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J. Anim. Sci. 2002. 80:3099-3106
© 2002 American Society of Animal Science

Genetic parameters for pork carcass components1

D. W. Newcom*, T. J. Baas*,2, J. W. Mabry* and R. N. Goodwin{dagger}

* Department of Animal Science, Iowa State University, Ames 50011 and and {dagger} National Pork Board, Des Moines, IA 50306

2 Correspondence:
109 Kildee Hall (phone: 515-294-6728; fax: 515-294-5698; E-mail:
tjbaas{at}iastate.edu).


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results and Discussion
 Implications
 Literature Cited
 
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.

Key Words: Carcass Composition • Genetic Parameters • Pigs


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results and Discussion
 Implications
 Literature Cited
 
Packers and processors are generally not paid based upon weight or backfat thickness of the carcass, but are paid for the weight of the lean, fat, and by-product components produced from that carcass, and the price of each component varies by weight (Boland, 1998). Brøndum et al. (1998) described the Automatic Fat-O-Meater as a technology to determine how lean is distributed in the carcass and to estimate weight of primal and boneless subprimal cuts in a pork carcass. Real time ultrasound on live pigs has also been investigated as a means to estimate the yield of primal and boneless subprimal cuts in pigs (Sellers et al., 2000). Brorsen et al. (1998) proposed a new carcass pricing system based upon the prices for individual components and showed how component pricing has improved quality of other commodities.

Genetic parameter estimates for backfat and muscle content have been studied extensively and are readily available in the literature (Stewart and Schinckel, 1989; Ducos, 1994; Clutter and Brascamp, 1998). Carcass composition traits are highly heritable and respond very favorably to selection. If payment programs evolve, and packers change from pricing based on carcass composition to a weight of primal and(or) boneless subprimal pricing strategy, producers need to emphasize these traits in their breeding programs.

In order for any selection program to be successful, variance component and genetic parameter estimates for the traits in question must be known. This study was designed to estimate variance components and genetic parameters for pork carcass components, including primal and boneless subprimal cut weights in pigs.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results and Discussion
 Implications
 Literature Cited
 
Data Utilized

Data from two national progeny testing and genetic evaluation programs were evaluated in this study. The first dataset was from 285 homozygous halothane normal purebred Yorkshire (144) and Duroc (141) pigs from two replications of the National Pork Board’s Genetics of Lean Efficiency project (R. N. Goodwin, personal communication). Barrows and gilts from both breeds were delivered to the Minnesota Swine Testing Station, New Ulm, MN, at 10 to 20 d of age. A standard health and vaccination protocol was implemented, and pigs were randomly assigned to pens within breed and sex. All pigs were randomly assigned to one of two target slaughter weights (113.4 and 131.5 kg) upon entry. Pigs were reared in a modified open-front finisher with a partially slotted floor and given 1.5 m2 of pen space per pig. At a pen average of 31.7 kg, pigs were placed on test and given ad libitum access to feed and water.

The second dataset utilized was from 171 homozygous halothane normal purebred Yorkshire (31), Duroc (19), and Other breeds, including Berkshire (52), Chester White (21), Hampshire (9), Landrace (29), Poland China (6), and Spot (4) from two seasons of the National Barrow Show Sire Progeny Test (Goodwin, 2000). Barrows and gilts from all three breed groups were delivered at approximately 8 weeks of age. Pigs were penned by sire group in an open front building with a bedded, solid concrete floor and given 1.4 m2 of pen space per pig. At a pen average of approximately 31.7 kg, animals were placed on test and given ad libitum access to feed and water until they reached a target end weight of 108.9 kg. Data from both projects were combined for analysis.

Animals were weighed off-test weekly upon reaching their target end weight. Pigs were delivered to Hormel Foods/Quality Pork Processors in Austin, Minnesota and harvested after an overnight rest period.

Carcasses entered the cooler forty-five minutes post-mortem. After a two-hour blast chill (-20°C), carcasses were selected for dissection based upon centrality of the dorsal split and lack of trim. At 24 hours post-mortem, the left side of each selected carcass was transported to Geneva Meats, Geneva, Minnesota, for dissection. A total of 456 carcasses were selected from 1,350 pigs slaughtered.

The right side of each carcass was used for measurement of 10th rib off-midline backfat (BF10) and loin muscle area (LMA). Carcasses were ribbed by a cut perpendicular to the vertebral column between the 10th and 11th ribs from the anterior end. Tenth rib off-midline backfat and loin muscle area were measured according to Pork Composition and Quality Assessment Procedures (NPPC, 2000).

