This study was conducted to estimate the relative contribution of dominance genetic effects to efficiency-related traits including Kleiber ratio (KR), efficiency of growth (EF) and relative growth rate (RGR) in Baluchi sheep. To this end, each trait was analysed with a series of 12 animal models which were identical for fixed and additive genetic effects but differed for combinations of dominance genetic and maternal effects. The Akaike's information criterion (AIC) was used to rank models. (Co)variances between traits were estimated using bivariate analyses. For all traits studied, according to AIC values, models containing the dominance genetic effects provided a better data fit than otherwise identical models. By including dominance genetic effects in the model, additive genetic variance did not change, but a significant decrease was observed in the residual variance (24, 19 and 25% for KR, EF and RGR, respectively). Estimates of dominance heritability $( {\boldsymbol h}_{\boldsymbol d}^ 2 )$ were 0.20 ± 0.05, 0.17 ± 0.05 and 0.19 ± 0.07 for KR, EF and RGR, respectively, more than corresponding estimates of additive heritability ${\bf ( }{\boldsymbol h}_{\boldsymbol a}^{\bf 2} {\bf ) }$ as 0.14 ± 0.02, 0.09 ± 0.03 and 0.13 ± 0.02, respectively. Dominance genetic correlations between traits were 0.89 ± 0.17 (KR-EF), 0.86 ± 0.20 (KR-RGR) and 0.93 ± 0.21 (EF-RGR). Additive genetic correlations between traits were 0.84 ± 0.05 (KR-EF), 0.78 ± 0.04 (KR-RGR) and 0.83 ± 0.04 (EF-RGR). The Spearman correlation between additive breeding values including and excluding dominance genetic effects were close to unity either for all animals or top ranked animals. Since presence of dominance genetic effects increased the model power to fit the data, inclusion of these effects in the genetic evaluation models for Baluchi sheep was recommended.

In breeding programmes, the genetic selection process is based on the prediction of animal breeding values, and its results may vary according to the employed selection method. The current study developed an economic selection index for animals of the Angus breed; performed cluster analyses using the breeding values in order to evaluate the genetic profile of the animals candidates to selection, and compared the obtained results between the economic selection index and the cluster analyses. The evaluated traits included weaning weight, 18-month weight, scrotal circumference, fat thickness and ribeye area. Economic values were obtained using bioeconomic modelling, simulating a complete cycle production system of beef cattle breeds in Brazil, and the selection objective were the weaning rate and slaughter weight. The chosen selection index was composed of all of the traits used as selection criteria for the simulated production system. During the cluster analyses, the population was divided into two to four groups, in which the groupings containing potential animals were assessed. The animals of the grouping which was used for comparison with the selection index were identified, and most of the bulls that were included in the index were among the best in the analysed group. These results suggest that the cluster analyses can be used as a tool for the selection of animals to be used as parents for future generations.

The increased demand for animal-derived protein and energy for human consumption will have to be achieved through a combination of improved animal genetic merit and better management strategies. The objective of the present study was to quantify whether differences in genetic merit among animals materialised into phenotypic differences in commercial herds. Carcass phenotypes on 156 864 animals from 7301 finishing herds were used, which included carcass weight (kg), carcass conformation score (scale 1 to 15), carcass fat score (scale 1 to 15) at slaughter as well as carcass price. The price per kilogram and the total carcass value that the producer received for the animal at slaughter was also used. A terminal index, calculated in the national genetic evaluations, was obtained for each animal. The index was based on pedigree index for calving performance, feed intake and carcass traits from the national genetic evaluations. Animals were categorised into four terminal index groups on the basis of genetic merit estimates that were derived before the expression of the phenotypic information by the validation animals. The association between terminal index and phenotypic performance at slaughter was undertaken using mixed models; whether the association differed by gender (i.e. young bulls, steers and heifers) or by early life experiences (animals born in a dairy herd or beef herd) was also investigated. The regression coefficient of phenotypic carcass weight, carcass conformation and carcass fat on their respective estimated breeding values (EBVs) was 0.92 kg, 1.08 units and 0.79 units, respectively, which is close to the expectation of one. Relative to animals in the lowest genetic merit group, animals in the highest genetic merit group had, on average, a 38.7 kg heavier carcass, with 2.21 units greater carcass conformation, and 0.82 units less fat. The superior genetic merit animals were, on average, slaughtered 6 days younger than their inferior genetic merit contemporaries. The superior carcass characteristics of the genetically elite animals materialised in carcasses worth €187 more than those of the lowest genetic merit animals. Although the phenotypic difference in carcass traits of animals divergent in terminal index differed statistically by animal gender and early life experience, the detected interactions were generally biologically small. This study clearly indicates that selection on an appropriate terminal index will produce higher performing animals and this was consistent across all production systems investigated.

