Influence of indirect factors and its effect analysis on performance level of Slovak warmblood horse breed
Bibliographic record
Abstract
Article Details: Received: 2020-10-21 | Accepted: 2020-11-27 | Available online: 2021-01-31 https://doi.org/10.15414/afz.2021.24.mi-prap.105-108 During their career, horses are affected by a large number of direct and indirect factors. The aim of our study was to determine the effect of indirect factors, such as year of start, sex, breed, number of starts, age and proportion of genes of Slovak Warmblood horse breed. For determination of indirect factors on performance level, results from test efficiency and final placement in showjumping category 4, 5 and 6 years old young horses were used. 540 horses of Slovak Warmblood breed were analysed between 2015 - 2019 and 1155 data samples were collected. Based on the results of the linear model, parameters – the effect of gender and the influence of the gene proportion of Slovak Warmblood horse had statistically significant influence (p<0.05). High significant effect (p<0.001) on performance of Slovak Warmblood horse was observed in parameters – year of start, age during start and breed. Keywords: horse, indirect factors, performance References CASTEJON-RIBER, C. et al. (2017). Objectives, Principles and Methods of Strength Training for Horses. Journal of Equine Veterinary Science , 56, 93-103. http://dx.doi.org/10.1016/j.jevs.2017.04.011 De MARÉ, L. et al. (2017). Standardized exercise tests in horses: current situation and future perspectives. Vlaams Diergeneeskundig Tijdschrift , 86(2): 63-72. http://dx.doi.org/10.21825/vdt.v86i2.16290 GOŠČÍK, Z. (1993). Fyziologický základ tréningu koňa atléta. Nitra: Mgr. Marta Ölvecká. ISBN 80-900413-6-1, 70p. GOŠČÍK, Z. (2000). Racionálny tréning športových koní a jeho vplyv na ich dlhodobé využitie. [online]: http://www.horses.sk/'konfer/kratr. htm HENNESSY, K. et al. (2008). Vendor and purchaser expectations: differential market segment requirements for sport horses. In proceeding from 4th International Conference of International Society for Equitation Science . Dublin (p. 53). KEARSLEY, C. G. S. et al. (2008). Use of competition data for genetic evaluations of eventing horses in Britain: analysis of the dressage, showjumping and cross country phases of eventing competition. Livestock Science , 118(1), 72-81. https://doi.org/10.1016/j.livsci.2008.01.009 KOENEN, E. (2002). Genetic evaluations for competition traits of warmblood sport horses. In WBFSH seminar , Budapest. KOENEN, E. P. C., ALDRIDGE, L. I. & PHILIPSSON, J. (2004). An overview of breeding objectives for warmblood sport horses. Livestock Production Science , 88(1), 77-84. http://dx.doi.org/10.1016/j.livprodsci.2003.10.011 KRATTENMACHER, N. et al. (2014). The role of maternal lineages in horse breeding: Effects on conformation and performance traits. In proceeding from 10th World Congress on Genetics Applied to Livestock Production , Vancouver, Canada (p. 17-22). LUEHRS-BEHNKE, H. et al. (2002). Genetic associations among traits of the new integrated breeding evaluation method used for selection of German warmblood horses. Veterinarija ir zootechnika , 18(40), 90-93. RICARD, A.; BRUNS, E.; CUNNINGHAM, E. P. (2000). Genetics of performance traits. The genetics of the horse , (p. 411-538). http://dx.doi.org/ 10.1079/9780851994291.0000 RICARD, A. & BLOUIN, C. (2011). Genetic analysis of the longevity of French sport horses in jumping competition. Journal of Animal Science , 89(10), 2988-2994. http://dx.doi.org/10.2527/jas.2011-3931 STEWART, I. D., WOOLLIAMS, J. A. & BROTHERSTONE, S. (2010). Genetic evaluation of horses for performance in dressage competitions in Great Britain. Livestock Science , 128(1), 36-45. http://dx.doi.org/10.1016/j.livsci.2009.10.011 STEWART, M. et al. (2011). Assessment of positive emotions in horses: Implications for welfare and performance. Journal of Veterinary Behavior: Clinical Applications and Research , 6(5), 296. http://dx.doi.org/10.1016/j.jveb.2011.05.014 SCHUBERTOVÁ, Z., PAVLÍK, I. & CANDRÁK, J. (2014). The influence of the genomic data on the showjumping horses performance evaluation. Journal of Central European Agriculture , 15(2), 33-40. http://dx.doi.org/10.5513/JCEA01/15.2.1447 SCHRÖDER, W. et al. (2012). A genome‐wide association study for quantitative trait loci of show‐jumping in Hanoverian warmblood horses. Animal genetics , 43(4), 392-400. http://dx.doi.org/10.1111/j.1365-2052.2011.02265.x Van VELDHUIZEN, A. E. (1997). Breeding value estimation for riding horses in the Netherlands. In 48th Ann. Meet. EAAP , Vienna, Austria
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".