Estimates of variance components and heritability using different animal models for growth, backfat, litter size, and healthy birth ratio in Large White pigs

This study compared the estimates of variance components using various animal models for Large White pigs. The traits included three production traits, birth weight (BW), age at 100 kg (Age_100), and backfat thickness at 100 kg (BF_100), and two reproduction traits, number of total born (NTB) and the ratio of healthy births (RHB). Five models including or ignoring common litter environmental effects, maternal effects, and the direct-maternal covariance (σam) were used for this study. The results showed that the model including all terms, or including all terms except σam, yielded the best-fitting result. The direct variance and heritability were overestimated when the model ignored all previously listed effects, especially for production traits. When all terms were modeled, the direct heritability estimates ([Formula: see text] ± standard error) were 0.038 ± 0.008, 0.216 ± 0.022, 0.416 ± 0.023, 0.066 ± 0.013, and 0.049 ± 0.007 for BW, Age_100, BF_100, NTB, and RHB, respectively. The common litter effects reached statistical significance for all traits, and maternal heritability reached statistical significance for three production traits. The direct-maternal correlations were negative for all traits but only reached statistical significance for BW. These results indicate that using a more complex model may result in more accurate estimation of variance components in Large White pigs.

Genetic correlations between two strains of Durocs and crossbreds from differing production environments for slaughter traits

The aim of this study was to estimate the genetic correlations between 2 purebred Duroc pig populations (P1 and P2) and their terminal crossbreds [C1 = P1 x (Landrace x Large White) and C2 = P2 x (Landrace x Large White)] raised in different production environments. The traits analyzed were backfat (BF), muscle depth (MD), BW at slaughter (WGT), and weight per day of age (WDA). Data sets from P1, P2, C1, and C2 included 26,674, 8,266, 16,806, and 12,350 animals, respectively. Two-trait models (nucleus and commercial crossbreds) for each group included fixed (contemporary group, sex, weight, and age), random additive (animal for P1 and P2 and sire for C1 and C2), random litter, and random dam (C1 and C2 only) effects. Heritability estimates (+/-SE) for BF were 0.46 +/- 0.04, 0.38 +/- 0.02, 0.32 +/- 0.02, and 0.33 +/- 0.02 for P1, P2, C1, and C2, respectively. Heritability estimates for MD were 0.31 +/- 0.01, 0.23 +/- 0.02, 0.19 +/- 0.01, and 0.12 +/- 0.01 for P1, P2, C1, and C2, respectively. The estimates for WGT and WDA were 0.31 +/- 0.01, 0.21 +/- 0.02, 0.16 +/- 0.01, and 0.18 +/- 0.01 and 0.32 +/- 0.01, 0.22 +/- 0.02, 0.16 +/- 0.01, and 0.19 +/- 0.01, respectively. Genetic correlations between purebreds and crossbreds for BF were 0.83 +/- 0.09 (P1 x C1) and 0.89 +/- 0.05 (P2 x C2), for MD 0.78 +/- 0.05 (P1 x C1) and 0.80 +/- 0.08 (P2 x C2). For WGT and WDA, the correlations were 0.53 +/- 0.08 (P1 x C1), 0.80 +/- 0.10 (P2 x C2), and 0.60 +/- 0.07 (P1 x C1) and 0.79 +/- 0.09 (P2 x C2), respectively. (Co)variances in crossbreds were adjusted to a live BW scale. Compared with purebreds, the genetic variances in crossbreds were lower, and the residual variances were greater. Sire variances in crossbreds were approximately 20 to 30% of the animal variances in purebreds for BF and MD but were 13 to 25% for WGT and WDA. The efficiency of purebred selection on crossbreds, assessed by EBV prediction weights, ranged from 0.43 to 0.91 for line 1 and 0.70 to 0.92 for line 2. When nucleus and commercial environments differ substantially, the efficiency of selection varies by line and traits, and selection strategies that include crossbred data from typical production environments may therefore be desirable.

Estimation of genetic parameters based on individual and group mean records in laying hens

(1) The study was conducted to estimate the heritability, genetic correlations and breeding values of laying hens based on individual records and group mean records. (2) Records of two pure lines from a commercial breeding programme of White Leghorns from three generations housed in single cages and in group cages were used. A total of 8483 and 8817 individual records of lines A and D, respectively, and a total of 1358 (line A) and 1161 (line D) group mean records were analysed. (3) An animal model using Restricted Maximum Likelihood (REML) was used to estimate variance components of individual records. Group mean records were analysed using the sire model, taking heterogeneity of error variance and correlated residual effects into account. Breeding values of sires were estimated based on the BLUP method using a multivariate sire model. Spearman Rank correlations were used to compare sire breeding values estimated from individual records and from group mean records. The traits studied were monthly egg production, cumulative production and egg weight. (4) Heritability estimates based on individual records were higher than from group mean records. Heritabilities for cumulative production records were higher than for monthly production, based on individual as well as group mean records. The estimates of genetic correlations between monthly egg production and cumulative production were moderate to high. Egg production and egg weight recorded individually were highly genetically correlated with those recorded on group means. Sire breeding values estimated from individual records showed high correlations with those from group mean records. (5) Differences in the ranking of sire breeding values estimated from individual vs group mean records were negligible, indicating that no genotype x environment interaction exists. Selection based on individual performance records of laying hens housed in single cages could give a good response on performance of laying hens housed in group cages. Cumulative egg production over periods 1 to 6 is the best trait for the selection programme.