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Random regression model estimation of genetic parameters for show‐jumping results of Hungarian Sporthorses
Author(s) -
Posta J.,
Malovhr S.,
Mihók S.,
Komlósi I.
Publication year - 2010
Publication title -
journal of animal breeding and genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.689
H-Index - 51
eISSN - 1439-0388
pISSN - 0931-2668
DOI - 10.1111/j.1439-0388.2009.00848.x
Subject(s) - statistics , random effects model , regression , mathematics , jumping , residual , fixed effects model , regression analysis , estimation , biology , panel data , algorithm , medicine , physiology , meta analysis , management , economics
Summary The aim of this study was to estimate the genetic parameters for show‐jumping competition performance of Hungarian Sporthorses using a random regression model. There were 21 210 records from 739 horses collected in Hungary between 1996 and 2004. Performance was expressed as shifted Blom normalized ranks and as the difference between fence height and fault points. The random regression model (RRM) included fixed effects for sex, year, location, and obstacle height and random effects for animal, rider and permanent environment. Regressions for the random effects in the RRM were modelled with Legendre polynomials from first to fifth order of fit. The model focused on performance of horses from 4 to 11 years of age, with heterogeneous residual variances considered. The heritabilities were low to moderate for both variables. Genetic and phenotypic correlations between different ages decreased with increasing distance between the ages.