A comparison of methods to calculate a total merit index using stochastic simulation

Area of Science:

• Animal breeding and genetics
• Quantitative genetics
• Dairy cattle evaluation

Background:

• Dairy cattle breeding aims to improve production and functional traits using estimated breeding values (EBV).
• Multivariate animal models are complex; approximate methods are often used for total merit index derivation.
• Current methods often rely on single-trait models or approximate multivariate approaches.

Purpose of the Study:

• To compare a full multitrait animal model with approximate multitrait models and a selection index approach.
• To evaluate the accuracy and bias of different methods for deriving total merit index in dairy cattle.
• To assess the impact of residual covariances on the performance of these methods.

Main Methods:

• Simulated data for three production and two functional traits in Austrian Brown Swiss cattle.
• Reference method: Multitrait evaluation using all phenotypic data.
• Approximate methods: Multitrait models using yield deviations or de-regressed EBV, and a selection index approach.
• Scenarios with zero, half, or full genetic covariance for residual covariances were tested.

Main Results:

• Approximate multitrait models using yield deviations and de-regressed EBV closely matched the reference method (rank correlations of 1) and were nearly unbiased.
• The selection index method performed well with zero residual covariances but showed decreased correlations and bias with increasing residual covariances.
• EBV derived from the selection index approach were biased when residual covariances were high.

Conclusions:

• Approximate multitrait models, particularly using de-regressed EBV, yield accurate and nearly unbiased results for total merit index.
• Ignoring residual covariances in selection index calculations introduces significant bias, impacting selection accuracy.
• The approximate multitrait approach using de-regressed EBV is suitable for routine genetic evaluations in dairy cattle.