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Practical efficiency of breeding value estimations based on annual earnings of horses for jumping, trotting, and galloping races in France
Livestock Production Science 87 (2004) 99 – 107 www.elsevier.com/locate/livprodsci
Practical efficiency of breeding value estimations based on annual earnings of horses for jumping, trotting, and galloping races in France B. Langlois *, C. Blouin INRA, Station de Ge´ne´tique Quantitative et Applique´e, Domaine de Vilvert, 78352 Jouy-en-Josas Cedex, France Received 19 November 2002; received in revised form 27 August 2003; accepted 14 October 2003
Abstract In France, breeding value estimations for horses are calculated according to a BLUP animal model fitted to the log of annual earnings in jumping, trotting races, flat races, steeplechases and hurdle races. The regression b p/I0 and correlation R between the breeding value estimation at the moment of conception with the mean of future performances P make it possible to check the practical efficiency of the method of indexation used. The expected regression is one and the expected correlation depends on heritability and the mean of the determination coefficient of the index I0. The results are the following. Discipline
Number
b p/I0
Expected R
Obtained R
Jumping Trotting Flat races Steeplechases and hurdle races
9569 7029 4383 1986
0.95 0.79 1.18 0.80
0.25 0.33 0.27 0.22
0.39 0.26 0.33 0.15
The situation appears to be suboptimal in the case of jumping but improvements are certainly possible in the case of races. The obtained results, however, confirm the usefulness of these tools for trotting and flat races. The case of steeplechases and hurdle races is not as effective mainly because of the low precision of the estimations. Other predictors of performance, BLUP for yearlings or at 3 years of age for jumpers, confirm this first analysis and the results, age per age, are detailed in the text. D 2003 Elsevier B.V. All rights reserved. Keywords: Horse; Performance; Breeding value; Earnings; BLUP; Animal model; Performance prediction; Sport competitions; Races
Re´sume´ Efficacite´ pratique des indices de se´lection fonde´s sur les gains annuels en concours hippique et dans les courses de trot et de galop en France.
* Corresponding author. Tel.: +33-0-1-34-65-21-10; fax: +33-0-1-34-65-22-10. E-mail address: [email protected] (B. Langlois). 0301-6226/$ - see front matter D 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.livprodsci.2003.10.003
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B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107
L’estimation de la valeur ge´ne´tique des chevaux est calcule´e en France par un BLUP en mode`le animal ajuste´ sur le logarithme des gains annuels en concours hippique, en courses au trot et au galop, en plat et a` l’obstacle. La re´gression b p/I0 et la corre´lation R entre l’estimation de la valeur ge´ne´tique au moment de la conception, avec la moyenne des futures performances P autorise a` ve´rifier l’efficacite´ the´orique et pratique de la me´thode d’indexation mise en œuvre. La re´gression attendue est de 1 et la corre´lation attendue de´pend de l’he´ritabilite´ et du coefficient de de´termination moyen de l’indice I0. Les re´sultats obtenus sont les suivants: Discipline
Effectif
b p/I0
R attendu
R obtenu
Concours hippique Courses au trot Courses plates Courses a` obstacles
9569 7029 4383 1986
0.95 0.79 1.18 0.80
0.25 0.33 0.27 0.22
0.39 0.26 0.33 0.15
La situation apparaıˆt eˆtre suboptimale dans le cas du concours hippique mais des ame´liorations sont tre`s certainement envisageables dans le cas des courses. Toutefois, les re´sultats obtenus confirment l’utilite´ de ces outils de se´lection pour les courses au trot et les courses plates. Dans le cas des courses a` obstacles c’est moins e´vident principalement a` cause de la faible pre´cision moyenne des estimations. D’autres pre´dicteurs de la performance, le BLUP des yearling ou des 3 ans pour les chevaux de sport confirment cette premie`re analyse et les re´sultats aˆge par aˆge sont de´taille´s dans le texte. Mots cle´s: Cheval/Valeur ge´ne´tique/Gains/BLUP/Mode`le animal/Pre´diction des performances/Compe´titions e´questres/ Courses D 2003 Elsevier B.V. All rights reserved.
