Commercial adaptation of ultrasonography to predict pork carcass composition from live animal and carcass measurements.

Live animal and carcass data were collected from market barrows and gilts (n = 120) slaughtered at a regional commercial slaughter facility to develop and test prediction equations to estimate carcass composition from live animal and carcass ultrasonic measurements. Data from 60 animals were used to develop these equations. Best results were obtained in predicting weight and percentage of boneless cuts (ham, loin, and shoulder) and less accuracy was obtained for predicting weight and ratio of trimmed, bone-in cuts. Independent variables analyzed for the live models were live weight, sex, ultrasonic fat at first rib, last rib, and last lumbar vertebra, and muscle depth at last rib. Independent variables for the carcass models included hot carcass weight, sex of carcass, and carcass ultrasonic measurements for fat at the first rib, last rib, last lumbar vertebra, and muscle depth at last rib. Equations were tested against an independent set of experimental animals (n = 60). Equations for predicting weight of lean cuts, boneless lean cuts, fat-standardized lean, and percentage of fat-standardized lean were most accurate from both live animal and carcass measurements with R2 values between .75 and .88. The results from this study, under commercial conditions, suggest that although live animal or carcass weight and sex were the greatest contributors to variation in carcass composition, ultrasonography can be a noninvasive means of differentiating value, especially for fat-standardized lean and weight of boneless cuts.     

Using live estimates and ultrasound measurements to predict beef carcass cutability

Commercial slaughter steers (n = 329) and heifers (n = 335) were selected to vary in frame size, muscle score, and carcass fat thickness to study the effectiveness of live evaluation and ultrasound as predictors of carcass composition. Three trained personnel evaluated cattle for frame size, muscle score, fat thickness, longissimus muscle area, and USDA quality and yield grade. Live and carcass real-time ultrasound measures for 12th-rib fat thickness and longissimus muscle area were taken on a subset of the cattle. At the time of slaughter, carcass ultrasound measures were taken at "chain speed." After USDA grade data were collected, one side of each carcass was fabricated into boneless primals/subprimals and trimmed to .64 cm of external fat. Simple correlation coefficients showed a moderately high positive relationship between 12th rib fat thickness and fat thickness measures obtained from live estimates (r = .70), live ultrasound (r = .81), and carcass ultrasound (r = .73). The association between estimates of longissimus muscle area and carcass longissimus muscle area were significant (P < .001) and were higher for live evaluation (r = .71) than for the ultrasonic measures (live ultrasound, r = .61; carcass ultrasound, r = .55). Three-variable regression equations, developed from the live ultrasound measures, explained 57% of the variation in percentage yield of boneless subprimals, followed by live estimates (R2 = .49) and carcass ultrasound (R2 = .31). Four-variable equations using frame size, muscle score, and selected fat thickness and weight measures explained from 43% to 66% of the variation for the percentage yield of boneless subprimals trimmed to .64 cm. Live ultrasound and(or) live estimates are viable options for assessing carcass composition before slaughter.     

