4.1. Statistical Models
For some groups of traits (i.e., growth and carcass traits), multiple covariates were found to be significant during the model development process. The final covariates fitted in the models (
Table 3,
Table 4 and
Table 5) were chosen based on biological and industry considerations, and precedents established in the literature. For example, HCW and LW included age as a covariate, as they are measures of body weight and carcass growth. Another example was adjusting carcass traits for HCW to have the estimates be analyzed by content of lean muscle and fat instead of weight by accounting for lighter or heavier carcasses. For other traits, such as ADG, no covariate was added to the model due to potential confounding factors, as ADG was calculated directly from the age and weight of the animal.
Other studies have used age and cold carcass weight (CCW) as covariates to estimate genetic parameters. Miar et. al [
29] used age and CCW as covariates, while van Wijk et. al [
16] also used CCW. Age is a common fixed effect due to older animals growing larger and naturally having greater body mass and measurement than a younger animal. CCW has been used in other studies to adjust for the size of the carcass, similar to the use of HCW in this study.
Color traits were significantly affected by both AGE and HCW in some instances. In one study [
30], the effect of age on meat color was studied using the Minolta scale. Age was observed to have a significant effect on L* and b*, and one on the ratio between a* and b*, whereas a* was not significant. Other studies have reported that meat becomes redder with age due to the concentration of myoglobin [
31]. Pork color has also been related to the type of muscle fiber present, as lighter meat will often have more Type IIB fibers [
32]. For these reasons, both were considered valid covariates for the statistical models used in this study.
The models in this study do not include some of the typical fixed effects, as seen for estimates of genetic parameters, due to the nature of the datasets. Studies available in the literature commonly use farm, sex, herd-year-season or slaughter plant (in the case of carcass traits) to define their contemporary groups [
13,
15,
33,
34]. However, this study dealt with only female pigs that were raised on the same farms from birth to slaughter and were also slaughtered at the same slaughter plant. Therefore, our models did not consider these factors due to the lack of variability. Past literature has shown that there is a significant difference in results between the sexes in pigs [
35,
36,
37], and as such, further study in this area should be conducted with information from boars and barrows. However, the impact in the genetic parameter estimates is expected to be minimal, as sex is usually accounted for in statistical genetic models.
4.2. Heritabilities
Growth, pork quality and conventional carcass trait heritabilities and variance components are presented in
Table 6. Growth and weight traits had moderate heritabilities with estimates of 0.28 ± 0.07, 0.30 ± 0.06 and 0.26 ± 0.06 for ADG, HCW and LW, respectively. The heritability estimated for ADG in this study is lower than estimates reported in other studies for the same trait (e.g., 0.36 ± 0.07 and 0.47 ± 0.02) in the Duroc breed [
14,
38]. However, it is similar to estimates found for other breeds: 0.24 (no SE presented) in Large White [
39] and 0.27 ± 0.03 in Landrace [
40] pigs. The estimate of 0.30 ± 0.06 for HCW falls within the range seen in the literature (0.24 – 0.36) [
41,
42,
43]. The heritability estimate for LW is in agreement with the body weight by age heritability curve presented by Edwards et al. [
44]. The heritability and additive genetic variance estimates indicate that growth traits are under moderate genetic control and can be improved through direct genetic selection. For instance, high genetic progress for growth traits has been reported in various pig populations [
45,
46,
47].
Pork quality traits had moderate heritabilities with the only low heritability estimated for LNC (0.14 ± 0.05). To the best of our knowledge, a heritability for color score based on the NPPC scale has not been previously reported. There is more information available in the literature for the Japanese color scale, possibly due to the popularity of this color scale. Suzuki et al. [
14] estimated a heritability of 0.18 ± 0.02 for LJPC, while this study found a slightly higher heritability of 0.22 ± 0.05. Meanwhile, another study found a heritability of 0.83 ± 0.12 [
48], which is above the common range observed for meat quality traits in livestock species.
The Minolta color scale (L*, a*, and b*) is used to quantify the color of pork based upon lightness, redness and yellowness values given by a machine. The heritability estimate for L* (0.36 ± 0.07) is within the range of 0.15−0.57 [5, p 358] reported in literature, though it is greater than the value of 0.16 ± 0.02 estimated in another Duroc population [
14]. The heritability estimated for a* (0.30 ± 0.06) is similar to that estimated in a crossbred commercial population (0.36 ± 0.06) [
13], but is different from another estimate of 0.52 ± 0.10 [
40]. Our estimate of b* (0.32 ± 0.06) is different from those found in literature, as it is higher than 0.20 ± 0.06 found by Miar et al. [
13] and less than the 0.94 ± 0.11 found by Newcom et al. [
48]. However, Newcom et al. [
48] stated that the high heritability estimates in their study could have been due to the study design and limited environmental variation.
