrasonography techniques

Iberian pigs are renowned for their high-quality products and distinctive characteristics, including high fat accumulation, low protein deposition rate, and a long productive cycle. The study aimed to assess in vivo body composition of purebred Iberian pigs using bioimpedance analysis (BIA) and ultrasonography. Accurate estimation of body composition in live animals is crucial for adopting decisions at the farm level. The experiment involved three groups of pure male Iberian pigs differing in body weight (BW; 60, 80 and 100 kg) with the same nutritional management. Body measurements, BIA and back fat and loin thickness (measured by ultrasonography) were obtained before slaughter. After slaughter pig carcasses were chemically analysed. A strong correlation between BIA measurements, specifically resistance (Rs) values, and body chemical parameters (total protein, lipids, ash, and water contents; p < 0.001 for all) was found. Reactance values (Xc), however, did not exhibit significant correlations. Regression analyses were conducted to predict carcass composition based on BIA measurements, BW, ultrasonography and linear corporal measurements. The prediction models achieved high R2 values for lipids, protein, total ash, water, and lean tissue (0.957, 0.968, 0.936, 0.961 and 0.976, respectively, p < 0.001 for all), indicating strong predictive power. These findings demonstrate the potential of non-invasive techniques such as BIA for estimating body chemical composition and quality of pig carcasses. However, it is important to acknowledge that the prediction models developed may not be applicable to other pig populations, as they were based on a specific sample of pigs.

Prediction of Carcass Composition and Meat and Fat Quality Using Sensing Technologies: A Review

Consumer demand for high-quality healthy food is increasing; therefore, meat processors require the means toassess their products rapidly, accurately, and inexpensively. Traditional methods for quality assessments are time-consum-ing, expensive, and invasive and have potential to negatively impact the environment. Consequently, emphasis has been puton finding nondestructive, fast, and accurate technologies for product composition and quality evaluation. Research in thisarea is advancing rapidly through recent developments in the areas of portability, accuracy, and machine learning.Therefore, the present review critically evaluates and summarizes developments of popular noninvasive technologies(i.e., from imaging to spectroscopic sensing technologies) for estimating beef, pork, and lamb composition and quality,which will hopefully assist in the implementation of these technologies for rapid evaluation/real-time grading of livestockproducts in the near future.

Fat Deposition and Fat Effects on Meat Quality-A Review.

Simple SummaryAnimal fat deposition has a major impact on the meat yield from individual carcasses as well the perceived eating quality for consumers. Understanding the impact of livestock production practices on fat deposition and the molecular mechanisms activated will lead to a better understanding of finishing livestock. This enhanced understanding will also lead to the increased efficiency and improved sustainability of practices for livestock production. The impact of fat storage on physiological functions and health are also important. This review brings together both the production practices and the current understanding of molecular processes associated with fat deposition.Growth is frequently described as weight gain over time. Researchers have used this information in equations to predict carcass composition and estimate fat deposition. Diet, species, breed, and gender all influence fat deposition. Alterations in diets result in changes in fat deposition as well as the fatty acid profile of meat. Additionally, the amount and composition of the fat can affect lipid stability and flavor development upon cooking. Fat functions not only as a storage of energy and contributor of flavor compounds, but also participates in signaling that affects many aspects of the physiological functions of the animal. Transcription factors that are upregulated in response to excess energy to be stored are an important avenue of research to improve the understanding of fat deposition and thus, the efficiency of production. Additionally, further study of the inflammation associated with increased fat depots may lead to a better understanding of finishing animals, production efficiency, and overall health.

Estimation of Carcass Tissue Composition from the Neck and Shoulder Composition in Growing Blackbelly Male Lambs.

