# Genetic parameters of backfat thickness, age at 100 kg and meat quality traits in Pietrain pigs

Jean Pierre Bidanel, A Ducos, F Labroue, R Guéblez, C Gasnier

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Jean Pierre Bidanel, A Ducos, F Labroue, R Guéblez, C Gasnier. Genetic parameters of backfat thickness, age at 100 kg and meat quality traits in Pietrain pigs. Annales de zootechnie, 1994, 43 (2), pp.141-149. 10.1051/animres:19940204. hal-00888966

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Original article

# Genetic parameters of backfat thickness, age at 100 kg and meat quality traits in Pietrain pigs

JP Bidanel <fnref n="1" />, A Ducos <fnref n="2" />, F Labroue <fnref n="2" />, R Guéblez <fnref n="2" />, C Gasnier <fnref n="3" />

(Received 8 June 1993; accepted 6 December 1993)

**Summary** — Genetic parameters were estimated for Pietrain pigs using a derivative-free restricted maximum likelihood procedure applied to a multiple trait individual animal model. Two production traits, *ie* age (AGE) and average backfat thickness (ABT) adjusted to 100 kg liveweight, and 4 meat quality traits, pH of Semispinalis muscle at 45 min *post mortem* (pH₁), ultimate pH (pH_u), drip loss (DL) and cooking loss (CL) of a sample of Semimembranosus muscle, were considered. The data consisted of 5 464 boars tested for AGE and ABT in a single station between 1986 and 1992, of which 1 276 were measured for meat quality traits. The heritabilities of AGE, ABT, pH₁, pH_u, DL and CL are 0.30, 0.45, 0.04, 0.07, 0.04 and 0.24, respectively, with standard errors ranging from 0.02 to 0.03. AGE and ABT exhibit an unfavourable genetic correlation (−0.44 ± 0.05). The genetic correlations between the meat quality traits are high, with the exception of pH₁ which is almost independent of DL and CL. Both pH₁ and pH_u show positive, *ie* unfavourable, genetic correlations with ABT (0.26 ± 0.15 and 0.22 ± 0.12, respectively) and AGE (0.15 ± 0.28 and 0.60 ± 0.21, respectively). DL tends to be unfavourably correlated with ABT (−0.20 ± 0.17), but shows favourable genetic correlations with AGE (0.77 ± 0.19). CL is almost independent of both AGE (0.07 ± 0.12) and ABT (−0.04 ± 0.08).

pigs / genetic parameters / growth / backfat / meat quality

**Résumé** — Paramètres génétiques de l'épaisseur de lard dorsal, de l'âge à 100 kg et de caractères de qualité de la viande chez des porcs Piétrain. Les paramètres génétiques de caractères de production et de qualité de la viande ont été estimés chez des porcs Piétrain à l'aide d'une procédure du maximum de vraissemblance restreinte sans dérivation appliquée à un modèle animal multicaractères. Les caractères considérés sont, d'une part, l'âge (AGE) et l'épaisseur de lard dorsal (ELD) à 100 kg, d'autre part, le pH du muscle Semispinalis mesuré 40 mn post mortem (pH₁), le pH ultime (pH_u), les pourcentages de perte d'exsudat (PR) et à la cuisson (PC) d'un échantillon de muscle Semimembranosus. L'analyse a porté sur un total de 5 464 verrats contrôlés pour AGE et ELD dans une station unique entre 1986 et 1992, parmi lesquels 1 276 ont fait l'objet de mesures de qualité de la viande. Les valeurs d'héritabilité de AGE, ELD, pH₁, pH_u, PR et PC s'élèvent respectivement à 0,30 ; 0,45 ; 0,04 ; 0,07 ; 0,04 et 0,24, avec des erreurs standard de 0,02 à 0,03. Une corrélation génétique défavorable (−0,44 ± 0,05) est obtenue entre AGE et ELD.

