A canonical correlation analysis of the association between carcass and ham traits in pigs used to produce dry-cured ham

The association between carcass and ham traits in a pig population used to produce dry-cured ham was studied using canonical correlation analysis. The carcass traits examined were hot carcass weight (HCW), backfat thickness (BT) and loin depth (LD), and the ham traits studied were gross ham weight (GHW), trimmed ham weight (THW), ham inner layer fat thickness (HIFT), ham outer layer fat thickness (HOFT), pH (pH) and the Göfo value. Carcass and ham traits are not independent. The canonical correlations (r) between the carcass and ham traits at 130 kg were 0.77, 0.24 and 0.20 for the first, second and third canonical pair, respectively, and were all significant (p < 0.01) by the Wilks test. The corresponding canonical correlations between the three canonical variate pairs for the carcass and ham traits at 160 kg were 0.88, 0.42 and 0.14, respectively (p < 0.05 for all, except the third). The correlations between the traits and their canonical variate showed an association among HCW, GHW and THW, and between BT and HOFT. These results indicate that carcass traits should be used to cull pigs that are not suitable for dry-cured ham production.

Quantitative trait loci for carcass, internal organ and meat quality traits on porcine chromosomes 16, 17 and 18

The objective of this study was to map quantitative trait loci (QTL) on porcine chromosomes 16, 17 and 18 and to determine their association with carcass, organ and meat quality traits. An F2 population was produced by crossing two boars of the naturalized Brazilian Piau breed with 18 commercial females (Landrace x Large White x Pietrain). The population was genotyped for 11 microsatellite markers distributed over the three chromosomes and the results were used to construct a marker-specific linkage map for the population. Analysis of the polymorphic information content showed that the microsatellite markers were adequate for the study of quantitative traits. QTL were identified by regression interval mapping using QTL Express software. QTL not previously described in the literature were detected on chromosome 16, whereas QTL described in other populations were detected on chromosomes 17 and 18. The information from the significant QTL identified here will be useful for future fine-mapping studies and should provide a better understanding of productive phenotypes in pigs.