Pork color scales generally had lower heritability (average of 0.18) compared to the Minolta color measurements (average of 0.33). This difference could be due to human error, as color scores were given by a technician while Minolta L*, a* and b* were measurements taken using a machine. Thus, these measurements would be expected to have less error.
The DLP heritability found here (0.28 ± 0.09) is within the range of what was found in literature [
49], though it is higher than the heritability of 0.14 ± 0.01 estimated by Suzuki et al. [
14] with a Japanese population of Duroc pigs. The main factors that influence DLP are the rate of pH decline postmortem and the ultimate pH of the meat. Additionally, sarcomere length and other environmental factors may also influence the amount of drip loss from a pork product [
50].
Previous heritability estimates for LNM range from 0.16 ± 0.07 to 0.23 ± 0.05 to 0.31 ± 0.12 [
13,
16,
38], which are lower than the estimated 0.42 ± 0.06 found in this study. Heritability for LPHA has a range from 0.07 to 0.39 ([
9] p. 358); the estimate in this study (0.39 ± 0.07) is among the higher estimates. The higher heritabilities found for these traits could be due to the amount of variation in this population of Duroc pigs, as it is comprised of a combination of purebred animals from Europe, Canada and the United States. In addition, there are other factors that influence the heritability estimates, including the statistical method used, variables included in the models, sample size and trait recording.
Conventional carcass traits were generally moderately to highly heritable, with the exception of GI, which had an estimated heritability of 0.00 ± 0.00. This indicates that GI is not under genetic control, as grades are determined by individual packing plants and fluctuate based on plant and time of the year, making genetic prediction difficult. Therefore, GI (as currently measured) is not a trait that should be included in a genetic or genomic evaluation scheme.
A heritability of 0.14 ± 0.05 was found for DP in this study as compared to estimates of 0.32 ± 0.04, 0.40 ± 0.03 and 0.31 ± 0.06 for maternal breeds (Landrace, Large White Sire and Large White Dam, respectively) [
51]. In another study on the Duroc breed, a heritability of 0.22 (no SE presented) was found [
52], which is similar to our estimate, indicating that heritability for dressing percentage in terminal lines is lower than in maternal lines. Additionally, the lower heritability observed in this study could be due to the delay in collecting live weight to carcass weight data, as live weight was measured three days prior to slaughter.
A heritability of 0.38 ± 0.07 was estimated for GBF, which is below the average of the range shown in Clutter [
53]: 0.12 – 0.74. In another population of Duroc pigs, the heritability for backfat was 0.65 ± 0.06 [
54], while in a population of Berkshire pigs it was 0.57 ± 0.06 [
49]. On the other hand, Miar et al. [
13] found a heritability of 0.31 ± 0.06 in a population of crossbred pigs. GLD had a heritability of 0.27 ± 0.06, which falls within the range (0.13 ± 0.06 to 0.41 ± 0.06) estimated by Van Wijk et al. [
16] and Miar et al. [
13]. Similarly, our estimate for LA (0.47 ± 0.08) is average compared to estimates (0.22 to 0.80) found by Miar et al. [
13] and Lo et al. [
38], respectively, and is similar to another estimate in a population of Duroc pigs of 0.45 ± 0.02 [
14]. The heritability for LL was estimated to be 0.32 ± 0.06, which is slightly lower than another estimate of 0.46 ± 0.09 [
55] reported in Large White pigs, but is close to an estimate of 0.39 (no SE presented) in Landrace pigs [
56]. Specific heritability estimates for LC (0.23 ± 0.09) and RMD (0.39 ± 0.07) are scarce, though they can be related to other measurements of the loin, such as LA, which indicate the size of the loin muscle.
The moderate to high heritabilities estimated for traits such as GBF, LA and RMD indicate that substantial progress can be made by selecting for these traits. Due to their higher heritabilities, genetic progress will be faster while also providing more accurate estimated breeding values.