The dissection procedure described in Berg et al. (1999) was performed on all selected carcasses 48 hours post-mortem. Primals and boneless subprimals were cut according to Institutional Meat Purchase Specifications (NAMP, 1997). Boneless subprimal cuts and individual muscles were trimmed to 0.0 cm external fat. Primal weights included the 401 Ham (HAM), 410 Loin (LOIN), 405 Picnic shoulder (PIC), 406 Boston Butt (BB), and 409 Belly (BELLY). Each primal was separated into its respective boneless subprimals and muscles. The inside (INS), outside (OUT), and knuckle (KNU) muscles of the ham were summed to yield a boneless ham (BHAM). The longissimus dorsi (LD) and psoas major (TEND) were summed to yield a boneless loin product (BLOIN). The boneless picnic (BPIC) and boneless Boston Butt (BBUTT) were summed to yield a boneless shoulder (BSHLDR). The boneless subprimal components BHAM, BLOIN and BSHLDR were summed to yield total primal boneless lean (LEAN). Summary statistics from the two projects are shown in Table 1Go.


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  		Table 1. Summary statistics for traits in the Genetics of Lean Efficiency project (GLE) and National Barrow Show Sire Progeny Test (NBS)
 
Statistical Analysis

Groups of traits were designated for analysis. The first group included HAM, LOIN, BB, PIC, BELLY, BF10, and LMA. A second group included BHAM, BLOIN, BSHLDR, and LEAN. Primals were also grouped with their respective boneless subprimals, individual muscles, and LEAN.

All traits were first analyzed with a single trait sire model using PROC MIXED of SAS (SAS Inst. Inc., Cary, NC) to test for significant effects in the model and estimate between sire ({delta}s) and residual variance ({delta}e). The initial model was


where Yijklm = observation for a trait, ai = fixed effect of ith breed; bj = fixed effect of jth sex; ck = fixed effect of kth group (where group is defined as a slaughter group within project); abij = fixed effect of the interaction of ith breed with jth sex; wijklm = covariate of off-test weight for ith breed with jth sex; ßij = linear regression coefficient of the dependent variable on off-test weight, wij; sil = random effect of sire l within breed i; and eijklm = random residual error. Distribution of records by breed, gender, and project is shown in Table 2Go. A significance level of P = 0.25 was established as a maximum level for an effect to remain in the model. The interaction of breed with sex was not significant (P > 0.25) and was removed from the final model.


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  		Table 2. Distribution of records by breed and gender in the Genetics of Lean Efficiency (GLE) project and National Barrow Show Sire Progeny Test (NBS)
 
For parameter estimation, pigs were classified into their respective breeds. Within each group of traits, all possible two-trait models were analyzed with the multiple trait animal model option of DFREML (Meyer, 1991) with 4{delta}s and {delta}e from the single trait sire model as initial variance component estimates. Multiple trait analyses by group were performed using averaged variance components from the two-trait analyses as initial variance estimates. The version of DFREML utilized for the multiple trait analyses allowed for the estimation of SE of variance components and genetic parameters by using the average information matrix. All SE for variance component and genetic parameter estimates reported are from the within-group multiple trait analyses.


   Results and Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results and Discussion
Implications
 Literature Cited
 
Gender and Breed Effects

Least squares means by gender and breed for primal and boneless subprimal cut weights, individual muscle weights, LEAN, BF10, and LMA are given in Table 3Go. Gilts had heavier weights (P < 0.01) than barrows for all boneless subprimals, individual muscles, and LEAN, and for all primal cuts, except BELLY. Gilts also had less (P < 0.01) BF10 and more (P < 0.01) LMA than barrows. Barrows had a heavier (P < 0.01) BELLY when compared to gilts. These gender differences for BF10 and LMA are similar to those found in previous studies (NPPC, 1995; Moeller, 1994).


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  		Table 3. Least squares means (at the mean off-test weight) by gender and breed for primal and boneless subprimal cuts, total primal boneless lean, individual muscles, backfat, and loin muscle area
 
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 Durocs. For muscles in the ham, Durocs had more (P < 0.01) INS weight than Yorkshires. Duroc pigs were not different (P > 0.05) from Yorkshires for OUT weight. Durocs could be used in a specialty ham market where two-piece hams (INS plus OUT) are desirable. Yorkshires had heavier (P < 0.05) KNU weights when compared to Duroc pigs. For muscles from the loin, Yorkshire and Duroc pigs did not differ in weight of LD (P < 0.01). Yorkshires had heavier (P < 0.01) weights for TEND when compared to Durocs. No breed differences (P > 0.05) were found for BLOIN, BSHLDR, LEAN, BPIC, and BBUTT.