Using ultrasound measurements to predict body composition of yearling bulls

Carcass traits have been successfully used to determine body composition of steers. Body composition, in turn, has been used to predict energy content of ADG to compute feed requirements of individual animals fed in groups. This information is used in the Cornell value discovery system (CVDS) to predict DM required (DMR) for the observed animal performance. In this experiment, the prediction of individual DMR for the observed performance of group-fed yearling bulls was evaluated using energy content of gain, which was based on ultrasound measurements to estimate carcass traits and energy content of ADG. One hundred eighteen spring-born purebred and crossbred bulls (BW = 288 +/- 4.3 kg) were sorted visually into 3 marketing groups based on estimated days to reach USDA low Choice quality grade. The bulls were fed a common high-concentrate diet in 12 slatted-floor pens (9 to 10 head/pen). Ultrasound measurements including back-fat (uBF), rump fat, LM area (uLMA), and intramuscular fat were taken at approximately 1 yr of age. Carcass measurements including HCW, backfat over the 12th to 13th rib (BF), marbling score (MRB), and LM area (LMA) were collected for comparison with ultrasound data for predicting carcass composition. The 9th to 11th-rib section was removed and dissected into soft tissue and bone for determination of chemical composition, which was used to predict carcass fat and empty body fat (EBF). The predicted EBF averaged 23.7 +/- 4.0%. Multiple regression analysis indicated that carcass traits explained 72% of the variation in predicted EBF (EBF = 16.0583 + 5.6352 x BF + 0.01781 x HCW + 1.0486 x MRB - 0.1239 x LMA). Because carcass traits are not available on bulls intended for use as herd sires, another equation using predicted HCW (pHCW) and ultrasound measurements was developed (EBF = 39.9535 x uBF - 0.1384 x uLMA + 0.0867 x pHCW - 0.0897 x uBF x pHCW - 1.3690). This equation accounted for 62% of the variation in EBF. The use of an equation to predict EBF developed with steer composition data overpredicted the EBF predicted in these experiments (28.7 vs. 23.7%, respectively). In a validation study with 37 individually fed bulls, the use of the ultrasound-based equation in the CVDS to predict energy content of gain accounted for 60% of the variation in the observed efficiency of gain, with 1.5% bias, and identified 3 of the 4 most efficient bulls.     

Practical means for estimating pork carcass composition

Three hundred sixty-one market-weight barrow and gilt carcasses were physically dissected into bone, skin, fat and muscle. A three-variable multiple linear regression equation containing the same independent variables (warm carcass weight, 10th rib loin muscle area and 10th rib fat depth) used (U.S.) to determine pork carcass lean weight was found to be the most practical means for predicting weight of muscle standardized to 10% fat. Multiple linear regression equations containing more than three independent variables produced only slight improvements in R2 values; however, the standard deviation about the regression line was not greatly improved by the addition of more independent variables to this three-independent-variable regression model. A single multiple linear regression equation using the three independent variables above may not be adequate to describe variation over the entire live-weight range for all hogs marketed in the U.S. For most accurate muscle weight prediction, different equations should be used for weight subclasses with one equation for carcasses under 100 kg and another for those heavier than 100 kg. A single prediction equation for muscle weight was adequate for carcasses of both barrows and gilts.     

Predicting carcass composition of beef cattle using ultrasound technology.

We evaluated 20 slaughtered cattle with ultrasound before hide removal to predict fat thickness and ribeye area at the 12th rib for possible use in carcass composition prediction. Carcasses were fabricated into boneless subprimals that were trimmed progressively from 2.54 to 1.27 to .64 cm maximum fat trim levels. Stepwise regression was used to indicate the relative importance of variables in a model designed to estimate the percentage of boneless subprimals from the carcass at different external fat trim levels. Variables included those obtained on the slaughter floor (ultrasound fat thickness and ribeye area; estimated percentage of kidney, pelvic, and heart [KPH] fat; and warm carcass weight) and those obtained from carcasses following 24 h in the chill cooler (actual fat thickness, actual ribeye area, estimated percentage of KPH fat, warm carcass weight, and marbling score). At all different subprimal trim levels, percentage KPH was the first variable to enter the model. In the models using measures taken on the slaughter floor, ultrasound fat thickness was the only other variable to enter the model. Ultrasound fat thickness increased R2 and decreased residual standard deviation (RSD) in models predicting subprimals at 2.54-cm maximum fat trim; however, at 1.27- and .64-cm trim levels, R2 and RSD increased. Models using the same two variables (except actual fat instead of ultrasound) in the cooler were similar to those using data from the slaughter floor. However, as more cooler measurement variables entered the models, R2 increased and RSD decreased, explaining a greater amount of the variation in the equation. Ultrasonic evaluation on the slaughter floor may be of limited application compared with the greater accuracy found in chilled carcass assessment.     

