Genetic evaluation of Iranian Holstein population using Random Regression models and Cross validation

Abstract

Introduction: The objective of this study was predicting breeding values for sires and
cows at an early stage of cows’ first lactation, to enable early selection of sires.
Materials & Methods: Accuracy of predicted breeding values were investigated using
cross validation method. Data consisted of 2,166,925 test-day records from 456,712 cows
calving between 1990 and 2015. (Co)-variance components and breeding values were
estimated using a random regression test-day model and the average information
Restricted Maximum Likelihood method. Legendre polynomial functions of order 3 were
chosen to fit the additive genetic and permanent environmental effects and homogeneous
residual variance was assumed throughout lactation.
Results: The lowest heritability of daily milk yield was estimated to be 0.14 in early
lactation, and the highest heritability of daily milk yield was estimated to be 0.18 in mid
lactation. Cross validation showed high positive correlation of predicted breeding values
between consecutive yearly evaluations for both cows and sires. Correlation between
predicted breeding values in early lactation (5-90 days) and late lactation (181-305 days)
were 0.77-0.87 for cows and 0.81-0.94 for sires.
Conclusion: These results show that we can select sires according to their daughters’
early lactation before they finish first lactation. This can be used to decline generation
interval and increase genetic gain in Iranian Holstein population.