1. Introduction
2. Material and methods
In France, the performance of horses in races and equestrian competitions is measured by different performance indices (Langlois, 1993). These indices are based on transformations of the annual earnings and they produce normally distributed values with a mean of 100 and a standard deviation of 20. These indices are corrected intra-year of performance for age and sex. Breeding value estimations were calculated according to a BLUP animal model fitted to the log of annual earnings in jumping (Tavernier, 1990a), trotting races (earnings per start) (Tavernier, 1989a,b), flat races, and steeplechases and hurdle races. Evaluations were made every year. In the future, additional information based on ranking will be used (Tavernier, 1990b). It is, therefore, possible to check, discipline by discipline, the BLUP obtained at certain moments of decision-making by the breeder with the mean of its future performances evaluated by annual indices. In this paper, the regression and the correlation between the breeding value estimation at the moment of conception (first choice of the breeder) and at the moment of the sale, as a yearling for race horses or as 3 year olds for sport horses, with future performances were studied.
2.1. Measuring performances The choice of annual earnings as criteria to measure horse performances has often been discussed (for reviews, see Hintz, 1980; Klemetsdal, 1990; Langlois, 1980b, 1982, 1984b, 1996a,b; Tolley et al., 1985). In France, the criteria for jumping are the logarithm of annual earnings. The same applies for gallop races (flat and steeplechases and hurdles). For trotting, it is the log of annual average earnings per start. Other transformations of earnings have been proposed with similar effect as log (Minkema, 1979; Arnason et al., 1989; Klemetsdal, 1989). 2.2. Model of analysis Measure of performance is fitted to the following linear model according to Tavernier (1988a): y ¼ Xb þ Zu þ Wm þ Zp þ e with: y = vector of observations, b = vector of fixed effects (sex and age year classes), u = vector of individual additive genetic values, m = vector of ‘‘ma-
B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107
ternal’’ effects: common environment to the offsprings of a same mare, p = vector of common environment ef-fects on different performances of the same horse, e = vector of residual error, X, Z, W are incidence matrices. Fixed effects were sex (female and male or gelding) and an age by year interaction. There were five age classes: 4, 5, 6 – 7, 8 –10, 11 years old and more for jumping; 2, 3, 4, 5, 6– 10 years old for trotters. There were four age classes for gallop races: 2, 3, 4, 5 years old and more for flat races and 3, 4, 5, 6 years old and more for steeplechases and hurdle races. These age classes were cross classified with year of performance starting in 1972 for jumping, 1968 for trotting and 1950 for gallop races. The effects of age with year is significant and can be explained by the policy of allocating money for age classes changes with time and combines its effect with that of money inflation. The ‘‘maternal’’ effect is an interpretation of the difference found between the paternal and maternal components of variance. This difference is due to the common environment of the offspring of the same mare because, in the great majority of cases, an owner only has one mare; the maternal effect (sensu stricto) is confounded with the influence of the breeder. Common environment on different performances of the same horse represents the difference between the correlations between two performances (repeatability) and heritability added to the ‘‘maternal’’ component, and is explained by the permanent environment of the horse after the rearing period. Expectation (E) and variance– covariance matrix (V) of this linear model are: 2
y
3 2
6 7 6 6 7 6 6 7 6 6u7 6 6 7 6 6 7 6 6 7 6 6 7 6 7 6 E6 6 m 7¼6 6 7 6 6 7 6 6 7 6 6p7 6 6 7 6 6 7 6 4 5 4 e
Xb
3
7 2 u 3 2 Ar 2 7 7 6 7 6 u 0 7 7 6 7 6 7 6 7 6 6 6 0 7 6m7 6 7 6 7 7 6 0 7 7¼6 7V6 7 6 7 6 7 6 0 7 6p7 6 7 6 7 6 6 7 0 7 4 5 4 7 0 e 5 0
0
0
Ir2m
0
0
Ir2p
0
0
0
3
7 7 7 0 7 7 7 7 7 0 7 7 7 5 2 Ire
101
2 with ru2 =h2ry2,rm =vry2,rp2,rp2 =(rvh2)ry2, r2e =(1r) 2 ry , A: relationship matrix, I: identity matrix, h2: heritability, r: repeatability, v: ‘‘maternal’’ component of variance. Relationship matrix includes all animal performers and nonperformers, reproducers and nonreproducers. Lines of the Z matrix corresponding to nonperformers are filled with zeros.
