This study evaluated genetic parameters of direct and maternal effects for calving ease in Hanwoo. A total of 2,102 records for calving ease were collected from 2018 to 2020 from the Hanwoo Genetic Improvement Center in Korea. The calving ease score was rated from 1 to 4 (1=unassisted delivery, 2=assisted easy calving, 3=assisted difficult calving, 4=mechanical or caesarean section) as categorical data, and the data were converted using a truncated normal distribution for linear model analysis. To evaluate the genetic parameters, the birth year-season of calving, the sex of the calf, parity, and the age of the dam at calving were considered as fixed effects, and genetic and maternal effects were considered random effects. The genetic parameters were evaluated using the program BLUPF90. The calving ease scores for male calves, first parity cows, and currently calving cows were much higher than for females, later parities, and past calving cows. The direct genetic variance (0.0164) was higher than the maternal genetic variance (0.0018), and the estimated heritabilities of the direct and maternal effects were 0.055 and 0.006, respectively. The parameters determined here should help with the genetic evaluation of calving ease in Hanwoo.

This study was conducted to find out that how much does it effects as it considered not only animal additive genetic effect but also maternal genetic effect for improving litter traits of pigs. The data of 10,836 records on 2,636 sows in Landrace and 14,463 records on sows in Yorkshire were analyzed which had been measured from 1998 to July 2017 in a nucleus herd of pig population. The traits used on this analysis were total number of born with (TNB2) and without mummy (TNB1) and number of born alive (NBA). Two different multivariate animal mixed models were considered and compared of variance components estimated from these models. The one (Model 1) was set up with assumed to parity, return events and batch effects as fixed and service sire, permanent environment and animal additive genetic effects as random. The other (Model 2) was same with Model 1 except considering maternal additive genetic effects as random. (Co)variance for random effects and genetic parameters were estimated using restricted maximum likelihood method and breeding values as best linear unbiased prediction were estimated using preconditioned conjugate gradient algorithm on each model and breed. From these models, heritability estimates for NBA were about 0.10 and 0.11 on both models in Landrace and Yorkshire, respectively. Forthermore, it was estimated that there were little variations in the maternal genetic effects with roughly 1~2% of total variation. Result from comparing estimated breeding values for each trait between each model, ranking of genetic capability through total breeding values on model 1 and on model 2 showed highly correlated with more than 0.92. Consequently, for improving litter traits, selection based on breeding values by direct genetic effects without considering maternal genetic effects were reccommendable.