<footnote n="1">¹ INRA, Station de Génétique Quantitative et Appliquée, Centre de Recherche de Jouy-en-Josas, 78352 Jouy-en-Josas Cedex;</footnote>

<footnote n="2">² Institut Technique du Porc, Pôle Amélioration de l'Animal, BP 3, 35650 Le Rheu;</footnote>

<footnote n="3">³ UCAGENOF, Erin, 62134 Anvin, France</footnote>
Les caractères de qualité de la viande sont fortement corrélés entre eux, à l'exception de $pH_1$, qui est pratiquement indépendant de PR et de PC. $pH_1$ et $pH_u$ présentent des corrélations génétiques défavorables avec AGE (respectivement $0,26 \pm 0,15$ et $0,22 \pm 0,12$) et ELD (respectivement $0,15 \pm 0,28$ et $0,60 \pm 0,21$). PR tend à être lié de façon défavorable avec ELD ($-0,20 \pm 0,17$), mais est génétiquement lié de façon favorable avec AGE ($0,77 \pm 0,19$). CL est pratiquement indépendant de AGE ($0,07 \pm 0,12$) et de ELD ($-0,04 \pm 0,08$).

*porcin / paramètres génétiques / croissance / épaisseur de lard dorsal / qualité de la viande*

## INTRODUCTION

Accurate estimates of genetic parameters are essential for predicting breeding values and evaluating alternative breeding plans. Numerous estimates of genetic parameters for growth, carcass and to a lesser extent meat quality traits in the Large White (or Yorkshire) and Landrace breeds are available in the literature (see reviews by Ollivier and Sellier, 1982; Sellier, 1988; Stewart and Schinckel, 1988; Hovenier et al, 1993; Ducos, 1994). Conversely, estimates of genetic parameters in the Pietrain breed are scarce and generally based on relatively limited numbers of animals. More-over, with the exception of Sönnichsen et al (1984a,b), they only deal with growth and carcass traits (Hanset and Van Snick, 1972; Kintaba et al, 1981; Lagrange, 1982; Schirvel and Hanset, 1988). Meat quality is becoming increasingly important in pig production. The processing quality of meat has been included in the selection goal and the selection criteria for several years in France. Predictors of the technological yield of cured-cooked ham processing, ie pH, reflectance and water-holding capacity (Jacquet et al, 1984), are measured on pig carcasses 24 h post mortem. However, some abattoirs cannot keep carcasses for 24 h. In such cases, the measurement of the curing cooking yield on a small sample of meat has been suggested (eg, Naveau et al, 1985). The purpose of this study was to estimate genetic parameters in a Pietrain population for growth rate, backfat thickness and meat quality traits measured on a sample of Semimembrano-

sus muscle using a restricted maximum likelihood (REML) procedure (Patterson and Thompson, 1971) applied to a multiple trait individual animal model.

## MATERIALS AND METHODS

### Data

The data were obtained from a Pietrain testing station located in the north of France (Erin, Pasde-Calais) belonging to the Ucagenof selection scheme. The performance data of 5 464 male pigs tested between 1986 and 1992 were used in the analysis. The meat quality measurements began in 1989, and only 1 276 of the pigs were slaughtered and measured for meat quality traits. The pigs originated from 3 Pietrain selection herds with synchronized batch farrowing. Hence, the pigs were tested in batches, which systematically included animals from all 3 herds. All the male pigs from the 3 herds were tested. The structure of the data is shown in table I.

Piglets from each batch entered the testing station at around 35 d of age. They were kept in a postweaning unit until 75 d of age and then allotted to fattening pens of 15-18 animals, where they stayed until the end of the test at 100 kg liveweight. They were fed ad libitum during the whole test period with a commercial diet formulated to contain 3 100 kcal of digestibility energy and 17-18% crude protein. At the end of the test, pigs were weighed and backfat thickness was measured ultrasonically on each side of the spine, 4 cm from the mid-dorsal line at the shoulder, the last rib and the hip joint. Age (AGE) and average backfat thickness (ABT = mean of the 6 ultrasonic measurements) were adjusted to 100 kg liveweight using the equations established by Jourdain et al (1989). The pigs chosen for the meat
<table><caption>**Table I.** Structure of the data set analysed.</caption><thead><tr><th rowspan="2"></th><th colspan="2">Traits measured</th></tr><tr><th>Production</th><th>Meat quality</th></tr></thead><tbody><tr><td>Pigs tested</td><td>5 464</td><td>1 276</td></tr><tr><td>No of sires</td><td>175</td><td>43</td></tr><tr><td>No of dams</td><td>651</td><td>141</td></tr><tr><td>No of batches</td><td>40</td><td>-</td></tr><tr><td>No of tested pigs/batch</td><td>136.6</td><td>-</td></tr><tr><td>No of slaughter dates</td><td>-</td><td>60</td></tr><tr><td>No of tested pigs / slaughter date</td><td>-</td><td>21.27</td></tr><tr><td>No of litters</td><td>1 579</td><td>619</td></tr><tr><td>No of tested pigs/litter</td><td>3.46</td><td>2.06</td></tr></tbody></table>

