Multivariate outlier detection in genetic evaluation in Nordic Jersey cattle

Abstract Text: A procedure was developed for detection of multivariate outliers based on an approximation for Mahanalobis Distance (MD) and was implemented in the Nordic Jersey population. Evaluations are carried out by Nordic Cattle Genetic Evaluation (NAV), who uses a 9 trait model for milk, protein and fat in the first 3 lactations. It is based on the phenotypic correlation structure as a function of days in milk (DIM) and on computation of trait means and standard deviations (SDs) within classes of production year (PY), lactation and days in milk (DIM). For each record in the data, MD is computed based on trait means and co-variance matrix for the actual PY, lactation and DIM. Accuracy of EBV’s is improved for animals having extreme outlier record(s) deleted compared to EBV’s based on data not filtered for MD.

Keywords: Mahalanobis distance, Genetic evaluation, Multivariate outlier