Novel carcass traits had low to high heritabilities (
Table 7). To our knowledge, there have been few estimates of these heritabilities in the literature, especially concerning a purebred terminal line of Duroc pigs. Miar et al. [
13] estimated genetic parameters for similar traits in a crossbred population (Duroc x (Landrace x Large White)) and found estimates of 0.32 ± 0.06, 0.53 ± 0.06, 0.29 ± 0.05, 0.63 ± 0.04, 0.44 ± 0.06, 0.49 ± 0.06, 0.46 ± 0.06, 0.63 ± 0.06 and 0.55 ± 0.06 for SRW, TBLW, TBW, THW, TPW, UBLW, UHW, ULW and USW, respectively, as compared to the estimates received in this study of 0.28 ± 0.06, 0.18 ± 0.06, 0.26 ± 0.05, 0.40 ± 0.07, 0.14 ± 0.05, 0.16 ± 0.05, 0.23 ± 0.06, 0.25 ± 0.06 and 0.22 ± 0.06 for the same traits. The SRW and TBW have similar estimates between the studies, while the remaining traits (TBLW, THW, TPW, UBLW, UHW, ULW and USW) had lower estimates in this study. TW was estimated to have a heritability of 0.30 ± 0.06, which is similar to the estimate of 0.29 ± 0.11 found by Van Wijk et al. [
16]. Neither BL (0.19 ± 0.08) nor BW (0.10 ± 0.04) heritability estimates are similar to those found (0.28 ± 0.08 and 0.49 ± 0.08, respectively) by Kang et. al [
57] in a population of Yorkshire pigs, which could be due to the populational (breed) difference.
To our best knowledge, the current study is the first report of heritability estimates for BLFT, BRW, BLW, BWR, SW and UBW. Thus, the heritability estimates in this study were 0.31 ± 0.11, 0.19 ± 0.05, 0.40 ± 0.06, 0.17 ± 0.12, 0.12 ± 0.05 and 0.15 ± 0.05 for these traits, respectively.
Carcass traits had low to high heritability, with the novel and less studied traits tending towards a low to moderate heritability. These results show that these traits are under some degree of genetic control and can be used for the purpose of selecting for specific gains on the primal and subprimal cuts of the carcass. Additionally, the moderate estimate for BLFT indicates that it may be a candidate for consideration to account for belly quality in a selection index.
4.3. Genetic Correlations Between Growth and Conventional Carcass and Pork Quality Traits
Genetic correlations between conventional carcass traits and pork quality traits can be found in
Table 8. In general, genetic correlations of interest had moderate relationships with the exception of the strong and favorable relationships between DL1 and DL2 with GLD (0.91 ± 0.09 and 0.92 ± 0.09, respectively), LA (0.95 ± 0.05 and 0.96 ± 0.05, respectively), LC (0.82 ± 0.14 and 0.74 ± 0.01, respectively) and RMD (0.80 ± 0.10 and 0.82 ± 0.10, respectively). As DL1 and DL2 are weights of 2.4 cm thick cuts of the loin, these favorable correlations were expected; this group of traits is all related to loin size. Similarly, DL1 and DL2 have moderately unfavorable correlations with GBF (−0.63 ± 0.12 and −0.65 ± 0.13, respectively). As lean loin and backfat depth are known to be inversely correlated [
5,
58], this was an expected finding within this population. However, this relationship is favorable and has been used for decades within the swine industry to decrease backfat depth and increase leanness in swine carcasses.
Both color score measurements (LJPC and LNC) had a moderately unfavorable correlation with DP, (−0.50 ± 0.30 and −0.47 ± 0.30, respectively) which indicates that selection for an increased ratio of internal body contents to lean muscle tissue could lead to paler pork color. A similar correlation was found between LJPC and HCW (−0.36 ± 0.04). However, Miar et al. [
13] found that the Japanese color scale was lowly genetically correlated with HCW. Meanwhile, another study reported that body weight did not have an impact on the loin color [
59]. This indicates that there may be a genetic relationship between these traits, but phenotypically the effect may not be observed. Overall, more studies in independent populations are needed to better understand the genetic correlation between pork color and carcass weight traits.
Backfat depth had moderate correlations of 0.26 ± 0.15, 0.38 ± 0.14 and 0.37 ± 0.15 with L*, a* and b*, respectively. This indicates that selection for backfat is likely to moderately increase the Minolta color score. Inversely, GBF and LNC have a moderate and negative correlation of −0.37 ± 0.21, which indicates that selection for backfat has an inverse relationship with the NPPC color score. The NPPC color scale is based on Minolta L* values, and as NPPC score decreases, the L* value increases. As such, these correlations align.
The moderate and favorable correlation between GBF and LNM of 0.30 ± 0.11, was expected, as these traits have been reported to be positively correlated previously [
9,
60]. Additionally, Suzuki et. al [
14] found a correlation of 0.28 ± 0.03 in another population of Duroc pigs. Similarly, LNM had a moderate and unfavorable correlation with GLD of −0.37 ± 0.13. It is commonly known that increased back fat depth will also increase the amount of marbling in a carcass [
60].
