Introduction The housing system in the test station from 18 to 22

250 S . Hermesch et al. Livestock Production Science 65 2000 249 –259

1. Introduction The housing system in the test station from 18 to 22

weeks consisted of single penning. Carcase traits The genetic evaluation of farm animals is based on were recorded on the live animal as well as on the multitrait best linear unbiased prediction BLUP carcase and included backfat at P2 site, and backfat procedures which require knowledge of genetic and muscle depth between the third and fourth last correlations between all analysed traits. Estimates of ribs LFDP2, LFD3 4, LMD3 4, FDP2, FD3 4. In genetic correlations might differ between populations addition, weight of the whole back left leg and the due to genetic differences or differences in manage- slash boned ham were recorded as further carcase ment practices. For example, lean meat percentage traits BLW, LMW. Meat quality traits included pH and meat quality traits are unfavourably correlated in recorded 45 min and 24 h after slaughter pH45, populations carrying the halothane gene Cole et al., pH24, colour of the m . longissimus dorsi and m. 1988. In contrast, de Vries et al. 1994 found no multifidus dorsi CLD, CMD, drip loss percentage unfavourable relationship between lean meat per- DLP and intramuscular fat content IMF. The centage and meat quality traits in a halothane free fixed effect models included date of recording all population. In the past, the main emphasis of selec- traits, breed not significant for ADG2, FDINT, tion decisions has been on growth rate, food conver- FCR, pH24 and CMD and parity ADG1, ADG2, sion ratio and lean meat content Ollivier et al., BLW, LMW. Weight of the animal at test begin was 1990. Genetic parameters have been obtained fre- fitted for feed intake and feed conversion ratio. quently for these traits as reviewed by Stewart and Backfat measurements, muscle depth and in- Schinckel 1990. In addition to these traits, meat tramuscular fat content were corrected for weight of quality traits have received greater attention in the animal at slaughter. Litter was fitted for growth breeding programs with the main focus on reduction rate and back leg weight traits as an additional of incidence of pale, soft and exudative PSE and random effect. A further description of the data and dark, firm and dry DFD meat. In Australia, genetic the analysed traits was given in Hermesch et al. parameters have been obtained for growth rate and 2000 along with derivation of the appropriate backfat for a number of herds Klassen, 1992. model and heritability estimates for each trait. However, genetic parameters for further performance Variance components together with standard errors and carcase traits as well as meat quality traits are of genetic correlations were obtained applying an not available yet and selection for meat quality has average information algorithm Johnson and Thomp- only been achieved by selecting against the son, 1995 implemented in DFREML Meyer, 1997. halothane gene. In order to include meat quality Only genetic correlations obtained from the com- traits in breeding decisions knowledge of genetic bined analysis of Large White and Landrace data set parameters is required. The objective of this study are presented since standard errors for genetic corre- was to obtain genetic parameters for meat quality, lations estimated for the individual breeds generally carcase and performance traits as well as reproduc- exceeded differences in genetic correlations between tive traits of the sow. This paper presents genetic and breeds Hermesch, 1996. Genetic correlations were environmental correlations between production, car- obtained by bivariate analyses. The development of case and meat quality traits. the average information algorithm makes multi- variate analyses of variance components feasible. However, comparing bivariate estimates with multi-

2. Material and methods variate estimates of genetic correlations showed no