Evaluation of alternative measures of pork carcass composition

Carcass and live measurements of 203 pigs representing seven genetic populations and four target live weights (100, 114, 128, and 152 kg) were used to evaluate alternative measures of carcass composition. Measures of carcass lean (fat tissue-free lean, FFLM; lipid-free soft tissue, LFSTIS; and dissected lean in the four lean cuts, DL), fat (total carcass fat tissue, TOFAT), and lipid mass (soft tissue lipid, STLIP) were evaluated. Overall, LFSTIS was 22.8% greater than FFLM (47.8 vs 38.9 kg) and TOFAT was 30% greater than STLIP (38.5 vs 29.6 kg). The allometric growth coefficients relative to carcass weight were different for the measures: b = 0.776, 0.828, 0.794, 1.37, and 1.49 for FFLM, LFSTIS, DL, TOFAT, and STLIP, respectively. At 90 kg carcass weight, the predicted growth of FFLM, LFSTIS, TOFAT, and STLIP was 0.314, 0.420, 0.553, and 0.446 kg/kg increase in carcass weight. The difference between FFLM and LFSTIS, representing nonlipid components of the carcass fat tissue, was greater for barrows than for gilts (9.2 vs 8.6 kg). Lipid-free soft tissue mass was predicted more accurately from carcass or live animal measurements than FFLM with smaller relative RSD (4.6 vs 6.5% of their mean values). The alternative measures of carcass composition were evaluated as predictors of empty body protein (MTPRO) and lipid (MTLIP) mass. Empty body protein was predicted with similar accuracy (R2 = 0.74 to 0.81) from either DL, FFLM, LFSTIS, or ribbed carcass measurements. Empty body lipid was predicted more accurately from TOFAT (R2 = 0.92) or STLIP (R2 = 0.93) than ribbed carcass measurements (R2 = 0.88). Although the alternative measures of lean mass (LFSTIS vs FFLM) and lipid mass (TOFAT vs STLIP) were highly related to each other (r = 0.93 to 0.98), they had different relative growth rates (allometric coefficients) and thus cannot be predicted as linear functions of the similar alternative variable without significant weight group biases. From the 100- to 152-kg target weight groups, gilts gained 12.9% greater FFLM and 12.1% greater MTPRO but only 4.4% greater LFSTIS than barrows. Fat-free lean mass is more precise as a measure of muscle growth and as a predictor of lysine requirements. Lipid-free soft tissue can be obtained more quickly and predicted more accurately from carcass or live animal measurements.     

Ractopamine treatment biases in the prediction of pork carcass composition

Carcass and live measurements of 45 barrows were used to evaluate the magnitude of ractopamine (RAC) treatment prediction biases for measures of carcass composition. Barrows (body weight = 69.6 kg) were allotted by weight to three dietary treatments and fed to an average body weight of 114 kg. Treatments were: 1) 16% crude protein, 0.82% lysine control diet (CON); 2) control diet + 20 ppm RAC (RAC16); 3) a phase feeding sequence with 20 ppm RAC (RAC-P) consisting of 18% crude protein (1.08% lysine) during wk 1 and 4, 20% crude protein (1.22% lysine) during wk 2 and 3, 16% crude protein (0.94% lysine) during wk 6, and 16% crude protein (0.82% lysine) during wk 6. The four lean cuts from the right side of the carcasses (n = 15/treatment) were dissected into lean and fat tissue. The other cut soft tissue was collected from the jowl, ribs, and belly. Proximate analyses were completed on these three tissue pools and a sample of fat tissue from the other cut soft tissue. Prediction equations were developed for each of five measures of carcass composition: fat-free lean, lipid-free soft tissue, dissected lean in the four lean cuts, total carcass fat tissue, and soft-tissue lipid mass. Ractopamine treatment biases were found for equations in which midline backfat, ribbed carcass, and live ultrasonic measures were used as single technology sets of measurements. Prediction equations from live or carcass measurements underpredicted the lean mass of the RAC-P pigs and underpredicted the lean mass of the CON pigs. Only 20 to 50% of the true difference in fat-free lean mass or lipid-free soft-tissue mass between the control pigs and pigs fed RAC was predicted from equations including standard carcass measurements. The soft-tissue lipid and total carcass fat mass of RAC-P pigs was overpredicted from the carcass and live ultrasound measurements. Prediction equations including standard carcass measurements with dissected ham lean alone or with dissected loin lean reduced the residual standard deviation and magnitude of biases for the three measures of carcass leanmass. Prediction equations including the percentage of lipid of the other cut soft tissue improved residual standard deviation and reduced the magnitude of biases for total carcass fat mass and soft-tissue lipid. Prediction equations for easily obtained carcass or live ultrasound measures will only partially predict the true effect of RAC to increase carcass leanness. Accurate prediction of the carcass composition of RAC-fed pigs requires some partial dissection, chemical analysis, or alternative technologies.     

