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

“The selection index of the Italian Saddle horse stallions”

DRUENTO, 31 Ottobre 2008

ADMISSION TO FIRST NINE PERFORMANCE TEST EDITIONS

Horses must qualify in 2 steps:

2. Selection before Performance test through free jumping evaluation

1. Preselection (2 years) for "gaits":

Objective evaluation of candidates’ athletic performance

trotting measurement

speed

amplitude

10th edition:

no test for “gait” for 2 years old horses

For 3 years old horses, 4 test steps

Stance andmorpho-functional measurament andevaluation

Obedience test

free jumping (objective scores based on the results)

free jumping with 3 judges scores

In all editions

1. Horse daily assigned to a random trainer

2. Twice a week jumping

These same traits are scored at the end of the training period by 2 PROFESSIONAL RIDERS

score

score

character

gaits

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

264 candidates

115 candidates

are approved

MATERIAL AND METHOD

The dataset file:

5226 scores

94 trainers

character

gaits

14371 scores

jumping

+ 500 PROFESSIONAL RIDERS scores For 3 same traits

GENEALOGICAL DATA from 3737 animals

obtained from 4 generation ancestors of these 264 horses

TRAINING PERIOD INDEX

3 different ways

separately and for each trait without use the genealogical information

with 3 single trait BLUP models

with multiple trait BLUP model

in all 3 models were

FIXED EFFECTS

- date

- trainer

RANDOM EFFECTS

- horse

- horse X trainer interaction

- error

FINAL SCORE INDEX

3 different ways

separately and for each trait without use the genealogical information

with 3 single trait BLUP models

with multiple trait BLUP model

in all 3 models were

FIXED EFFECTS

- professional rider

RANDOM EFFECTS

- horse

- error

different WEIGTHING

scores

TRAINING PERIOD

FINAL SCORES

Analyzed SEPARATELY

10% final scores90% training period

5%5%

90%

prof. rider

prof. rider

training

TOTAL INDEX

calculated by assigning a weight

25%

“character” “gaits”

50%

“jumping”

25%

25%

50%

character

gaits

jumping

RESULTS AND DISCUSSION

The pedigree files showed that the relationships between the tested horses are still very few:

N° sons / n° parents

1,071

1,571,13

TOTALfirst 7 edition (Silvestrelli et al.)

264 candidate

168 sires

246 mares

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.ht

ml

this to get a comparative analysis

Variance component ratios in the model with unrelated animals

0,465 ± 0,0160,276 ± 0,0120,528 ± 0,014error

0,034 ± 0,0070,076 ± 0,0040,085 ± 0,004Horse trainer

0,500 ± 0,0160,648 ± 0,0140,387 ± 0,015animal

JumpingGaitsCarattereComponent

Variance component ratios in the single trait BLUP models

0,502 ± 0,0180,305 ± 0,0120,528 ± 0,014error

0,037 ± 0,0070,084 ± 0,0040,085 ± 0,004Horse trainer

0,461 ± 0,0180,611 ± 0,0150,386 ± 0,016animal

JumpingGaitsCharacterComponent

Variance component ratios in the Multiple Trait BLUP models

0,392 ± 0,0080,407 ± 0,0080,490 ± 0,015

0,371 ± 0,0060,305 ± 0,011

0,529 ± 0,013error

0,602 ± 0,0450,683 ± 0,0400,049 ± 0,006

0,536 ± 0,0200,084 ± 0,004

0,086 ± 0,004Horse trainer

0,738 ± 0,0220,775 ± 0,0200,411 ± 0,016

0,672 ± 0,0250,610 ± 0,014

0,385 ± 0,015animal

JumpingGaitsCharacterComponent

1. Variance component ratios are in good agreement between the different models and with that observed in the first 7 editions

2. High traits heritability

3. High accuracy (>95%) in the training period scores for all 3 traits.

Heritability and genetic correlation in the finals scores

0,804 ± 0,0490,911 ± 0,0270,541 ± 0,034

0,863 ± 0,0390,429 ± 0,036

0,330 ± 0,041III) multiple trait

0,461 ± 0,0350,441 ± 0,0560,355 ± 0,054II) single trait

0,486 ± 0,0350,461 ± 0,0360,368 ± 0,039I) sigle trait with unrelated animals

jumpinggaitscharacterModel

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)

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)

Estimates of the “gaits” heritability 0,58±0,04 (first 7th

final scores) goes to opposite way

Estimates of the “character” heritability (first 7th final scores)

0,23±0,14 close to the estimate during training period.

CORRELATION

A. Between the complessive indexes of the training period (single trait models with relationship or unrelated animals) 98,2%

B. Between sigle trait model with unrelated animals and multiple trait model 98,1

C. Between single and multiple trait BLUP models 99,9%

on RANKS

A. 98,2%,

B. 97,9%

C. 99,8%

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 3 couple of not approved horses swap their consecutive position.

CONCLUSION

genetic indices of the ancestors could help in choosing candidates

Dataset collected in 10 editions of the Performance Test permitted BLUP evaluation

low impact on estimate accuracy

comparation between stallions approved in different edition are now possible

low impact on ratings within edition