Integration of MACE breeding values into Swiss multi-trait test-day model evaluation
Abstract
In this study, we integrated Multiple Across Country Evaluation (MACE) information for Interbull (ITB) bulls into the Swiss Test-day model (TDM). The 9-trait TDM includes test-day records of milk, protein and fat from the first three lactations, while total yield indices submitted to ITB are averages of 305d yields for lactations. A bull was considered to have relevant MACE information if its reliabilities for all indices in MACE were at least 0.1 units higher than its reliabilities from the Swiss TDM. With this integration, the Swiss TDM gained information for round 5,800 bulls with MACE index reliabilities exceeding 0.5.
The integration process had three steps. 1) For selected bulls, the multitrait reversed reliability approximation was used to estimate effective record contributions (ERC) for Swiss and MACE yield indices, based on their respective reliabilities. 2) Yield indices and ERCs were used to calculate multitrait deregressed proofs (DRP) separately for Swiss and MACE evaluation. Correlations between the evaluated indices and pedigree relationships were accounted during the ERC and DRP calculations. 3) Based on the DRPs and ERCs for domestic and MACE indices, pseudo-observations approximating the additional information in the MACE evaluation were calculated for the selected bulls. As a result, for each selected bull a DRP and ERC for milk, protein, and fat were obtained.
The original Swiss TDM describes breeding values using 45 random regression coefficients. The DRP was included in the model as a separate trait, weighted by its ERC. The genetic correlation between pseudo trait and lactation averages of the original traits was assumed to be 1. MACE inclusion improved correlations between MACE and Swiss indices to 0.99 (from 0.78–0.80 for milk, fat, protein). This demonstrates a good alignment between the two evaluation systems. Integration of MACE is now implemented successfully in the Swiss single-step routine genetic evaluation.
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