Estimation of sheep carcass traits by ultrasound technology

Real-time ultrasound technology offers the possibility of estimating carcass characteristics in live animals and represents a potential method for selection of breeding stocks. A total of 745 live lambs born during 2001–2003 into two flocks was used to estimate rib muscle and fat depth by ultrasound. Lambs came from 559 ewes and 97 rams of a fat-tailed breed, known as the ‘Barbarine’ in North Africa. Ultrasound measurements of external fat thickness (UFD) and muscle (UMD), taken at the 12–13th rib and palpation of body conditions (loin and tail scores) were made for 150 days until lambs 520 days old of lamb ages. Main results showed that UMD and UFD had the same trend as live weights from 150 to 240 days old. They decreased from 150 to 200 days old, and then increased. The same trend was seen for loin and tail scores. Average differences in live weights between male and female lambs were 1, 3 and 6 kg at 30, 90 and 120 days old, respectively. The highest muscle depth for males was reached at day 180 and the lowest fat depth was recorded between 180 and 200 days. Average loin scores became greater for males than females from 240 days of age. Male lambs had greater tail scores at all ages, from 150 to 520 days old. Differences became greater for ages more than 180 days, showing that males have a tendency to store more fat in their tails than females. Phenotypic correlation was 0.70 between muscle depth and loin scores, indicating that, at 180 days old, the Barbarine breed has more muscle and less fat. The optimum slaughter age was defined between 180 and 200 days old, producing carcasses with more muscle and less fat. Regression equations estimating carcass traits (UMD, UFD) at 180 and 240 days old were computed.     

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

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

Nutritional approaches to slow late finishing pig growth: implications on carcass composition and pork quality