Results of studies in dairy cattle about the magnitude of the genotype–environment interaction (GEI) are variable, depending on the definitions of genotype and environment. Therefore, the objective of this study was to determine the magnitude of the interaction of genotype and feeding system (confinement and grazing) in the Mexican genetic evaluation of Jersey cattle for milk yield. The number of lactations and animals in the pedigree used were 5122 and 18 432. An animal model and the MTDFREML program were used to estimate genetic parameters and predict genetic values of the animals. Bivariate analysis was carried out considering the performance of confined and grazing cows as two different traits. Three indicator variables were used to assess GEI: (i) magnitude of the genetic correlation coefficients, (ii) correlation between predicted breeding values and (iii) frequency of coincidence in the ranking of top sires. The magnitude of GEI depended on the choice of the indicator variable. The estimate of genetic correlation coefficient less than unity (0.76; P < 0.05) suggested the presence of biologically important GEI. The differences in phenotypic averages and variances between confinement and grazing systems seem to be the main causes for the genotype by environment interaction detected. However, the correlation coefficient between breeding values from confined and grazing animals (0.96) and the frequency of coincidence between breeding values of common sires within the top 100 in confinement and grazing (0.86) indicated low-to-moderate re-ranking of animals or top sires. In addition, the high correlations between predicted breeding values of Mexican genetic evaluation and the two environments (0.99 and 0.93 for confinement and grazing) indicated that for the two feeding systems, breeding values from national analyses could be safely used.

The objective of this study was to investigate genetic merit of return over feed (ROF), which is a herd profit index defined by CanWest Dairy Herd Improvement as a difference between milk income and feed cost. A multiple-trait (MT) model and random regression model (RRM) were used. The traits analyzed in MT were rearing cost and ROF of the first three lactations. In RRM, a cumulative ROF was fitted as function of age and rearing cost was treated as a correlated trait. Variance components were estimated within a Bayesian framework by Gibbs sampling using a subsample of data. Breeding values were then estimated for 3 041 078 animals using records of 1 951 893 cows. Estimates of heritability for rearing cost from MT and RRM were 0.23 and 0.22, respectively. ROF per lactation and cumulative ROF were negatively correlated with rearing cost. Estimates of heritability of ROF through the first, second and third lactation from MT were 0.27, 0.10 and 0.08, respectively. Estimates of heritability of ROF from RRM increased with age and ranged from 0.08 through 0.31. Estimated breeding values (EBVs) for ROF from MT and RRM were moderately correlated with official EBV for production traits and the Canadian selection index (Lifetime Profit Index). Herd life EBV had −0.07 and 0.19 correlations with EBVs for ROF from MT and RRM, respectively. From both MT and RRM, small favorable correlations were reported between EBVs for ROF and for bone quality and angularity, whereas low unfavorable correlations were reported with EBV for udder depth, front end and chest width. Majority of correlations between EBVs for ROF and for reproduction traits were near 0, with the exception of EBV for gestation length, calf size and calving ease, where small favorable correlations were reported. The ROF is a good indicator of cow profitability despite the fact that it is a simplified profit index that does not account for animal-specific health and reproductive cost. However, because ROF does not account for differences in heritabilities between components of profit, ROF is not recommended to be used for direct selection for profit.

The purpose of this study was to examine the importance of the genetic and maternal environmental factors influencing the 12-week weight (12WW) of Welsh Mountain lambs and to estimate genetic parameters for this trait. Records of 8880 Welsh Mountain lambs born between 1979 and 1995 were analysed. The records were from the nucleus flock of the CAMDA cooperative breeding group. In this flock selection of replacements had been based on a multi-trait index incorporating lamb growth and maternal ability as important objectives and 12WW as one of the selection criteria. Twelve models were examined, all including direct additive genetic variance and various combinations of genetic and environmental maternal effects. The most appropriate model was chosen based on log-likelihood ratio tests. It included appropriate fixed effects, and direct additive, maternal additive, maternal permanent environment and maternal common environment (litter) random effects that defined proportionally 0⋅21 (h2), 0⋅09 (m2), 0⋅06 (pe2) and 0⋅18 (ce2) of the phenotypic variance. Ignoring the additive maternal effect resulted in inflated estimates of direct heritability and ignoring the environmental effects associated with dam inflated the direct and maternal heritabilities. There was no correlation (P < 0⋅05) between the additive direct and additive maternal effects. Additive direct and maternal breeding values increased by 0⋅12 (s.e. 0⋅006) kg/year and 0Ό3 (s.e. 0⋅003) kg/year respectively. The results demonstrate the effective incorporation of selection index methodology in the context of a hill sheep flock and also the importance of several categories of maternal effects.