The aim of the study was to estimate genetic parameters for show-jumping competition performance using random regression model. Show-jumping competition results collected between 1996 and 2009 were analyzed. The database contained 272 951 starts of 8020 horses. Identity number and gender of the horse, rider, competition date, the level of the competition and placing were recorded in the database. Competition levels were categorized into five groups. Weighted – competition level used – square root transformed placing was used to measure performance of horses. The random regression model included fixed effects for gender, year and place of competition, and random effects for rider, animal and permanent environment.
Later performance of show-jumping horses measured with weighted square root ranks is less influenced by rider and permanent environmental effects than performance at the beginning of a horse’s sporting career. Heritability increased continuously from 6.3 years of age (2296 age in days), values were in the range of 0.07 and 0.37. Higher heritability was found in later ages. Weak genetic and phenotypic correlation was found between the early 4–5–6 years of age and older (7, 8, 8+) age classes. From 8.5 years of age (3132 days old) there were strong genetic and phenotypic correlations between neighboring age groups. For the same age classes moderate and strong genetic and phenotypic correlation was found. Genetic correlation between 13.5 years of age and older horses was very strong.
The aim of the study was to compare different fitted models for show-jumping results of sporthorses and to estimate heritability and repeatability value. Show-jumping competition results collected between 1996 and 2011 were analyzed. The database contained 358 342 starts of 10 199 horses. Identity number, name and gender of the horse, rider, competition year, the level and location of the competition and placing were recorded in the database. To measure performance of horses, placing, number of starters and competition level were used. Competitions were categorized into five groups based on their difficulty level. The used repeatability animal model included fixed effects for age, gender, competition place, year of competition (and competition level in case of non-weighted measurement variables), and random effects for rider, animal and permanent environment effect. Variance components were estimated with VCE-6 software package. The goodness-of-fit of the models was low and moderate. Heritability and repeatability values were low for each measurement variables. The best goodness-of-fit model the weighted square root of placing resulted the highest heritability and repeatability value h2=0.074 and R=0.296.