A. Giontella 1 , L.Buttazzoni 2 , M. Silvestrelli 1 , C. Baiocco 2 e C. Pieramati 1

1. “The selection index of the Italian Saddle horse stallions” A. Giontella1, L.Buttazzoni2, M. Silvestrelli1, C. Baiocco2 e C. Pieramati1 1 Centro di Studio del Cavallo Sportivo, Facoltà di Medicina Veterinaria, Perugia 2 Associazione Nazionale Allevatori Suini, Roma DRUENTO, 31 Ottobre 2008

2. trotting measurement amplitude Preselection (2 years) for "gaits": speed Objective evaluation of candidates’ athletic performance ADMISSION TO FIRST NINE PERFORMANCE TEST EDITIONS Horses must qualify in 2 steps: Selection before Performance test through free jumping evaluation

3. free jumping(objective scores based on the results)‏ free jumpingwith 3 judges scores 10th edition: no test for “gait” for 2 years old horses For 3 years old horses, 4 test steps Obedience test Stance and morpho-functional measurament and evaluation

4. character score gaits jumping score In all editions Horse daily assigned to a random trainer Twice a week These same traits are scored at the end of the training period by 2PROFESSIONAL RIDERS

5. 264 candidates 115 candidates In the first 10 editions of the Performance Test, for licensing stallions in the III section of the Italian Saddle Horse Studbook completed the testing period are approved

6. 14371scores character 94trainers gaits jumping For3same traits + 500PROFESSIONAL RIDERS scores GENEALOGICAL DATAfrom 3737animals obtained from 4 generation ancestors of these 264 horses MATERIAL AND METHOD The dataset file: 5226scores

7. in all 3 models were - date - trainer TRAINING PERIOD INDEX 3 different ways separately and for each trait without use the genealogical information with 3single trait BLUP models with multiple trait BLUP model FIXED EFFECTS RANDOM EFFECTS - horse - horse X trainer interaction - error

8. in all 3models were - horse - error FINAL SCORE INDEX 3 different ways separately and for each trait withoutuse the genealogical information with multiple trait BLUP model with 3single trait BLUP models FIXED EFFECTS RANDOMEFFECTS - professional rider

9. scores TRAINING PERIOD FINAL SCORES Analyzed SEPARATELY different WEIGTHING 90%training period 10%final scores

10. TOTAL INDEX calculated by assigning a weight 25% 50% “character” “gaits” “jumping”

11. first 7 edition(Silvestrelli et al.)‏ TOTAL 1,13 1,57 1 1,07 RESULTS AND DISCUSSION The pedigree files showed that the relationships between the tested horses are still very few: 168sires 264candidate 246mares N° sons / n° parents

12. For estimated the genetic values were used two different software: MTDFREML (Boldman et al., 1993) www.tzv.fal.de/~eg VCE (Kovac e Groeneveld, 2003)‏ www.aipl.arsusda.gov/curtvt/mtdfreml.html this to get a comparative analysis

13. Component Carattere Gaits Jumping animal 0,387 ± 0,015 0,648 ± 0,014 0,500 ± 0,016 Horse trainer 0,085 ± 0,004 0,076 ± 0,004 0,034 ± 0,007 error 0,528 ± 0,014 0,276 ± 0,012 0,465 ± 0,016 Component Character Gaits Jumping animal 0,386 ± 0,016 0,611 ± 0,015 0,461 ± 0,018 Horse trainer 0,085 ± 0,004 0,084 ± 0,004 0,037 ± 0,007 error 0,528 ± 0,014 0,305 ± 0,012 0,502 ± 0,018 Component Character Gaits Jumping animal 0,385 ± 0,015 0,672 ± 0,025 0,610 ± 0,014 0,738 ± 0,022 0,775 ± 0,020 0,411 ± 0,016 Horse trainer 0,086 ± 0,004 0,536 ± 0,020 0,084 ± 0,004 0,602 ± 0,045 0,683 ± 0,040 0,049 ± 0,006 error 0,529 ± 0,013 0,371 ± 0,006 0,305 ± 0,011 0,392 ± 0,008 0,407 ± 0,008 0,490 ± 0,015 Variance component ratios in the model with unrelated animals Variance component ratios in the single trait BLUP models Variance component ratios in the Multiple Trait BLUP models

14. Variance component ratios are in good agreement between the different models and with that observed in the first 7 editions High traits heritability High accuracy (>95%) in the training period scores for all 3 traits.

15. Model character gaits jumping I) sigle trait with unrelated animals 0,368 ± 0,039 0,461 ± 0,036 0,486 ± 0,035 II) single trait 0,355 ± 0,054 0,441 ± 0,056 0,461 ± 0,035 III) multiple trait 0,330 ± 0,041 0,863 ± 0,039 0,429 ± 0,036 0,804 ± 0,049 0,911 ± 0,027 0,541 ± 0,034 Heritability and genetic correlation in the finals scores Unlike what is found in previous editions (Silvestrelli et al.) were be able to obtain multivariate estimates for the final professional riders scores. (HIGH NUMBER OF OBSERVATIONS)‏

16. Estimates of the “character” heritability (first 7th final scores)0,23±0,14close to the estimate during training period. Estimates of the “gaits” heritability 0,58±0,04(first 7th final scores)goes to opposite way Data analysis shows that estimates of heritability between single and multiple traits models are relatively concordant mixed model not used for the estimation of the final scores(deviate from riders mean)‏

17. Between the complessive indexes of the training period (single trait models with relationship or unrelated animals)98,2% Between sigle trait model with unrelated animals and multiple trait model98,1 Between single and multiple trait BLUP models99,9% CORRELATION 98,2%, 97,9% on RANKS 99,8%

18. In this edition the use of a Single Trait BLUP model instead the old evaluation method gives an exchange of consecutive positions in the ranking between 2 stallions. Furthermore with the Multiple Trait BLUP model 3couple of not approved horses swap their consecutive position.

19. Dataset collected in 10 editions of the Performance Test permitted BLUP evaluation CONCLUSION   low impact on estimate accuracy  low impact on ratings within edition comparation between stallions approved in different edition are now possible   genetic indices of the ancestors could help in choosing candidates