quality study were litter-mates of pigs selected for breeding. They were slaughtered at a commercial abattoir 40 km away. Pigs were killed by electrostunning and severing of the *vena cava*. About 45 min after slaughter, the pH of the *Semispinalis* muscle (pH₁) was measured and a sample of about 100 g of *Semimembranosus* muscle was taken from the right-hand side of the carcass. The sample were weighed and hung for 48 h in a plastic bag at 0–4°C. The meat sample was not allowed to touch the bottom of the bag in order to ensure a correct drip. It was then weighed again, measured for pH (pH_u), placed inside another plastic bag in water at 75°C and cooked for 30 minutes. After cooking, the sample was finally wiped and weighed. Drip loss (DL) and cooking loss (CL) were computed as:

$$DL = 100 \times (X_1 - X_2) / X_1$$

$$CL = 100 \times (X_2 - X_3) / X_2$$

where X₁ and X₂ are the weights of the fresh sample at 45 min and 48 h after slaughter, respectively, and X₃ is the weight of the cooked sample.

## Model

Genetic effects, common litter environmental effects and residual variance and covariance components were estimated using a derivative-free REML algorithm (Graser *et al*, 1987) applied

to a multiple trait individual animal model (IAM). The model for each trait was as follows:

$$y_{ijkl} = \mu + H_i + B_j + bx_{ijkl} + c_{jk} + a_{ijkl} + e_{ijkl}$$

where $y_{ijkl}$ = observation of the *ijkl* th pig; $\mu$ = over-all mean; $H_i$ = fixed effect of the i th herd of origin (for AGE and ABT only); $B_j$ = fixed effect of the j th batch (or slaughter date for meat quality traits); b = regression of $y_{ijkl}$ on weight at slaughter $x_{ijkl}$ (for meat quality traits only); $c_{jk}$ = random effect of the k th litter in the j th batch; $a_{ijkl}$ = random additive genetic effect of the l th pig of the i th sex in the jk th litter; and $e_{ijkl}$ = random residual associated with the *ijkl* th observation. Location and dispersion parameters for the random effects have the same structure as in Ducos *et al* (1993). The analyses were performed using the derivative-free multiple trait REML procedure described by Groeneveld (1991). For computational reasons, the calculations were done pairwise. Approximate standard errors of variance components and genetic parameters were obtained from an approximation of the Hessian matrix as described by Ducos (1994).

## RESULTS

Means and phenotypic standard deviations for the 6 traits studied are shown in table II. Preliminary univariate analyses indicated that common litter effects (c²) were close to zero (less than 1% of phenotypic standard deviation) for pH₁, pH_u and DL. As a consequence, the common litter variance for these 3 traits was set to zero in multivariate analyses. The litter covariance was also set to zero for all pairs of traits. The herd of origin had a significant effect on AGE and ABT (about 0.2 phenotypic standard deviations between the extremes for both traits). Conversely, the herd of origin effect did not significantly affect meat quality traits and was hence excluded from final analyses for these traits.

Estimates of heritability and common litter effect are shown in table III. Heritability estimates are 0.30 and 0.45, for AGE and ABT respectively. Meat quality traits have
<table><caption>**Table II.** Means and phenotypic standard deviations ($\sigma_p$) for the 6 traits studied.</caption><thead><tr><th>Trait</th><th>Mean</th><th>$\sigma_p$</th></tr></thead><tbody><tr><td>Age at 100 kg (d)</td><td>177.1</td><td>12.2</td></tr><tr><td>Average backfat thickness at 100 kg (mm)</td><td>6.4</td><td>1.2</td></tr><tr><td>pH<sub>1</sub> of <i>Semispinalis</i> muscle <sup>a</sup></td><td>6.22</td><td>0.23</td></tr><tr><td>Ultimate pH (pH<sub>u</sub>) <sup>b</sup></td><td>5.42</td><td>0.11</td></tr><tr><td>Drip loss (DL) (%) <sup>b</sup></td><td>2.1</td><td>0.7</td></tr><tr><td>Cooking loss (CL) (%) <sup>b</sup></td><td>22.2</td><td>2.6</td></tr></tbody></table>