Although pork producers typically aim to optimize growth rates, occasionally it is necessary to slow growth, such as when harvest facility capacity is limited. In finishing pigs, numerous dietary strategies can be used to slow growth so pigs are at optimal slaughter body weights when harvest facility capacity and/or access is restored. However, the impact of these diets on pork carcass quality is largely unknown. Thus, this study aimed to evaluate the efficacy of dietary strategies to slow growth in late finishing pigs and evaluate their effects on carcass composition and pork quality. Mixed-sex pigs (n = 897; 125 ± 2 kg BW) were randomly allotted across 48 pens and assigned to 1 of 6 dietary treatments (n = 8 pens/treatment): (1) Control diet representative of a typical finisher diet (CON); (2) diet containing 3% calcium chloride (CaCl₂); (3) diet containing 97% corn and no soybean meal (Corn); (4) diet deficient in isoleucine (LowIle); (5) diet containing 15% neutral detergent fiber (NDF) from soybean hulls (15% NDF); and (6) diet containing 20% NDF from soybean hulls (20% NDF). Over 42 d, pen body weights and feed disappearance were collected. Pigs were harvested in 3 groups (14, 28, and 42 d on feed) and carcass data collected. From the harvest group, 1 loin was collected from 120 randomly selected carcasses (20 loins/treatment) to evaluate pork quality traits. Overall, ADG was reduced in CaCl₂, Corn, and 20% NDF pigs compared with CON pigs (P < 0.001). However, ADFI was only reduced in CaCl₂ and 20% NDF pigs compared with CON (P < 0.001). Feed efficiency was reduced in CaCl₂ and Corn pigs compared with CON (P < 0.001). Hot carcass weights were reduced in CaCl₂ pigs at all harvest dates (P < 0.001) and were reduced in Corn and 20% NDF pigs at days 28 and 42 compared with CON pigs (P < 0.001). In general, CaCl₂ and 20% NDF diets resulted in leaner carcasses, whereas the Corn diet increased backfat by 42 d on test (P < 0.05). Loin pH was reduced and star probe increased in CaCl₂ pigs compared with CON pigs (P < 0.05); no treatments differed from CON pigs regarding drip loss, cook loss, color, firmness, or marbling (P ≥ 0.117). Overall, these data indicate that several dietary strategies can slow finishing pig growth without evidence of behavioral vices. However, changes to carcass composition and quality were also observed, indicating quality should be taken into consideration when choosing diets to slow growth.     

Genetic parameters for pork carcass components

Data from 456 homozygous halothane normal purebred Yorkshire, Duroc, and Other-breed pigs from two national progeny testing and genetic evaluation programs were utilized to estimate genetic parameters for carcass components in pigs. Carcass components were cut and weighed according to Institutional Meat Purchase Specifications. Primal cut weights evaluated included 401 Ham (HAM), 410 Loin (LOIN), 405 Picnic shoulder (PIC), 406 Boston Butt (BB), and 409 Belly (BELLY). Individual muscle weights included the inside (INS), outside (OUT), and knuckle (KNU) muscles of the ham, the longissimus dorsi (LD) and psoas major (TEND) of the loin, and the boneless components of both the Boston Butt (BBUTT) and picnic (BPIC). Muscle weights from each primal were summed to yield a boneless subprimal weight (BHAM, BLOIN, BSHLDR), and all boneless subprimals were summed to yield total primal boneless lean (LEAN). Heritability estimates for HAM, LOIN, and BELLY were 0.57, 0.51, and 0.51, respectively. Heritability estimates for BB and PIC were 0.09 and 0.21, respectively. Heritability estimates for the boneless components of each primal were higher than those for the intact primals. Genetic correlations for HAM, LOIN, and PIC with loin muscle area (LMA) were 0.53, 0.78, and 0.70, respectively, and-0.62, -0.51, and -0.60, respectively, with 10th rib off-midline backfat (BF10). Boneless subprimal components were highly correlated with LEAN. Gilts had heavier weights (P < 0.01) than barrows for all boneless subprimals, individual muscles, LEAN, and for all primal cuts except BELLY. Gilts also had less BF10 and more LMA (P < 0.01) than barrows. Duroc pigs had a heavier (P < 0.01) weight for HAM and PIC when compared to Yorkshires. Yorkshire pigs had more (P < 0.01) LOIN weight than did the Durocs. Results suggest primal, boneless subprimal, and individual muscle weights in pigs should respond favorably to selection.     

Genetic parameters for carcass composition and pork quality estimated in a commercial production chain