This study was designed to develop predictive equations estimating carcass tissue composition in growing Blackbelly male lambs using as predictor variables for tissue composition of wholesale cuts of low economic value (i.e., neck and shoulder). For that, 40 lambs with 29.9 ± 3.18 kg of body weight were slaughtered and then the left half carcasses were weighed and divided in wholesale cuts, which were dissected to record weights of fat, muscle, and bone from leg, loin, neck, rib, and shoulder. Total weights of muscle (CM), bone (CB) and fat (CF) in carcass were recorded by adding the weights of each tissue from cuts. The CM, CF and CB positively correlated (p < 0.05; 0.36 ≤ r ≤ 0.86), from moderate to high, with most of the shoulder tissue components, but it was less evident (p ≤ 0.05; 0.32≤ r ≤0.63) with the neck tissue composition. In fact, CM did not correlate with neck fat and bone weights. Final models explained (p < 0.01) 94, 92 and 88% of the variation observed for CM, CF and CB, respectively. Overall, results showed that prediction of carcass composition from shoulder (shoulder) tissue composition is a viable option over the more accurate method of analyzing the whole carcass.

Prediction of carcass composition through measurements in vivo and measurements of the carcass of growing Santa Inês sheep.

In vivo and carcass measurements were evaluated to predict carcass physical and chemical composition and to list the measurements that best fit the prediction of the composition of growing Santa Inês sheep carcasses. Thirty-three animals were used to measure the loin eye area by ultrasound in vivo (LEAu) and in the carcass. We used 39 animals for biometric measurement in vivo and 42 sheep for morphometric measurement in the carcass. For the physical and chemical compositions of carcasses, dissection of the half left carcass was carried out in 42 animals. The data were submitted to Pearson’s correlation analysis and t test. Simple and multiple linear regressions were performed using a stepwise procedure. All correlations between in vivo measurements and the physical and chemical compositions of carcasses (in kg) were significant, except for LEAu. Biometric measurements and hot (HCW) and cold (CCW) carcass weights were considered as predictors of the carcasses’ physical and chemical compositions. Slaughter body weight (SBW) was the variable that most influenced the equations in the assessment of in vivo measurements and HCW and CCW most influenced the equations for measurements on carcasses. Biometric measurements of Santa Inês sheep can be used together with the SBW to estimate the physical and chemical compositions of carcasses, with emphasis on body compactness index, breast width, wither height, and croup height. The morphometric measurements can be used together with carcass weight to estimate the physical and chemical compositions of carcasses, with emphasis on croup width, carcass compactness index, croup perimeter, external and internal carcass lengths, chest width, and leg length and perimeter. The HCW can be used to predict the physical and chemical composition of carcasses without affecting the accuracy of the prediction model.

PSI-5 Comparison of ninth-tenth-eleventh rib section to carcass components in serially harvested steer carcasses

Abstract The objective of this study was to compare separable lean, fat and bone of samples taken from the ninth-tenth-eleventh rib section to those of the carcass. Charolais x Angus steers (n = 80) were randomized to implant treatments (REV: Revalor-XS on d-0 and d-190 or CON: no implant) and harvest date in a 2x10 factorial design. Four pairs of steers were randomly allocated to one of 10 harvest dates and harvested in 42d intervals (0, 42, 84, 126, 168, 210, 252, 294, 336, and 378). Carcass yields were determined by fabricating the right side of each carcass and separating lean, fat, and bone components and weighing to the nearest +/- .05 kg. Ninth-tenth-eleventh rib sections were collected from the left side of each carcass, dissected into lean, fat, and bone, and weighed to the nearest +/- .005 g. Regression models were created to determine linear associations between rib sections and carcass parameters. Carcass fat and lean were strongly correlated (r = 0.87 and 0.80 respectively) to 9-10-11 fat and lean, however carcass bone was only moderately correlated (r = 0.59) to 9-10-11 bone. Rib sections were representative of a whole carcass supporting use of this method to predict carcass composition of beef cattle.

Resource-Efficient Classification and Early Predictions of Carcass Composition in Fattening Pigs by Means of Ultrasound Examinations