low heritability (0.04–0.07), with the exception of CL, which has a medium heritability value (0.24 ± 0.03). Significant common litter effects are found for AGE and ABT (12 and 9% of phenotypic variance respectively). Conversely, the $c^2$ value for CL is low and non-significant (0.02 ± 0.02).

Estimates of genetic and phenotypic correlations are shown in table IV. AGE and ABT exhibit a rather marked genetic antagonism (–0.44 ± 0.05). The phenotypic correlations between meat quality traits are rather low. The genetic correlations are higher, with the exception of $pH_1$, which is

genetically almost independent from DL and CL. DL and CL are positively correlated (0.75 ± 0.19) and show negative genetic correlations with $pH_u$ (respectively, –0.99 ± 0.15 and –0.72 ± 0.18). The two pH measurements exhibit moderately positive correlations (0.49 ± 0.29). Unfavourable genetic correlations are found between ABT and the 4 meat quality traits. AGE also shows positive, ie unfavourable, genetic correlations with pH measurements, particularly $pH_u$ (0.60 ± 0.21), but is favourably related to DL (0.77 ± 0.19).

## DISCUSSION

### Methodology

The REML procedure using an animal model is now regarded as the method of choice to estimate genetic parameters for traits that can be described by linear models in animal breeding. The growing interest in this methodology is due to its desirable statistical and genetic properties (Harville, 1977). In particular, REML appears to be rather robust to the effects of selection, provided that all the information describing the selection process is included in the analysis

<table><caption>**Table III.** Estimates of heritability and common environmental effects.</caption><thead><tr><th>Trait</th><th>$h^2 \pm se_a$</th><th>$c^2 \pm se_a$</th></tr></thead><tbody><tr><td>Age at 100 kg</td><td>0.30 ± 0.02</td><td>0.12 ± 0.01</td></tr><tr><td>Average backfat thickness</td><td>0.45 ± 0.02</td><td>0.09 ± 0.01</td></tr><tr><td>pH<sub>1</sub> of <i>Semispinalis</i> muscle <sup>b</sup></td><td>0.04 ± 0.03</td><td>—</td></tr><tr><td>Ultimate pH (pH<sub>u</sub>) <sup>c</sup></td><td>0.07 ± 0.03</td><td>—</td></tr><tr><td>Drip loss (DL) <sup>c</sup></td><td>0.04 ± 0.03</td><td>—</td></tr><tr><td>Cooking loss (CL) <sup>c</sup></td><td>0.24 ± 0.03</td><td>0.02 ± 0.02</td></tr></tbody></table>

<footnote><sup>a</sup> Measurement 45 min *post mortem*; <sup>b</sup> measured on a sample of *Semimembranosus* muscle.</footnote>

<footnote><sup>a</sup> Heritability ($h^2$) and common environmental effect ($c^2$) ± standard error; <sup>b</sup> measured 45 min *post mortem*;</footnote>