Breeding goals in pigs are subject to change and are directed much more toward retail carcass yield and meat quality because of the high economic value of these traits. The objective of this study was to estimate genetic parameters of growth, carcass, and meat quality traits. Carcass components included ham and loin weights as primal cuts, which were further dissected into boneless subprimal cuts. Meat quality traits included pH, drip loss, purge, firmness, and color and marbling of both ham and loin. Phenotypic measurements were collected on a commercial crossbred pig population (n = 1,855). Genetic parameters were estimated using REML procedures applied to a bivariate animal model. Heritability estimates for carcass traits varied from 0.29 to 0.51, with 0.39 and 0.51 for the boneless subprimals of ham and loin, respectively. Heritability estimates for meat quality traits ranged from 0.08 to 0.28, with low estimates for the water holding capacity traits and higher values for the color traits: Minolta b*(0.14), L* (0.15), a* (0.24), and Japanese color scale (0.25). Heritability estimates differed for marbling of ham (0.14) and loin (0.31). Neither backfat nor ADG was correlated with loin depth (r(g) = 0.0), and their mutual genetic correlation was 0.27. Loin primal was moderately correlated with ham primal (r(g) = 0.31) and more strongly correlated with boneless ham (r(g) = 0.58). Backfat was negatively correlated with (sub)primal cut values. Average daily gain was unfavorably correlated with subprimals and with most meat quality characteristics measured. Genetic correlations among the color measurements and water-holding capacity traits were high (average r(g) = 0.70), except for Minolta a* (average r(g) = 0.17). The estimated genetic parameters indicate that meat quality and valuable cut yields can be improved by genetic selection. The estimated genetic parameters make it possible to predict the response to selection on performance, carcass, and meat quality traits and to design an effective breeding strategy fitting pricing systems based on retail carcass and quality characteristics.     

Evaluation of alternative techniques to determine pork carcass value.

Three techniques for estimating the value of pork carcasses were evaluated: an optical probe, a real-time ultrasound scanner, and an electromagnetic scanner (EMSCAN). The ability of these techniques to predict carcass value was compared to the predictive ability of actual measures of backfat depth and longissimus muscle area taken with a ruler and a dot grid. Results indicated the EMSCAN model was the best predictor of carcass value. However, the optical probe, ultrasound, and the ruler/dot grid all provided information not contained in the EMSCAN model. The choice among ultrasound, the optical probe, and the ruler/dot grid depends on how the carcass will be used. There is no significant difference between ultrasound and the ruler/dot grid or the optical probe and the ruler/dot grid if the carcass is to be marketed in wholesale primal form, but the ruler/dot grid is superior if the ham and loin are to be sold as lean, boneless products. A model combining the EMSCAN and optical probe readings provided more accurate value predictions than either technique alone. A carcass value matrix for use in pricing pork carcasses was developed using readings from the optical probe. Carcass use has a substantial impact on value differences between fat and lean pigs.     

Evaluation of ultrasound imagery and body shape to predict carcass and fillet yield in farm-raised catfish.

Accurate prediction of meat yield in live animals may allow more efficient genetic improvement of meat yield in farm-raised catfish. An initial trial with 30 channel catfish demonstrated significant correlations among weight-adjusted residuals for muscle area measured from transverse ultrasound images and transverse sections at five locations along the trunk musculature (r = 0.30 to 0.70). Relationships of weight-adjusted residuals for three meat yield traits (carcass, whole fillet, and shank fillet) with weight-adjusted residuals for 15 external body shape measurements and five transverse ultrasound measurements of muscle area were determined for 51 female and 91 male channel x blue catfish backcross hybrids. Compared to males, females had smaller heads; deeper, wider, shorter bodies; larger ultrasound muscle area; and higher meat yield. Correlations between carcass traits and body shape and carcass traits and ultrasound measurements were generally higher for females than for males. Correlations among carcass traits and ultrasound muscle area were typically higher than correlations among carcass traits and external body shape in both sexes. A single ultrasound measurement explained 40 to 50% and 16 to 23% of the variation in meat yield traits of females and males, respectively. The best three-variable model using ultrasound and body shape traits explained 48 to 56% and 31 to 38% of the variation in meat yield traits in females and males, respectively. Differences between males and females for the variability in meat yield traits explained by the models may be related to sexual dimorphism for body shape and fillet yield observed in catfish. Ultrasound has potential for predicting meat yield in live fish, but improved prediction accuracy is needed. Differences in meat yield traits between males and females and among individuals within sexes suggest that selecting for fish with smaller heads and deeper, shorter body shape posterior to the visceral cavity will increase meat yield in catfish.     