The development of the backfat thickness of fattening pigs in relation to their weight allows first conclusions to be drawn concerning the efficiency of individual growth and classification of the carcass. The hypothesis was that, firstly, via measurement of backfat thickness and muscle diameter, their ratio and the quality of the carcass can be predicted and that, secondly, using resource-efficient and sustainable feeding has no negative effects on the carcass. Over a 70-day period, ultrasound examinations of backfat and musculus longissimus dorsi were performed in a pen with sorting gates and automatic body mass recordings every two weeks on 121 animals of the same age, starting at approximately 50 kg. Data were subdivided into four groups for each measurement time. There was weak (Examination 1: r = −0.28164; p = 0.0018) but steadily increasing correlation (Examination 5: r = −0.60657; p ≤ 0.0001) between the backfat/muscle ratio and the carcass quality. In all four groups, significant differences in the diameter of the M. longissimus dorsi (“light fat (LF) = 3.29 cm; “light lean (LL)” = 3.62 cm; “heavy fat (HF)” = 3.69 cm; “heavy lean (HL)” = 3.93 cm) and in backfat thickness (LF = 0.44 cm; LL = 0.38 cm; HF= 0.47 cm; HL= 0.39 cm) could be shown during the first examination.

The comparison of the selected morphometric traits in three medium-sized rabbit breeds

The comparison of the selected morphometric traits in three medium-sized rabbit breeds

USING BEEF MORPHOLOGY TO PREDICT CARCASS WEIGHT WHICH CUTTING IN THAI-ISAAN STYLE

The trading of the beef cattle market in Thailand is based on the price satisfaction agreement between sellers and buyers. The rancher, the middlemen and the butcher shop have been predicted the return from visual assessment. The prediction of return from carcass composition depends on personal skill. The highest price of carcass cutting in Thai-Isaan style composes with all meat, liver, spleen, kidney, heart, tongue and gastric. The objective of this study was to determine the best-fitted regression model for predicting the weight of carcass composition using body measurements. Data on carcass composition cutting in Thai-Isaan style and linear body measurements recorded form 100 crossbred male beef in Northeastern (Isaan) region were used for this study. The simple and multiple regression models were fitted with carcass composition as the dependent variable and heart grit, body height, body length, hip width and hip length as independent variables. The correlation coefficients between carcass composition and body measurements were strongly and significantly (P<0.01). Body length was best fit to simple regression model for predict carcass composition weight (R2=0.712). A stepwise method was used to fitting the regression model. The recommended model was the 3 factors left in the model (heart girth, body length and hip length) with R2=08101. The study concludes that linear body measurements can predict carcass composition weight and their return. The rancher, the middlemen and the butcher shop can use this equation to predict the return and set the beef price for trading.

Effects of rumen-protected long-chain fatty acid supplementation during the finishing phase of beef steers on live performance, carcass characteristics, beef quality, and serum fatty acid profile.

: The effect of a rumen-protected long-chain fatty acid (LCFA) supplement on live performance, meat quality, blood serum fatty acid profile, and predicted carcass composition was evaluated in this study. Angus steer calves (n = 99) were fed a low energy diet for 77 d prior to finishing. Prior to study initiation, the steers were separated into 12 pens with eight or nine steers per pen. Steers were transitioned from the low energy forage–based diet to a high concentrate diet containing high moisture ear corn, corn silage, dry rolled corn, soybean meal, and a liquid supplement containing monensin across 21 d. Megalac-R (RPFA) was fed to six pens at 2% of the diet dry matter. Control pens (CON; n = 6) received an additional 2% of diet dry matter as dry rolled corn and soybean meal. The final finishing diet net energy for gain (NEg) was 1.20 and 1.19 mega calories·kg−1 of dry matter (DM) for RPFA and CON treatments, respectively. Steers were weighed every 28 d. Growth performance data including average daily gain (ADG), gain to feed ratio (G:F), and DM intake (DMI) were calculated as both monthly and overall data. After a 147-d finishing phase, steers were transported to a commercial abattoir for slaughter. After a 28-h chilling period, carcass data were obtained by trained personnel. Final live weights were greater (P = 0.01) for RPFA than CON cattle. Overall ADG and overall G:F was increased (P = 0.02; P = 0.01, respectively) for RPFA cattle. Ribeye area, backfat thickness, kidney pelvic heart fat, marbling score, and yield grade did not differ (P > 0.05) between treatments. Predicted percent carcass fat was increased for RPFA cattle (P = 0.05). Conversely, predicted percent carcass protein (P = 0.07) and bone (P = 0.06) tended to be greater for CON cattle. Long-chain fatty acid supplementation during the finishing phase did not increase marbling scores of the steers in this study but did increase final live weight, HCW, and predicted total body fat. These results suggest that RPFA supplementation has the potential to increase adipose tissue development. However, it is likely that animal age during supplementation and duration of supplementation impact the effect RPFAs have on carcass characteristics.

