Culling before testing in swine: identification of culling strategy and estimation of culling precision.

The aim of this simulation study was to identify culling strategy and to estimate culling precision based on various characteristics available in field data in order to evaluate the ability to detect situations in which adjustment for missing data should be applied in genetic evaluation. Data were simulated for age at 100 kg of live weight (AGE) measured on the farm. Culling was done within (C-W/IN) or over (C-OVER) litters by deleting records from the simulated datasets with culling intensities of .33 and .67. The culling variate (CVAR) used indicated the culling precision and had genetic and phenotypic correlations of 1.00, .75, .50, .25, or .00 with AGE (r(CVAR,AGE)). We were able to distinguish between culling strategies C-OVER and C-W/IN by means of decision rules based on proportion of tested animals per litter. Estimates of r(CVAR,AGE) were obtained from calibration curves for linear regression coefficients of litter average or within-litter variance for AGE on proportion of tested animals, and within- and between-litter variance (V(W) and V(B)) for AGE. Moderate to high r(CVAR,AGE) could be identified with little error by using V(W) or V(B) in C-W/IN and V(W) in C-OVER. Within-litter variance and the weighted average of the estimates from all four characteristics were well able to detect r(CVAR,AGE) values of .50 and higher in both C-W/IN and C-OVER. In conclusion, characteristics of swine field data with missing observations contain information that makes it possible to determine culling strategy, intensity, and precision. This information can be used to decide whether missing data should be replaced by their expected values in genetic evaluation.