Regression Coefficients

Regression coefficients for off-test weight by breed for primal and boneless subprimal cut weights, LEAN, BF10, and LMA are shown in Table 4Go. The Other breeds group was included in the analysis, but individual breed results are not reported due to the variation in sample numbers per breed within the group. Regression coefficients by breed group for LOIN, BB, PIC, and BF10 were not different (P > 0.05). Regression coefficients for LMA (P < 0.05), LEAN (P < 0.05), BELLY (P < 0.01), HAM (P < 0.05), BLOIN (P < 0.05), and BHAM (P < 0.01) were not different when comparing the Yorkshire and Duroc breeds. The interaction of off-test weight with sex did not affect weight of primal and boneless subprimal cuts, LEAN, BF10, and LMA (P > 0.05). Lo et al. (1992) reported a regression coefficient of 0.2304 ± 0.0245 for BF10 on off-test weight, similar to this study. They found a smaller regression coefficient for LMA (0.0971 ± 0.173) than in this study.


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  		Table 4. Off-test weight regression coefficients by breed groupa for primal and boneless subprimal cut weights, total carcass boneless lean, backfat, and loin muscle area
 
Backfat and Loin Muscle Area

Heritability estimates and genetic and residual correlations for BF10 and LMA are shown in Table 5Go. Heritability estimates for BF10 and LMA were 0.40 and 0.62, respectively, and the genetic correlation between BF10 and LMA was -0.45. These results are similar to previous literature estimates from Clutter and Brascamp (1998) (average h2 = 0.49 for backfat) and Stewart and Schinckel (1989) (average h2 = 0.52 and 0.47 for BF10 and LMA, respectively, and average rg = -0.35 between BF10 and LMA). Two studies have used National Barrow Show data to estimate genetic parameters for BF10 and LMA. Heritability estimates for BF10 and LMA were 0.72 and 0.76, respectively, as reported by Berger et al. (1994) and 0.79 and 0.71, respectively, by Moeller (1994). Berger et al. (1994) estimated the genetic correlation between BF10 and LMA to be -0.57, while Moeller (1994) estimated the genetic correlation to be -0.68. Results from the National Genetic Evaluation Terminal Line Program (NPPC, 1995), which followed a protocol similar to the Genetics of Lean Efficiency but evaluated crossbred pigs, showed heritability estimates for BF10 and LMA to be 0.46 and 0.48, respectively. The genetic correlation between BF10 and LMA in that study was estimated to be -0.61.


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  		Table 5. Heritabilities and genetic and residual correlations (with SE) from a seven-trait analysis for primal cut weights, backfat, and loin muscle areaa
 
Primals

Heritability estimates and genetic and residual correlations for primal cut weights are given in Table 5Go. Heritability estimates for HAM, LOIN, and BELLY were 0.57, 0.51, and 0.51, respectively. Heritability estimates for the two primal cuts from the shoulder, BB and PIC, were 0.09 and 0.21, respectively. Johansson et al. (1987) estimated genetic parameters for primal cut percentage from European progeny testing programs. They reported heritability estimates for ham percentage (0.28 to 0.43), back percentage, (0.40 to 0.44), streak percentage (0.29 to 0.61), shoulder percentage (0.35 to 0.55), percent meat plus bone in the ham (0.51 to 0.87), and for percent meat plus bone in the back (0.25 to 0.73) for the Landrace, Yorkshire, and Hampshire breeds.

The two largest primal cuts, HAM and LOIN, were highly correlated with each other (0.62). The primal weights for HAM, LOIN, and PIC were negatively associated with BELLY (-0.57, -0.42, and -0.82, respectively) and BF10 (-0.62, -0.51, and -0.60, respectively). The primal weights for HAM, LOIN, and PIC were also positively associated with LMA (0.53, 0.78, and 0.70, respectively). The genetic correlation between BELLY and LMA was -0.23. These results show primal cuts with higher lean to fat ratios (HAM, LOIN, BB, and PIC) are positively associated with lean predictors (LMA) and negatively associated with predictors of fat content (BF10). The primal cut with a lower lean to fat ratio (BELLY) showed opposite relationships with LMA and BF10.

Selection for decreased BF10 has been successful in the Duroc, Yorkshire, Hampshire, and Landrace breeds (NSR, 2001). The results in this study suggest that decreasing BF10 and increasing LMA increases HAM and LOIN but decreases BELLY. This could be detrimental as BELLY is a high value primal cut.

