Using a multitrait animal model BLUP, selection was conducted over seven generations for growth rate (ADG), real-time ultrasound LM area (LMA), backfat thickness (BF), and intramuscular fat content (IMF) to develop a new line of purebred Duroc pigs with enhanced meat production and meat quality. This selection experiment examined 543 slaughtered pigs (394 barrows and 153 gilts) from the first to the seventh generation for meat quality traits. Further, electric impedance and collagen content of loin meat were measured from the fourth to sixth generation. The present study was intended to estimate genetic parameters of the correlated traits of tenderness (TEND), meat color (pork color standard: PCS; lightness = L*), drip loss (DL), cooking loss (CL), pH (PH), electric impedance (IMP), and collagen (COL) of the LM, and the genetic trends of these traits. Respective heritability estimates for IMF, TEND, DL, CL, PCS, L*, PH, IMP, and COL were 0.39, 0.45, 0.14, 0.09, 0.18, 0.16, 0.07, 0.22, and 0.23. Genetic correlations of IMF with ADG and BF were low and positive, but low and negative with LMA. Tenderness was correlated negatively with ADG (-0.44) and BF (-0.59), but positively correlated with LMA (0.32). The genetic correlation between LMA and DL was positive and high (0.64). The genetic correlations of TEND with IMF and COL were low (-0.09 and 0.26, respectively), but a moderate genetic correlation (0.43) between COL and IMF was estimated, suggesting related increases of IMF and connective tissue. Genetic correlations among meat quality traits suggested that when IMF increases, the water holding capacity improves. Genetic trends of meat quality traits showed increased IMF and lighter meat color.

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This study estimated genetic parameters for fatty acids of different sites of fat tissue, meat production, and meat quality traits of Duroc pigs selected during 7 generations for ADG, LM area, backfat thickness (BF), and intramuscular fat (IMF). For this study, 394 barrows and 153 gilts were slaughtered at 105 kg of BW. High heritabilities for C18:0 of outer and inner subcutaneous fat tissue were estimated, respectively, as 0.54 and 0.51; those of intermuscular and intramuscular fat were 0.40 and 0.51, respectively. Genetic and phenotypic correlations of ADG and BF with saturated fatty acids of outer and inner subcutaneous fat were positive, but those with C16:1 and C18:2 were negative, and those with C18:1 were nearly zero. Genetic and phenotypic correlations between LM area and respective fatty acids showed opposite results. Respective genetic and phenotypic correlations of melting points with C18:0 and C18:1 were positive and high, and negative and high, respectively. Genetic correlations between cooking loss and SFA (C14:0, C16:0, and C18:0) of IMF were positive and moderate: 0.56, 0.47, and 0.47, respectively. On the other hand, monosaturated fatty acid of C18:1 was highly and negatively correlated with cooking loss (-0.61). Moreover, high genetic correlation between meat color (pork color standard and lightness) and fatty acid compositions of IMF suggest that the SFA (C14:0, C16:0, and C18:0) were correlated genetically with meat lightness and that unsaturated fatty acid compositions (C18:1 and C18:2) were correlated with meat darkness. Results of this study suggest that the fatty acid composition of adipose tissue is correlated genetically with meat production and meat quality traits.

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Genetic parameters for feed efficiency traits of 380 boars and growth and carcass traits of 1642 pigs (380 boars, 868 gilts and 394 barrows) in seven generations of Duroc population were estimated. Feed efficiency traits included the feed conversion ratio (FCR), and nutritional (RFI(nut)), phenotypic (RFI(phe)) and genetic (RFI(gen)) residual feed intake. Growth and carcass traits were the age to reach 105-kg body weight (A105), loin eye muscle area (EMA), backfat (BF), intra-muscular fat (IMF) and meat tenderness. The mean values for RFI(phe) and RFI(gen) were close to zero and for RFI(nut) was negative. All the measures of feed efficiency were moderately heritable (h(2) = 0.31, 0.38, 0.40 and 0.27 for RFI(nut), RFI(phe), RFI(gen) and FCR respectively). The heritabilities for all growth and carcass traits were moderate (ranged from 0.37 to 0.45), except for BF, which was high (0.72). The genetic correlations of RFI(phe) and RFI(gen) with A105 were positive and high. Measures of RFI were correlated negatively with EMA. BF was more strongly correlated with measures of RFI (r(g) > or = 0.73) than with FCR (r(g) = 0.52). Selection for daily gain, EMA, BF and IMF caused favourable genetic changes in feed efficiency traits. Results of this study indicate that selection against either RFI(phe) or RFI(gen) would give a similar correlated response in carcass traits.

Respiratory disease is the most important health concern for the swine industry. Genetic improvement for disease resistance is challenging because of the difficulty in obtaining good phenotypes related with disease resistance; however, identification of genes or markers associated with disease resistance can help in the genetic improvement of pig health. The purpose of our study was to investigate whether quantitative trait loci (QTL) associated with disease resistance were segregated in a purebred population of Landrace pigs that had been selected for meat production traits and mycoplasmal pneumonia of swine (MPS) scores over five generations. We analysed 1395 pigs from the base to the fifth generation of this population. Two respiratory disease traits [MPS scores and atrophic rhinitis (AR) scores] and 11 immune-capacity traits were measured in 630-1332 animals at 7 weeks of age and when the animal's body weight reached 105 kg. Each of the pigs, except sires in the base population, was genotyped using 109 microsatellite markers, and then, QTL analysis of the full-sib family population with a multi-generational pedigree structure was performed. Variance component analysis was used to detect QTL associated with MPS or AR scores, and the logarithm of odds (LOD) score and genotypic heritability of the QTL were estimated. Five significant (LOD > 2.51) and 18 suggestive (LOD > 1.35) QTL for respiratory disease traits and immune-capacity traits were detected. The significant QTL for Log-MPS score, located on S. scrofa chromosome 2, could explain 87% of the genetic variance of this score in this analysis. This is the first report of QTL associated with respiratory disease lesions.