Contribution of nutrient fluxes to the evolution of the net energy systems, example of the INRA feeding system for beef cattle.

Energy feeding systems define energy as a whole, but progress made to define metabolizable energy (ME) as the sum of the metabolizable nutrients produced by digestion and available for tissue metabolism in a wide range of nutritional situations opens the way to quantitatively model and predict nutrient fluxes between and within tissues and organs and improve predictions of energy use. This review addresses the contribution of nutrient flux concepts and data to the evolution of the Institut de la Recherche Agronomique (INRA) energy feeding system for growing and fattening cattle and evaluates the outcomes on the net energy (NE) requirements. It summarizes recent progress made to quantitatively predict nutrient fluxes both at digestive and visceral levels. It reviews how nutrient flux concepts and results were introduced in the recently updated INRA feeding system, resulting in improvements in the accuracy of the revised digestible energy (DE) and ME value of diets. The use of an independent database showed that for diets fed to fattening cattle, DE and ME concentrations were downgraded for low-energy-dense diets and upgraded for high-energy-dense diets. We are also showing that compared with its previous version, the updated INRA system improves the quantitative relationship between ME supply and flows of metabolizable nutrients. Evidence is provided on how measured nutrient fluxes at portal level were used to evaluate the predicted flows of metabolizable nutrients. This review then revisits the NE values of diets for fattening cattle as defined by the INRA feeding system and not updated yet. Using an independent database and at similar ME intake, carcass composition was shown to be linearly related to the energy density of diets for fiber-rich diets but not for concentrate-rich diets, suggesting that the efficiency of energy utilization of ME into NE is not linearly related to differences in the composition of the gain. Accounting for the balance of metabolizable nutrients or their proxies in models used to predict carcass composition from ME intake can improve predictions. Overall partitioning aggregated energy fluxes into their subcomponent nutrient fluxes in a more physiological approach offers promising perspectives for the evolution of NE feeding systems.

Bodyweight performance, estimated carcass traits and methane emissions of beef-cattle categories grazing Andropogon gayanus, Melinis minutiflora and Stylosanthes capitata mixed swards and Brachiaria humidicola pasture

Cow–calf operations constitute the main land-use system in the 18 million ha of well drained tropical savannas of Colombia located in the Orinoco basin. There, numerous sex and age animal categories are present, ranging from suckling calves to old cull cows and steers, which in variable proportions are stocked at one animal unit (AU)/5–10 ha, depending on the ranch and distance from markets. In parallel, early-on farm observations showed that when sown pastures are introduced, graziers recur to opportunistic partial fattening of cull animals for a rapid economic return. The paper reports animal weight gains of cull cows, old steers, and young heifers and yearlings over seven consecutive years grazing on a low fertiliser-input well managed Andropogon gayanus-based pasture and four contemporary years on Brachiaria humidicola. The first 2 years involved three stocking rates (SR; 1.38, 1.85 and 2.32 animal units/ha), whereas a single SR of 1.33 animal units/ha was used for the remainder. A large database that included chemical, and in vitro and in vivo digestibility, values for all forages involved, was used as an input to a mathematical model to estimate methane (CH4) emissions. Estimations were compared with weight-based predictions derived from chamber measurements recorded recently in tropical Australia. Faecal mineral concentration varied little (not significantly) among SR and animal categories. Weight gains of old steers were 4–24% larger than those of cull cows, which, in turn, were larger than those of young steers and heifers (P &amp;lt; 0.01). Excepting one year, the performance of cull cows and old steers did not differ between pastures, confirming earlier on-ranch observations of reasonable weight gains of adult cattle on both pastures. The predicted carcass composition of cull cows and old steers did not differ between pastures either. Over the length of the experiment, cull cows emitted significantly less CH4 than did old steers (129 vs 141 g/day) on A. gayanus, while emissions on B. humidicola amounted to 128 and 137 g/day respectively. Despite between-year differences in animal performance, they are indicative of well managed pasture sustainability. They also show some of the trade-offs involved in the use of contrasting animal categories and pastures in terms of weight performance and predicted carcass composition and CH4 production. The authors expect that the present results will contribute to a rational, science-based discussion of the role of beef systems vis-à-vis environment in a region with limited production alternatives.