2.3. Estimating breeding values Equations obtained by minimisation of the error variance for estimating the effects of the model described above are as follows: 2
XVX
XVZ
XVW
6 6 6 6 ZVX ZVZ þ t1 A1 ZVW 6 6 6 6 6 WVX WVZ WVW þ t2 I 6 6 4 ZVW ZVZ ZVW 3 2 3 2 XVy b 7 6 7 6 7 6 7 6 7 6 7 6 6 u 7 6 ZVy 7 7 6 7 6 7 6 7 6 6 7¼6 7 7 6 7 6 6 m 7 6 WVy 7 7 6 7 6 7 6 7 6 5 4 5 4 ZVy p
XVZ ZVZ WVZ
3 7 7 7 7 7 7 7 7 7 7 7 5
ZVZ þ t3 I
with: t 1 =(1 r)/h 2 , t 2 =(1 r)/v, t 3 =(1 r)/(r h2 v), resolution of these equations and calculation of the precision are shown in Tavernier (1988). Genetic parameters for jumping have been estimated by Langlois (1975b, 1980a) and Tavernier (1986). Repeatability is 0.45, maternal component of variance 0.05, and heritability 0.20. For trotting, the genetic parameters have been estimated by Langlois (1984a, 1986, 1989) and [Tavernier (1989a,b). Heritability is 0.26, repeatability 0.36, and maternal component of variance 0.04. For gallop races, the genetic parameters used are the last estimated by Langlois et al. (1996). In flat
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Table 1 Percentage of born horses having earnings at a given age Activity
Breed
Age (years) 2
Jumping
SF + AA (% of the total)a
Trotting Flat races Steeplechases and hurdle races
TF Thoroughbred Thoroughbred
Career 3
–
–
0.04 0.16 –
0.25 0.32 0.08
4
5
6
0.22 (0.90) 0.27 – 0.10
0.29 (0.82) 0.18 – 0.07
0.29 (0.76) – – –
0.42 (0.75) 0.32 0.35 0.16
Abbreviations: SF = ‘‘Selle Francßais’’; AA = Anglo-Arab; TF = ‘‘Trotteur Francßais’’. a Jumping competitions are open to racing breeds.
races, such as steeplechases and hurdle races, heritability is 0.25 and maternal component of variance is 0.05, repeatability being 0.38 and 0.44, respectively. They are in concordance with our previous results (Langlois 1975a, 1980b). 2.4. Expected regressions and correlations between breeding value and future performances
where R is the precision of I (correlation of I with A) and c is the correlation of I with E rI ¼ RrA ¼ RhrP rE ¼ erP By definition of e, which lead to CovðI; PÞ ¼ R2 r2A þ cRher2P
Let I be the animal model BLUP Index estimator of the additive genetic value A of a horse for the aptitude to a given discipline (jumping, trotting races, flat races, hurdle races and steeple chases). Let P be the measure of the horse performance: P ¼AþE where E is a residual error mainly due to the effect of environment. We can write: CovðI; PÞ ¼ CovðI; AÞ þ CovðI; EÞ CovðI; AÞ ¼ RrI rA and Cov(I, E) = crIrE
and to the regression of performance P on I bP =I ¼
CovðI; PÞ R2 h2 r2P cRher2P ¼ 2 2 2 þ 2 2 2 r2I R h rP R h rP
which give after simplifications bP =I ¼ 1 þ c
1 e R h
If c = 0 the value of that regression is 1 and deviation from 1 gives a tool to evaluate c the correlation between BLUP evaluation and environmental effect on performance. If such a correlation exists, it induces a genotype by environment correlation s = Rc between A and E.
Table 2 Population structure Breed
SF + AA
TF
Thoroughbred
Activity
Jumping
Trotting
Flat races
Steeplechases and hurdle races
Considered career (years) Mean number of yearly performances per horse having earnings Mean yearly number of offsprings born per stallion Mean age of reproducers
4–6 1.9 9.3 11.6
2–5 2.3 14.0 11.3
2–3 1.4
3–5 1.6
Abbreviations: SF ‘‘Selle Francßais’’; AA = Anglo-Arab = TF = ‘‘Trotteur Francßais’’.
