No. 53 (2013)
Articles

Evaluation of Hungarian show-jumping results using different measurement variables

Published May 6, 2013
Anita Rudiné Mezei
University of Debrecen Centre for Agricultural and Applied Economic Sciences, Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Animal Sciences, Biotechnology and Environmental Protection, Debrecen
János Posta
University of Debrecen Centre for Agricultural and Applied Economic Sciences, Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Animal Sciences, Biotechnology and Environmental Protection, Debrecen
Sándor Mihók
University of Debrecen Centre for Agricultural and Applied Economic Sciences, Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Animal Sciences, Biotechnology and Environmental Protection, Debrecen
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APA

Rudiné Mezei, A., Posta, J., & Mihók, S. (2013). Evaluation of Hungarian show-jumping results using different measurement variables. Acta Agraria Debreceniensis, (53), 81-85. https://doi.org/10.34101/actaagrar/53/2133

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.

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