Impact of data transformation on the heritability estimates of reproductive traits in laying hens

Abstract

Two reproductive traits: percentage of fertilized egg (PFE) and percentage of hatched of set eggs (PHC) of four strains of laying hens (15 339 recorded individuals) over nine generations from pedigree farm were studied. The computations for three type of data sets for each trait (untransformed, arcsinsqrt transformed, probit transformed data) were used to estimate direct and maternal genetic variances within strains. Prior to analysis each observation was divided by the average. Error variance estimates and logarithms of likelihood were taken as comparison criteria. Generally, the reproductive traits are low heritable. Negligible differences between direct heritability estimates of PFE have been registered. However, these estimates obtained from untransformed data were larger than the transformed ones. Generally, smaller residual variances have been received from arcsinsqrt transformed data (in a majority of cases, largest error variances were estimated from probit transformed data). It usually corresponds with the second of the employed criteria.

Bayesian estimates of genetic variance of fertility and hatchability under a threshold animal model

“…In general, the heritabilities estimated for continuous data (expressed as percentage of fertilized eggs) are lower. In the study of Piotrowski and Szwaczkowski (2002) the REML heritability estimates ranged from 0.08 to 0.12 and the so-called total heritability, which includes the variability due to the correlated maternal additive genetic effects, were only slightly higher (from 0.11 to 0.13).…”