Boneless Subprimals

Heritability estimates and genetic and residual correlations for boneless subprimal cut weights are shown in Table 6Go. Heritability estimates for BHAM, BLOIN, and BLEAN were 0.76, 0.72 and 0.69, respectively. These estimates are higher than those for the primal cuts. Variation in fat deposition within each primal could lead to this higher estimate of heritability when compared to the individual primal.


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  		Table 6. Heritabilities and genetic and residual correlations (with standard errors) from a four-trait analysis for boneless subprimal cut weightsa
 
Genetic correlations among boneless subprimals ranged from 0.73 to 0.92 and were similar to those found among the primals. The genetic correlations of BHAM, BLOIN, and BSHLDR with LEAN were 0.92, 0.90, and 0.89, respectively. These high correlations show that any one of the three boneless components of the carcass could be used to predict LEAN.

Carcass Component Groups

Heritability estimates and genetic and residual correlations for ham components from a six-trait analysis that included HAM, BHAM, LEAN, INS, OUT, and KNU are given in Table 7Go. Heritability estimates for HAM, BHAM, and LEAN were similar to estimates from the primal and boneless subprimal analyses. Heritability estimates for INS, OUT, and KNU were 0.80, 0.80 and 0.61, respectively. The estimates for INS and OUT were higher than those for HAM and similar to those for BHAM.


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  		Table 7. Heritabilities and genetic and residual correlations (with standard errors) from a six-trait analysis for ham component weightsa
 
Genetic correlations among ham components were high. The correlation between HAM and BHAM was 0.89. The genetic correlations of HAM and BHAM with LEAN were 0.79 and 0.94, respectively. The knuckle muscle was more highly correlated with HAM than with BHAM (0.90 vs 0.76). The inside and outside muscles were more highly correlated with BHAM than with HAM (0.88 vs 0.67 and 0.91 vs 0.78, respectively). The correlations of INS, OUT, and KNU with LEAN were 0.84, 0.88, and 0.64, respectively. These results suggest that selection based on INS and OUT (either from prediction equations or real-time ultrasound) could be used to improve LEAN.

Heritability estimates and genetic and residual correlations for loin components from a five-trait analysis that included LOIN, BLOIN, LEAN, LD, and TEND are shown in Table 8Go. The heritability estimates for LOIN and LEAN were similar to estimates from the primal and boneless subprimal analyses. The heritability estimate for BLOIN was lower than the estimate from the boneless subprimal analysis. Heritability estimates for LD and TEND were 0.64 and 0.21, respectively.


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  		Table 8. Heritabilities and genetic and residual correlations (with standard errors) from a five-trait analysis for loin component weightsa
 
The genetic correlations of LOIN and BLOIN with LEAN were 0.97 and 0.90, respectively. This relationship is different from what was seen in the ham where the boneless subprimal was more highly correlated with LEAN than was the primal. The correlation between LOIN and BLOIN is 0.90, which is similar to what was seen in the ham. The genetic correlation was 0.87 between LD and LOIN and 0.86 between LD and LEAN. This shows the importance of the relationship of LD to the lean content of the carcass. The genetic correlation between LD and TEND was 0.35.

Heritability estimates and genetic and residual correlations for weights of shoulder components from a six-trait analysis that included BB, PIC, BSHLDR, LEAN, BBUTT, and BPIC are given in Table 9Go. Heritability estimates for BB, PIC, BSHLDR, and LEAN were similar to estimates from the primal and boneless subprimal analyses. Heritability estimates for BBUTT and BPIC were 0.17 and 0.38, respectively. These estimates were slightly higher than those for the intact primal, similar to what was seen with the other subprimals.


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  		Table 9. Heritabilities and genetic and residual correlations (with standard errors) from a six-trait analysis for shoulder component weightsa
 
The genetic correlations of BB and PIC with BSHLDR were 0.82 and 0.90, respectively. This relationship is lower than what was seen in the loin. The correlation between BB and BBUTT was 0.80, and the correlation between PIC and BPIC was 0.92. The correlation between BPIC and LEAN was higher than the relationship between BBUTT and LEAN (0.87 vs 0.64). Standard errors of these estimates are somewhat high, which means they may not be different from one another.