4.7. Genetic Correlations among Pork Quality Traits
Genetic correlations amongst the pork quality traits can be found in
Table 12. Drip loss, ultimate pH (pH at 24 h post mortem) and pork color have strong correlations [
61,
62], as when pH drops too low, pork that is pale in color, soft and squishy in texture and highly exudative (PSE) can occur. Inversely, if ultimate pH is too high, pork that is dark in color, firm in texture and dry in appearance (DFD) can occur [
63]. Both are detrimental characteristics for pork quality and should be avoided. Within this population, several correlations can further define this relationship genetically. Several correlations indicate that if LPHA (−0.76 ± 0.25), LJPC (−0.74 ± 0.24) or LNC (−0.70 ± 0.13) are selected for, DLP will change in an inverse direction. For example, if the breeding goal was to increase the color score, DLP would be expected to decrease. Similarly, if selecting for an increase in L*, DLP will increase due to the high and favorable genetic correlation (0.70 ± 0.21). LPHA had comparable, albeit more moderate, correlations with L* (−0.48 ± 0.11), LJPC (0.67 ± 0.08) and LNC (0.56 ± 0.08), indicating selection for color should generally have a favorable impact upon ultimate pH. Miar et. al. [
13] found similar correlations between L* and DL (0.55 ± 0.24), LPHA and DL (−0.99 ± 0.49), and LPHA and L* (−0.65 ± 0.21).
The favorable correlation between LNC and LJPC of 0.96 ± 0.00 suggests that these traits are nearly genetically identical. L* also shows a high degree of correlation with both LNC (−0.84 ± 0.13) and LJPC (−0.79 ± 0.02). Suzuki et al. [
14] also found a correlation of −0.80 (no SE presented) between LJPC and L*. As the NPPC color score is based on Minolta L* values, this inverse correlation is explainable because the NPPC score decreases as L* increases, and if LNC and LJPC are genetically the same trait, then the Japanese color score should also decrease.
Among the Minolta values, moderate to high correlations were observed. Correlations between L* and a* (0.47 ± 0.13), L* and b* (0.82 ± 0.06) and a* and b* (0.86 ± 0.05) are all positively related. Lee et al. [
49] found a similar estimate for L* and b* of 0.75 (no SE presented) and a* and b* of 0.41 (no SE presented), but a lower correlation between L* and a* of 0.03 (no SE presented). Miar et al. [
13] reported moderate to high correlations among the Minolta color scale (L* and a* were −0.40 ± 0.15, L* and b* were 0.51 ± 0.12, and a* and b* were 0.46 ± 0.13), but estimated an inverse correlation between L* and a*, contrary to this study. However, in general the Minolta color scale has a positive and moderate to high correlation.
Moderate correlations were found between LNM and DLP (−0.30 ± 0.19), L* (0.34 ± 0.13), a* (0.54 ± 0.12) and b* (0.45 ± 0.12). Marbling and drip loss had a low and negative correlation of −0.06 ± 0.19 as estimated previously by Miar et al. [
13]; however, this estimate had high standard error. Miar et al. [
13] and Khanal et al. [
15] also estimated correlations between LNM and the Minolta scale (L* of −0.12 ± 0.16; a* of −0.03 ± 0.15; b* of −0.13 ± 0.17 and L* of 0.11 ± 0.30; a* of 0.02 ± 0.34; b* of 0.17 ± 0.44, respectively), but none of these estimates are similar. The differences among these estimates could be due to the different breeds of animals used in each study. Where this study worked with terminal Durocs, Miar et al. worked with commercial crossbreds and Khanal et al. worked with maternal lines. Additionally, fat does not carry any myoglobin, the primary molecule that provides pigment in meat products, so it would stand to reason that the presence of more marbling may reflect more light, giving a higher L* value [
64]. However, more studies should be done to better understand the genetic correlations between marbling and the Minolta scale within the Duroc breed.