Application of bioelectrical impedance analysis in prediction of light kid carcass and muscle chemical composition

Carcass data were collected from 24 kids (average live weight of 12.5±5.5 kg; range 4.5 to 22.4 kg) of Jarmelista Portuguese native breed, to evaluate bioelectrical impedance analysis (BIA) as a technique for prediction of light kid carcass and muscle chemical composition. Resistance (Rs, Ω) and reactance (Xc, Ω), were measured in the cold carcasses with a single frequency bioelectrical impedance analyzer and, together with impedance (Z, Ω), two electrical volume measurements (VolA and VolB, cm2/Ω), carcass cold weight (CCW), carcass compactness and several carcass linear measurements were fitted as independent variables to predict carcass composition by stepwise regression analysis. The amount of variation explained by VolA and VolB only reached a significant level (P<0.01 and P<0.05, respectively) for muscle weight, moisture, protein and fat-free soft tissue content, even so with low accuracy, with VolA providing the best results (0.326⩽R2⩽0.366). Quite differently, individual BIA parameters (Rs, Xc and Z) explained a very large amount of variation in dissectible carcass fat weight (0.814⩽R2⩽0.862; P<0.01). These individual BIA parameters also explained a large amount of variation in subcutaneous and intermuscular fat weights (respectively 0.749⩽R2⩽0.793 and 0.718⩽R2⩽0.760; P<0.01), and in muscle chemical fat weight (0.663⩽R2⩽0.684; P<0.01). Still significant but much lower was the variation in muscle, moisture, protein and fat-free soft tissue weights (0.344⩽R2⩽0.393; P<0.01) explained by BIA parameters. Still, the best models for estimation of muscle, moisture, protein and fat-free soft tissue weights included Rs in addition to CCW, and accounted for 97.1% to 99.8% (P<0.01) of the variation observed, with CCW by itself accounting for 97.0% to 99.6% (P<0.01) of that variation. Resistance was the only independent variable selected for the best model predicting subcutaneous fat weight. It was also selected for the best models predicting carcass fat weight (combined with carcass length, CL; R2=0.943; P<0.01) and intermuscular fat weight (combined with CCW; R2=0.945; P<0.01). The best model predicting muscle chemical fat weight combined CCW and Z, explaining 85.6% (P<0.01) of the variation observed. These results indicate BIA as a useful tool for prediction of light kids’ carcass composition.

Age at castration (surgical or immunological) impacts carcass characteristics and meat quality of male pigs

In order to accurately estimate body composition at slaughter and to meet specific market targets, the influence of age at time of castration (surgical or immunological) on body composition and boar taint indicators must be determined for male pigs. In all, 48 males were randomly assigned to one of four management regimens: (1) entire male pigs (EM), (2) EM surgically castrated at ~40 kg BW and 10 weeks of age (late castrates; LC), (3) conventional, early surgical castrates (within 4 days of birth; EC) and (4) EM immunized with a gonadotropin-releasing hormone (GnRH) analog (primary dose at 30 kg BW and 8 weeks of age; booster dose at 70 kg and 14 weeks of age; IM). Pigs were fed corn and soybean meal-based diets that were not limiting in essential nutrients. Back fat was sampled on days −3, 8, 18 and 42, relative to administering the booster dose of GnRH analog at day 0, to determine androstenone concentrations (n=8 or 9/group). Fat androstenone concentrations in IM were lower than EM between days 8 and 42 after administering the booster dose (173 v. 863 ng/g, respectively; P<0.01), and were not different from surgically castrated males (EC and LC) after day 18. Slaughter occurred at ~115 kg BW, 42 days (6 weeks) after administering the booster dose for IM, and 10 and 20 weeks after surgical castration for LC and EC, respectively (n=8 or 9/group). At slaughter, live BW, liver weight as a percent of live BW, dissectible bone as a percent of cold carcass side, body protein and water contents and whole-body protein deposition decreased with time after surgical castration (linear; P<0.05), whereas dressing percentage, dissectible fat, probe fat depth and body fat content increased with time after surgical castration (linear; P<0.05). The IM had intermediate dressing percentage and dissected fat to EM and EC, whereas liver weight as a percent of live BW and body protein and lipid contents were not different from EM. Whole-body lipid deposition tended to be greater in IM than in EM between 14 and 20 weeks of age (373 v. 286 g/d; P=0.051). In conclusion, castration of male pigs after 6 weeks of age has a lasting effect on physical and chemical body composition. The relationship between time after castration and body composition may be developed to predict carcass composition and can be used to determine the ideal immunization schedule aimed at specific markets in the future.