   Implications
Top
 Abstract
 Introduction
 Materials and Methods
 Results and Discussion
 Implications
Literature Cited
 
With advances in technology to predict primal and boneless subprimal cut weights in pigs, it is only a matter of time before packers and processors begin using these weights in some form of pricing matrix. When these pricing changes occur, geneticists and seedstock producers will need to have genetic parameter estimates available for use in a selection program to improve primal and boneless subprimal weights. The results found in this study show that each of the components of the hog carcass (with the exception of the shoulder) are as highly heritable as 10th rib backfat and loin muscle area, which should mean response to selection for these component traits is possible. These results also suggest that decreasing 10th rib backfat and increasing 10th rib loin muscle area could increase the weight of the ham and loin but decrease weight of the belly. This could, in turn, lower the value of the entire carcass.


   Footnotes
 
1 Journal paper no. J-19675 of the Iowa Agric. and Home Econ. Exp. Sta., Ames, IA, Project no. 3456, and supported by Hatch Act and State of Iowa funds. Back

Received for publication December 19, 2001. Accepted for publication July 22, 2002.


   Literature Cited
Top
 Abstract
 Introduction
 Materials and Methods
 Results and Discussion
 Implications
 Literature Cited
 


Berg, E. P., D. W. Grams, R. K. Miller, J. W. Wise, J. C. Forrest, and J. W. Savell. 1999. Using current on-line carcass evaluation parameters to estimate boneless and bone-in pork carcass yield as influenced by trim level. J. Anim. Sci. 77:1977–1984.[Abstract/Free Full Text]

Berger, P. J., L. L. Christian, C. F. Louis, and J. R. Mickelson. 1994. Estimation of genetic parameters for growth, muscle quality, and nutritional content of meat products for centrally tested purebred market hogs. Pages 51–63 in Research Investment Report 1994. Natl. Pork Prod. Counc., Des Moines, IA.

Boland, M. 1998. Market hog values by carcass components. National Pork Producers Council Quality Lean Growth Modeling Project Symposium. Des Moines, IA. November 17–18, 1998.

Brøndum, J., M. Egebo, C. Agerskov, and H. Busk. 1998. On-line pork carcass grading with the Autofom Ultrasound System. J. Anim. Sci. 76:1859–1868.[Abstract/Free Full Text]

Brorsen, B. W., J. T. Akridge, M. A. Boland, S. Mauney, and J. C. Forrest. 1998. Performance of alternative component pricing systems for pork. J. Agric. Appl. Econ. 302:313–324.

Clutter, A. C., and E. W. Brascamp. 1998. Genetics of performance traits. Pages 427–462 in Genetics of the Pig. Eds. M. F. Rothschild and A. Ruvinsky. CAB International, New York.

Ducos, A. 1994. Parmètres génétiques des caractères de production chez le porc. Mise au point bibliographique. Techni-porc. 17:35–67.

Goodwin, R. 2000. From hog show to meat case. National Hog Farmer. August 1, 2000. P. S3–S5.

Johansson, K., K. Andersson, and J. Sigvardsson. 1987. Evaluation of station testing of pigs. III. Genetic parameters for carcass measurements of partially dissected pigs. Acta Agric. Scand. 37:120–129.

Lo, L. L., D. G. McLaren, F. K. McKeith, R. L. Fernando, and J. Novakofski. 1992. Genetic analysis of growth, real-time ultrasound, and pork quality traits in Duroc and Landrace pigs: I. Breed effects. J. Anim. Sci. 70:2373–2386.[Abstract]

Meyer, K. 1991. Estimating variances and covariances for multivariate animal models by restricted maximum likelihood. Genet. Sel. Evol. 23:67–83.

Moeller, S. J. 1994. Evaluation of genetic parameters for fat and muscle deposition in swine utilizing serial real-time ultrasonic measurements. Ph.D. Diss. Iowa State Univ., Ames.

NPPC. 1995. Genetic Evaluation/Terminal Line Program Results. Ed. R. Goodwin and S. Burroughs. Natl. Pork Prod. Counc., Des Moines, IA.

NPPC. 2000. Pork Composition and Quality Assessment Procedures. Ed. E. P. Berg. Natl. Pork Prod. Counc., Des Moines, IA.

NAMP. 1997. The Meat Buyers Guide. North American Meat Processors Association, Reston, VA.

Sellers, H., T. J. Baas, and R. N. Goodwin. 2000. Prediction of kilograms of boneless primal yield and standardized primal cuts in pigs. J. Anim. Sci.78(Suppl. 1): 70 (Abstr.).

Stewart, T. S. and A. P. Schinckel. 1989. Genetic parameters for swine growth and carcass traits. Pages 77–79 in Genetics of Swine. Ed. L. D. Young. USDA-ARS, Clay Center, NE.


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