4.8. Genetic Correlations among Novel Carcass Traits
Genetic correlations for novel carcass traits can be found in
Table 13. As would be expected due to their part-whole correlation, the trimmed and untrimmed primal cuts are highly correlated. TBLW and UBLW had a correlation of 0.87 ± 0.04; TBW and UBW had a correlation of 0.80 ± 0.05; UHW and THW had a correlation of 0.88 ± 0.03; USW and TBW had a correlation of 0.75 ± 0.10 and USW by TPW had a correlation of 0.77 ± 0.08. Another study also found positive estimates between these cuts. UHW and THW had a correlation of 0.70 ± 0.01, TBLW and UBLW had a correlation of 0.21 ± 0.03, while TBW and TPW were correlated with USW with values of 0.42 ± 0.03 and 0.47 ± 0.02 [
13]. These correlations are similar in direction, though not in magnitude, and indicate that this study confirms what has been previously observed in the literature. Similarly, UBW and USW had a high and positive correlation of 0.82 ± 0.07, which was not studied by Miar et. al [
13] and may be the first estimate presented between these two subprimal cuts.
The genetic correlation between trimmed and untrimmed primal cuts and subprimal cuts are most commonly moderate but have a few high correlations as well. SRW and BRW had a highly favorable correlation of 0.71 ± 0.14, indicating these two cuts can be selected together in a positive direction. To contrast, TBLW and UBLW tend to be strongly and inversely correlated with TPW (−0.77 ± 0.30 and −0.71 ± 0.37, respectively) and USW (−0.72 ± 0.18 and −0.61 ± 0.20, respectively). TBLW also shares moderately inverse correlations with TBW (−0.60 ± 0.16), THW (−0.33 ± 0.17), TW (−0.42 ± 0.17), BRW (−0.31 ± 0.24) and UBW (−0.55 ± 0.25). UBLW has similar correlations with UBW (−0.51 ± 0.26), TBW (−0.43 ± 0.18) and TW (−0.41 ± 0.18). As the belly would be expected to have more fat than lean mass, these inverse correlations are explainable.
These estimates do not agree with what was found by Miar et al. [
13] where correlations between trimmed and untrimmed primal cuts tend to be either strong or moderate and positive. This may be due to difference in breed composition or the use of different covariates in the statistical analysis. Where this study adjusted all carcass traits with HCW, Miar et al. [
13] adjusted their traits by AGE instead. Therefore, the results may be interpreted slightly differently.
Meanwhile, cuts that contain more lean mass tend to have a moderate and positive relationship amongst each other. THW had positive correlations with TPW (0.37 ± 0.16), BRW (0.44 ± 0.16), and SW (0.47 ± 0.26). UHW has similar correlations with these traits as well. Among the loin traits (ULW, TW and SW) the average correlation was 0.47. TPW and TBW had a correlation of 0.40. These correlations indicate that the genetic relationship between leanness traits will be positive and favorable. Generally, these estimates are in agreement with previous estimates between leaner carcass traits [
13].
The belly flop test was developed to determine the degree of firmness of the fat as a measurement of overall belly quality and is phenotypically related to fatty acid profile [
65]. The distance measured between the ends of the belly are indicative of firmer (wider) or softer (closer) fat. Previous literature has explored the genetic correlation between the belly and fat traits, such as fat percentage in the belly, backfat depth, subcutaneous fat area and inter and intra-muscular fat content [
66]. Recently, pork processors have begun using the belly flop test to test bacon fat quality in packing plants, where firmer fat is preferred for the later stages of processing of bacon. With this knowledge, the genetic definition of this trait could be a valuable asset for swine breeders as well. To our knowledge, this is the first paper reporting the genetic correlations between the belly flop test (and other belly traits) and carcass traits.
Only THW was highly correlated with BLFT (−0.87 ± 0.06), though it is a strong and negative correlation. This indicates that selection for increased lean in the ham may decrease the distance measured between the ends of the bacon in the belly flop test, which is ultimately an undesirable impact upon the belly. Likewise, BLFT is moderately and inversely correlated with BRW (−0.36 ± 0.07), SRW (−0.58 ± 0.15), TBW (−0.47 ± 0.01), TPW (−0.58 ± 0.31), UHW (−0.49 ± 0.14) and UPW (−0.45 ± 0.31). With this unfavorable relationship, if producers consider including BLFT as a trait in a selection index, it may be important to include it alongside other carcass traits such as trimmed or untrimmed primal cuts to prevent any negative impacts upon bacon quality.
One expected correlation found was between BL and BLFT with a correlation of −0.66 ± 0.64, meaning that a longer belly may produce a smaller distance between the ends of the belly during the belly flop test will be closer together. BW and BWR are also closely related (0.87 ± 0.83), indicating they are similar traits and may not need to be measured separately. Using the BLFT to determine quality and BW to determine the preferable width of the belly could be beneficial to selection programs that wish to meet a packer’s preferences, and these results show promise in regard to the degree of genetic correlation between belly traits while also providing a measure of caution when selecting for primal or sub-primal cuts.