Effects of editing of daily feed intake on genetic parameters and predicted breeding values for feed efficiency-related traits in Large White pigs

Abstract

Abstract The main objectives of this study were to evaluate the pre-editing of phenotypic data obtained from electronic feeders in Large White pig breeding company and verify the effect of three data correction methods on the estimated genetic parameters and accuracy of breeding values to improve genetic gains for feed efficiency traits. Feed intake data from 962 Large White boars was used to evaluate the impact of data correction of phenotypic records based on three methods: DS-CSY, adjustment method proposed by Casey; DS-NADJ, without adjustments; DS-ITO, adjustment proposed by Ito. (Co)variance components were calculated for feed conversion ratio (FCR), average daily feed intake (ADFI), and residual feed intake (RFI) based on the datasets generated after editing and correction. The lowest heritabilities (ADFI and RFI) were obtained using the dataset no adjust (DS-NADJ), and the highest was obtained based on the DS-CSY dataset. The genetic correlation between traits ranged from 0.92 to 0.99. Rank correlations of estimated breeding values (EBVs) of all animals across datasets were high (above 0.94) for all traits. The percentage of commonly-selected individuals was high for 10% percentile in all traits (76% to 89%), and the lowest values were found for RFI between datasets in the 5% percentile. The method for pre-editing of daily feed intake (DFI) data from electronic feeders (DS-CSY) resulted in higher heritability and EBV accuracy of the derived traits. The recommended correction method for the data would be the exclusion of 16 error types and adjustment of the error-free DFI.