6.6 10.6
B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107 Table 3 BLUP at birth and their coefficients of determination (CD) of placed (1) versus unplaced (0) of horses born in the first year of the studya Breed and birth year
Placed = 1, Variable n unplaced = 0
Saddle breeds in jumping (1988)
1 1 0 0
BLUP CD BLUP CD
3628 3628 4462 4462
7.3 0.21 4.3 0.19
All breeds in jumping (1988)
1 1
BLUP CD
4869 4869
5.4 6.1 0.18 0.08
‘‘Trotteur Francßais’’ 1 in trotting 1 (1989) 0 0
BLUP CD BLUP CD
3549 21.0 3549 0.30 7171 18.5 7171 0.29
5.9 0.04 5.8 0.04
Thoroughbred in flat races (1991)
1 1 0 0
BLUP CD BLUP CD
2345 21.9 2345 0.26 3212 18.6 3212 0.25
5.3 0.07 6.3 0.07
Thoroughbred in steeplechases and hurdle races (1990)
1 1 0 0
BLUP CD BLUP CD
1009 1009 4612 4612
3.5 0.08 3.0 0.07
For trotting, birth years 1989 and 1990 were chosen to check the performances from 1991 to 1996. For flat races, birth years 1991 and 1992 were chosen to check the performances from 1993 to 1996. For steeplechases and hurdle races, birth years 1990 and 1991 were chosen to check the performances from 1993 to 1996. BLUP breeding value estimations at the moment of conception do not include the performances from the year before the birth to 1996. The same principle is applied + 1 year for yearlings and + 3 years for 3year-old sport horses. Table 1 gives the percentage of horses born with obtaining earnings at given ages in the studied disciplines. Table 2 gives information on the population structure. This is similar to that currently encountered for horse populations: too many stallions, a low replacement rate leading to animals that are too old with few offspring per reproducer, and a long generation interval. Table 3 allows estimation of the selection pressure realised when considering only horses with earnings. As a first example, the overall mean for saddle breeds (SF + AA) can be calculated from lines 1 and 3 of Table 3; i.e. 5.6. Intensity of selection i=(7.3 5.6)/ 5.5 = 0.309, which implies a selection rate p = 0.83, is far from the percentage of selection 0.42 presented in Table 1. The same calculation for trotters gives i = 0.288 which implies a selection rate p = 0.85 which is far from the 0.32 presented in Table 1.
Mean S.D.
6.9 0.18 5.8 0.13
103
5.5 0.06 5.6 0.07
a The results for the second birth year and for BLUP as yearling or as 3 year olds are very similar and are not given.
2.5. Birth year tested For jumping, birth years 1988 and 1989 were chosen to check the performances from 1992 to 1996.
Table 4 Linear relationship between the annual phenotypic index and the BLUP breeding value estimation at the moment of conception and at 3 years of age for jumping horses (all breeds) (mean for birth years 1988 and 1989) Performance at 4 years of age
Performance at 5 years of age
Performance at 6 years of age
Mean performance of the career
Number of horses
4203
6031
6385
9569
Regression coefficient on the BLUP at conception Expected correlationa Obtained correlation
0.76
1.03
1.02
0.95
0.20 0.35
0.20 0.36
0.20 0.34
0.25 0.39
0.75
1.00
1.02
0.93
0.21 0.36
0.21 0.38
0.21 0.36
0.28 0.40
Regression coefficient on the BLUP at 3 years of age Expected correlationa Obtained correlation a
Calculated from heritability, accuracy of the Blup and the reduction of variance in the mean performance of the career.
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Table 5 Linear relationship between the annual phenotypic index and the BLUP breeding value estimation at the moment of conception and as yearling for trotters (mean for birth years 1989 and 1990) Performance at 2 years of age
Performance at 3 years of age
Performance at 4 years of age
Performance at 5 years of age
Mean performance of the career
Number of horses
808
5402
5837
3923
7029
Regression coefficient on the BLUP at conception Expected correlationa Obtained correlation
0.60
0.76
0.89
0.75
0.79
0.28 0.17
0.28 0.22
0.28 0.26
0.28 0.21
0.33 0.26
0.59
0.79
0.92
0.76
0.81
0.28 0.17
0.28 0.23
0.28 0.26
0.28 0.22
0.33 0.26
Regression coefficient on the BLUP as a yearling Expected correlationa Obtained correlation a
Calculated from heritability, accuracy of the BLUP and the reduction of variance in the mean performance of the career.