Identification of quantitative trait loci for carcass composition and pork quality traits in a commercial finishing cross

A QTL study for carcass composition and meat quality traits was conducted on finisher pigs of a cross between a synthetic Piétrain/Large White boar line and a commercial sow cross. The mapping population comprised 715 individuals evaluated for a total of 30 traits related to growth and fatness (4 traits), carcass composition (11 traits), and meat quality (15 traits). Offspring of 8 sires (n = 715) were used for linkage analysis and genotyped for 73 microsatellite markers covering 14 chromosomal regions representing approximately 50% of the pig genome. The regions examined were selected based on previous studies suggesting the presence of QTL affecting carcass composition or meat quality traits. Thirty-two QTL exceeding the 5% chromosome-wise significance level were identified. Among these, 5 QTL affecting 5 different traits were significant at the 1% chromosome-wise level. The greatest significance levels were found for a QTL affecting loin weight on SSC11 and a QTL with an effect on the Japanese color scale score of the loin on SSC4. About one-third of the identified QTL were in agreement with QTL previously reported. Results showed that QTL affecting carcass composition and meat quality traits segregated within commercial lines. Use of these results for marker-assisted selection offers opportunities for improving pork quality by within-line selection.     

Effects of pea chips on pig performance, carcass quality and composition, and palatability of pork

Pea chips are produced as a by-product when field peas are processed to produce split peas for human consumption. The objective of this experiment was to test the hypothesis that inclusion of pea chips in diets fed to finishing pigs does not negatively influence pig growth performance, carcass composition, and the palatability of pork. A total of 24 barrows (initial BW: 58.0 ± 6.6 kg) were allotted to 1 of 4 treatments and fed early finishing diets for 35 d and late finishing diets for 35 d. A corn-soybean meal (SBM) control diet and 3 diets containing pea chips were formulated for each phase. Pea chips replaced 33.3, 66.6, or 100% of the SBM in the control diet. Pigs were housed individually, and all pigs were slaughtered at the conclusion of the experiment. Overall, there were no differences (P > 0.11) in final BW, ADFI, and G:F of pigs among treatments, but there was a quadratic response in ADG (P = 0.04), with the smallest value observed in pigs fed the control diet. Dressing percentage linearly decreased (P = 0.04) as pea chips replaced SBM in diets, but there were no differences (P > 0.20) among treatments in HCW, LM area, 10th-rib backfat, lean meat percentage, and marbling. Likewise, pH in loin and ham, drip loss, and purge loss were not influenced (P > 0.13) by treatment. However, there was a quadratic response (P = 0.08) in 24-h pH in the shoulder, with the smallest value present in pigs fed the diet, in which 66.6% of the SBM was replaced by pea chips. Subjective LM color and Japanese color score standard were reduced (quadratic, P = 0.03 and 0.05, respectively) and LM b* values and hue angle were increased (quadratic, P = 0.09 and 0.10, respectively) when pea chips replaced SBM in the diets. Ham L* (quadratic, P = 0.04), a* (linear, P = 0.02), b* (quadratic, P = 0.07), color saturation (linear, P = 0.02), and hue angle (quadratic, P = 0.05) were increased when pea chips replaced SBM. However, there were no differences (P > 0.16) in shoulder and fat color. Moreover, cook loss percentage, shear force, juiciness, and pork flavor of pork chops were not different (P > 0.10) among treatments, but tenderness of pork chops linearly decreased (P = 0.04) as SBM replaced pea chips. It is concluded that all the SBM in diets fed to growing-finishing pigs may be replaced by pea chips without negatively influencing growth performance or carcass composition. However, pigs fed pea chips will have pork chops and hams that are lighter, and chops may be less tender if pigs are fed pea chips rather than corn and SBM.