<footnote><sup>c</sup> measured on a sample of *Semimembranosus* muscle.</footnote>
<table><caption>Table IV. Estimates of genetic (above diagonal) and phenotypic (below diagonal) correlations in the Pietrain breed.</caption><thead><tr><th>Trait</th><th>Age at 100 kg</th><th>Average backfat thickness</th><th>pH<sub>1</sub> of Semispinalis muscle</th><th>Ultimate pH (pH<sub>1</sub>)<sup>a</sup></th><th>Drip loss (DL)<sup>a</sup></th><th>Cooking loss (CL)<sup>a</sup></th></tr></thead><tbody><tr><td>Age at 100 kg</td><td>-</td><td>-0.44 ± 0.05</td><td>0.15 ± 0.28</td><td>0.60 ± 0.21</td><td>0.77 ± 0.19</td><td>0.07 ± 0.12</td></tr><tr><td>Average backfat thickness</td><td>-0.22 ± 0.03</td><td>-</td><td>0.26 ± 0.15</td><td>0.22 ± 0.12</td><td>-0.20 ± 0.17</td><td>-0.04 ± 0.08</td></tr><tr><td>pH<sub>1</sub> of Semispinalis</td><td>-0.05 ± 0.05</td><td>0.00 ± 0.03</td><td>-</td><td>0.49 ± 0.29</td><td>0.01 ± 0.24</td><td>0.04 ± 0.20</td></tr><tr><td>Ultimate pH (pH<sub>1</sub>)<sup>a</sup></td><td>0.26 ± 0.05</td><td>0.03 ± 0.03</td><td>0.01 ± 0.02</td><td>-</td><td>-0.99 ± 0.15</td><td>-0.72 ± 0.18</td></tr><tr><td>Drip loss (DL)<sup>a</sup></td><td>0.17 ± 0.05</td><td>-0.01 ± 0.03</td><td>-0.10 ± 0.02</td><td>0.00 ± 0.03</td><td>-</td><td>0.75 ± 0.19</td></tr><tr><td>Cooking loss (CL)<sup>a</sup></td><td>-0.22 ± 0.05</td><td>-0.06 ± 0.03</td><td>-0.10 ± 0.03</td><td>-0.20 ± 0.03</td><td>0.34 ± 0.03</td><td>-</td></tr></tbody></table>

<footnote><sup>a</sup> Measured on a sample of *Semimembranosus* muscle.</footnote>
(Meyer, 1990). In pigs, this implies the use of multivariate models, as selection is gene-
rally based on several traits. In the present
case, the animals were selected using an
index involving AGE and ABT. Hence, the
fact that pigs slaughtered for meat quality
measurements were not chosen at random
could be taken into account by 3-trait IAM-
REML models including AGE and ABT. In
fact, only 2-trait analyses could be perfor-
med, due to the huge computational requi-
rements of IAM-REML procedures. As a
consequence, the effects of selection were
fully accounted for in the analysis of AGE
and ABT, but were only partly treated in the
other analyses. However, the lack of varia-
bility between estimates of variance com-
ponents obtained from the different 2-trait
analyses suggests that the bias should be
very limited.

An important assumption usually made when estimating variance components is that the traits analysed exhibit purely polygenic variation. This is probably not true in the present case, as the halothane sensitivity gene (Halⁿ) is known to be segregating in most Pietrain populations, with a very high frequency of the halothane sensitivity allele. A segregating major gene in a population generally affects the heritability and the genetic correlations (Smith and Webb, 1981). The effect of the gene on genetic parameters depends on the polygenic variability, the additive and dominance effects and the allele frequency at the corresponding locus. The Halⁿ gene is known to affect lean yield, feed efficiency, appetite, survival and meat quality traits such as pH₁, DL and to a lesser extent CL (Webb *et al*, 1985; Sellier, 1988). However, due to the very high frequency of the halothane sensitivity allele in the French Pietrain population (more than 95% according to first estimations using a molecular test; Sellier, personal communication) the impact of the gene on genetic parameters is likely to be small, except if the halothane sensitivity allele is recessive.

For instance, consider 2 traits with a poly-
genic heritability of 0.3, a genetic correla-
tion of zero and an additive genetic effect
of the gene of 0.5 standard deviation (ie a
difference of 1 standard deviation between
homozygotes). With no dominance, the
overall heritability would be 0.22 and a gene-
tic correlation of 0.11 would be generated
by the major gene. The corresponding
values would be 0.26 and 0.30 in the case of
complete dominance. The REML-animal
model methodology used in the present
study only estimates the genetic variability
due to the combined effects of the major
gene and the polygenes. Segregation ana-
lysis methods would allow the separation
of genetic variation related to a major gene
from polygenic variation (Le Roy *et al*, 1989,
Knott *et al*, 1992). These methods are unfor-
tunately computationally very demanding,
so that their use is currently limited to simple
pedigrees. Their use becomes unnecessary
if the genotype of the animals at the Halⁿ
gene is known, which has become possible
with the recent identification of the ryano-
dine receptor gene and the elaboration of
a molecular test (Fujii *et al*, 1991).