Prediction of Carcass Composition Using Carcass Grading Traits in Hanwoo Steers.

The prediction of carcass composition in Hanwoo steers is very important for value-based marketing, and the improvement of prediction accuracy and precision can be achieved through the analyses of independent variables using a prediction equation with a sufficient dataset. The present study was conducted to develop a prediction equation for Hanwoo carcass composition for which data was collected from 7,907 Hanwoo steers raised at a private farm in Gangwon Province, South Korea, and slaughtered in the period between January 2009 and September 2014. Carcass traits such as carcass weight (CWT), back fat thickness (BFT), eye-muscle area (EMA), and marbling score (MAR) were used as independent variables for the development of a prediction equation for carcass composition, such as retail cut weight and percentage (RC, and %RC, respectively), trimmed fat weight and percentage (FAT, and %FAT, respectively), and separated bone weight and percentage (BONE, and %BONE), and its feasibility for practical use was evaluated using the estimated retail yield percentage (ELP) currently used in Korea. The equations were functions of all the variables, and the significance was estimated via stepwise regression analyses. Further, the model equations were verified by means of the residual standard deviation and the coefficient of determination (R2) between the predicted and observed values. As the results of stepwise analyses, CWT was the most important single variable in the equation for RC and FAT, and BFT was the most important variable for the equation of %RC and %FAT. The precision and accuracy of three variable equation consisting CWT, BFT, and EMA were very similar to those of four variable equation that included all for independent variables (CWT, BFT, EMA, and MAR) in RC and FAT, while the three variable equations provided a more accurate prediction for %RC. Consequently, the three-variable equation might be more appropriate for practical use than the four-variable equation based on its easy and cost-effective measurement. However, a relatively high average difference for the ELP in absolute value implies a revision of the official equation may be required, although the current official equation for predicting RC with three variables is still valid.

Evaluating the accuracy of dual energy X-ray absorptiometry (DEXA) in predicting carcass composition from varying pig populations

Evaluating the accuracy of dual energy X-ray absorptiometry (DEXA) in predicting carcass composition from varying pig populations

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.

Evaluation of ultrasound scanning to predict carcass composition of Austrian meat sheep

Aims of the study were to evaluate the routine ultrasound scanning plus subjective muscle scoring system for meat sheep in Austria in terms of (1) their ability to predict carcass quality and composition, (2) the repeatability of ultrasound scanning and (3) a comparison of three anatomical scanning sites. Lambs of six breeds (n=189; mean bodyweight 39kg) were scored for the muscling of their shoulder, back and hindquarter and were scanned with an ultrasound device for back fat and longissimus dorsi muscle depth lateral of the spine at 10th/11th (US1) and 13th (US2) thoracic vertebrae as well as at 3rd/4th (US3) lumbar vertebrae. Each ultrasound picture was taken twice within a few minutes to check on within operator repeatability. After slaughter the carcasses were classified according to the EUROP system and back fat and muscle depth were measured on a carcass cross section, and 36 carcasses were dissected to lean meat, fat and bone to evaluate carcass composition. Relationships between carcass and dissection traits and routine performance testing traits (live weight, fat and muscle depth at US3) were evaluated based on partial regression coefficients additionally considering breed, sex (carcass traits only) and birth type as fixed effects. Further, fat and muscle depth at scan sites US1 and US2 were fitted alternatively and Pearson's correlation coefficients were calculated. Correlations between ultrasonic and carcass measures ranged from r=0.60 (muscle depth at US1 and EUROP conformation class) to r=0.84 (muscle depth at US1 and muscle depth at carcass). Repeatabilities for muscle and backfat thickness ranged from 0.90 to 0.95. The results support the usefulness of the currently routine ultrasound scans as relatively easy method to predict carcass composition in live lambs of different breeds. Muscle scans are valuable to estimate amount of carcass lean and EUROP conformation class, but fat scans have greater power to predict the fattiness of the carcass as well as lean percentage. Subjective muscle scoring of live animals seems to be mainly influenced by the fattiness of the animal. The comparison of three anatomical scanning sites did not give definite results. US1 seems to be favourable for estimating muscle depth, for the prediction of lean and in terms of repeatability whereas US2 and US3 had small advantages in scanning fat depth and in the prediction of EUROP classification and carcass fat.