Genetic parameters

The heritability estimates for AGE and ABT are slightly larger than average literature values for age at 100 kg and backfat thickness in pigs (Stewart and Schinckel, 1988; Ducos, 1994). There was apparently no published heritability value for age at 100 kg in the Pietrain breed. The only comparable estimate concerns lifetime daily gain: Sönrichsen *et al* (1984a) reported heritability values of 0.16–0.24 in a joint analysis of Pietrain and Belgian Landrace data. The heritability of ABT is larger than the only previously available estimate for ultrasonic backfat thickness in the Pietrain breed (0.20 ± 0.06, Lagrange, 1982). Hanset and Van Snick (1972) and Kintaba *et al* (1981)
obtained similar heritability estimates for carcass backfat thickness in centrally tested Pietrain pigs. Conversely, a larger value (0.61 ± 0.08) was reported by Schirvel and Hanset (1988).

The heritability values are also larger than (for AGE) or comparable to (for ABT) values obtained in on-farm tested Large White and Landrace pigs in France (Bidanel et al, 1994). Moreover, compared with the values obtained in Large White and Landrace breeds, the phenotypic variance was almost twice as large for AGE and 50% lower for ABT (Bidanel et al, 1994). Hence, the genetic variability in the French Pietrain population appears to be more important for growth rate and less important for backfat thickness than in French Large White or Landrace populations.

The heritability estimate for CL is comparable to average literature values (Sellier, 1988; Ducos, 1994) and shows that an important genetic variation for meat quality exists in the Pietrain breed. Conversely, heritability estimates of pH₁, pHₐ and DL are lower than usual values. These low values may indicate a low genetic variation for these traits, but could also be due to insufficiently standardized slaughter, sample collection or measurement conditions. The choice of a 'red' muscle, *ie* the Semispinalis muscle, which exhibits a much lower pH fall after slaughter, might also be associated with a lower genetic variation of pH₁.

The genetic antagonism between AGE and ABT tends to be more pronounced than indicated by average literature values (around -0.20, Stewart and Schinckel, 1988; Ducos, 1994) and the estimates of Kintaba *et al* (1981) and Schirvel and Hanset (1988) in the Pietrain breed. This unfavourable relationship tends to decrease the efficiency of selection for growth rate and carcass lean content in the Pietrain breed. The sign and the extent of the genetic correlations between production and meat quality traits are still debated. The recent reviews of Hovenier

*et al* (1993) and Ducos (1994) show that growth rate or backfat thickness are on average genetically independent from the ultimate pH of the meat, but unfavourably related to meat colour and water-holding capacity. However, large variations exist between individual estimates, which are probably partly due to the population studied and, in particular, to the frequency of alleles at the *Hal*ⁿ locus in the population. As emphasized by Sellier (1988), growth rate is unfavourably related to meat quality traits in the Large White, but not in the Landrace breed. On the other hand, the antagonism between meat quality and carcass lean content is stronger in highly muscular breeds, as shown by Sönnichsen *et al* (1984b) and Cole *et al* (1988). The antagonism between ABT and meat quality traits obtained in the present study is in agreement with these results, even if the most heritable meat quality trait, *ie* CL, exhibits a rather low genetic correlation with ABT. The genetic relationships between AGE and meat quality traits are more unusual, particularly the large positive correlations with pHₐ and DL. The very low phenotypic and genetic correlations between pH₁ and DL are also rather unexpected. However, these results may be due to the relatively low precision of estimates of genetic correlations or to the low additive genetic variance for pHₐ and DL, which tends to enlarge any variation of genetic covariances.

## CONCLUSION

This study supports previous results from other breeds indicating that meat quality traits show unfavourable genetic correlations with performance traits. As a consequence, any attempt to prevent further deterioration of meat quality in the Pietrain breed will require the inclusion of meat quality measurements in the selection criterion. However, it is necessary to accurately quan-
tify genetic variation due to the halothane sensitivity gene and residual polygenic variability to be able to define optimal selection strategies.

## ACKNOWLEDGMENTS

The authors are indebted to E Groeneveld and D Boichard for providing the variance component programs. The technical assistance of JY Flého and H Lagant and the useful comments of P Sellier are also gratefully acknowledged.

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