Prediction of carcass composition and individual carcass cuts of Japanese Black steers

The objective of this study was to develop equations to predict carcass tissue weights and percentages and boneless carcass non-trimmed cut weights by using the cold carcass weight (CCW) and three other traits at the 6–7th rib section, which are routinely collected in carcass markets in Japan. Carcasses from 94 Japanese Black steers were used for the multiple regression analysis with a stepwise procedure and a novel Least Absolute Shrinkage and Selection Operator (LASSO). The accuracies of prediction (R2) and RMSEs for the carcass tissue and cut weights were similar between the two procedures. In contrast, LASSO appeared to be the better procedure for predicting carcass tissue percentages. The longissimus muscle area and subcutaneous fat thickness were the important predictors for the lean percentage in the stepwise procedure, and CCW was additionally selected when the LASSO procedure was used.

Prediction of carcass composition, ham and foreleg weights, and lean meat yields of Iberian pigs using ultrasound measurements in live animals1

The most valuable lean cuts from Iberian pigs are the hams, forelegs, and loins, which yield high quality cured meat products. This study aimed to assess the correlation between body composition measurements taken in vivo by ultrasonography in Iberian pigs and those taken on the carcass, which were then used to develop predictive models to estimate the weight and yield of these cuts. Before slaughter, 241 Iberian pigs were weighed (slaughter BW) and ultrasonically scanned. Ultrasound images were collected at 3 locations: the 10th intercostal space, caudal to the last rib to image the loin muscle, and the rear gluteal region [ultrasound gluteal backfat (u-GBF)]. After slaughter, the weight of the carcass (CW), ham (HW), foreleg (FW), and loin (LW) were determined, and the sum of these lean cuts weights (CLPW) and the corresponding yields were calculated. A portion of loin with the associated bones, backfat, and skin was obtained by cutting the carcass between the 10th and last ribs and was used to measure, at the 10th (10) and last (14) rib locations, the total backfat thickness, the area of the loin muscle (c-LA), and the thickness of the 4 backfat (BF) layers, namely, the outer (c-OBF), middle (c-MBF), outer plus middle (c-OMBF), and the inner (c-IBF). Finally, intramuscular fat percentages (IMF) were obtained from the meat samples. Corresponding measurements from the ultrasound (u) images were similarly taken at the same 2 ribs (u-BF, u-LA, u-OBF, u-MBF, u-OMBF, and u-IBF). The correlation was greatest between u-MBF10 and c-MBF10 (0.84). Most correlations between ultrasound and carcass measurements were lower at the last rib than at 10th rib. The greatest correlation of IMF10 occurred with u-IBF10 (0.40). Ham weight and HL were more correlated with u-BF10 than with u-BF14 whereas FW was more correlated with u-BF14. The u-LA was more correlated with HW, FW, and LW at the last rib than at the 10th rib. Slaughter live weight accounted for 0.84, 0.42, 0.36, and 0.54% of the variation for the prediction of CW, HW, FW, and CLPW, respectively. The u-LA10 and u-LA14 increased the variation explained by the model up to 0.89, 0.48, 0.39, and 0.62% for CW, HW, FW, and CLPW, respectively. Including u-GBF in the models also increased the R(2) values for predicting HW, LW, HY (ham yield), and LY (loin yield). In conclusion, u-LA10, u-LA14, and u-GBF may improve weight of commercial cuts and yield prediction in live Iberian pigs.