For thoroughbreds in flat races, i = 0.189 which implies a selection rate p = 0.90, also far from the 0.35 presented in Table 1. The situation in steeplechases and hurdle races gives i = 0.257 which implies a selection rate p = 0.86, again far from the 0.16 presented in Table 1. One can observe from this data that the selection bias is not as important as it first appears. We can also note that the other birth years and BLUP as yearling or as 3 year olds gave similar results.
performance. Table 8 gives the estimates of these correlations from the observed data. It reveals that they are quite low, if they exist. From a practical point of view, breeding value estimation at the moment of conception has a correlation of 0.39 with further performances in jumping and 0.33 with those of flat races. In these two cases, the correlations exceed the expected values (0.25 and 0.27, respectively). In the case of trotting races, steeplechases and hurdle races, correlations of 0.33
3. Results
Table 6 Linear relationship between the annual phenotypic index and the BLUP breeding value estimation at the moment of conception and as yearling for flat races (mean for birth years 1991 and 1992)
Tables 4 –7 give the detailed results for jumping, trotting races, flat races and steeplechases and hurdle races, respectively. Predicting performance through breeding value evaluation at the moment of conception overevaluated the level of performance actually achieved by 5%, 21% and 20%, respectively, for jumping, trotting, and steeplechases and hurdle races. On the contrary, it underevaluated by 18% in the case of flat races. The situation was similar for predicting performance at the moment of the sale (as yearlings or as 3-year-old sport horses). For jumping it was suboptimal, as already discussed by Tavernier (1994). In the other cases, we have either an over- or underestimation of the realised heritability or we have to take into account a correlation between breeding value estimation at the beginning of the career and further environmental effects on
Performance Performance Mean at 2 years at 3 years performance of age of age of the career Number of horses
1928
3792
4383
Regression 0.77 coefficient on the BLUP at conception Expected correlationa 0.26 Obtained correlation 0.21
1.23
1.18
0.26 0.31
0.27 0.33
0.79
1.25
1.21
0.26 0.23
0.26 0.33
0.28 0.34
Regression coefficient on the BLUP as a yearling Expected correlationa Obtained correlation
a Calculated from heritability, accuracy of the BLUP and the reduction of variance in the mean performance of the career.
B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107
105
Table 7 Linear relationship between the annual phenotypic index and the BLUP breeding value estimation at the moment of conception and as yearling for steeplechases and hurdle races (mean for birth years 1990 and 1991) Performance at 3 years of age
Performance at 4 years of age
Performance at 5 years of age
Mean performance of the career
Number of horses
1013
1296
856
1986
Regression coefficient on the BLUP at conception Expected correlationa Obtained correlation
0.71
0.90
0.69
0.80
0.20 0.13
0.20 0.16
0.20 0.12
0.22 0.15
0.86
0.88
0.78
0.86
0.22 0.17
0.22 0.15
0.22 0.15
0.24 0.17
Regression coefficient on the BLUP as a yearling Expected correlationa Obtained correlation a
Calculated from heritability, accuracy of the BLUP and the reduction of variance in the mean performance of the career.
and 0.22 were expected but only 0.26 and 0.15 are obtained, respectively. Age by age, the results showed that agreement between expected and obtained values were generally better for performances obtained in older horses. Total expression of the performance potential was probably not regularly achieved in young animals. For the two birth years tested, agreement was generally good. The rare exceptions (2-year-old trot-
Table 8 Interpretation of the difference to 1 of the regression coefficient of the mean performance (P) on the BLUP at conception and as yearlings or 3 years old (I ) for jumpers in terms of genetic/ environment correlation Discipline
bP/I
CD
c
s
Jumping Conception 3 years old
0.95 0.93
0.19 0.22
0.01 0.01
0.00 0.00
Trotting races Conception Yearling
0.79 0.81
0.31 0.30
0.07 0.06
0.04 0.04
Flat races Conception Yearling
1.18 1.21
0.27 0.28
+ 0.06 + 0.06
+ 0.03 + 0.03
Steeplechases and hurdle races Conception 0.80 0.19 Yearling 0.86 0.18
0.05 0.03
0.02 0.02
CD: mean coefficient of determination of the BLUP; c: estimated correlation of the BLUP and environmental effect on performance; s: induced genetic/environment correlation.
ters) can easily be explained by certain changes in data management (anniversary date changing from December 31 to September 15 in 1992). Between the moment of conception and that of sale, the slight increase in accuracy and in efficacy is surprising. This is due to a large dispersion of the annual information over too many stallions. This is a characteristic of horse breeding structures (small number of mated mares per stallion and great variance of family size).
4. Discussion The results of this study indicate that breeding value estimations proposed in France to optimise the use of earnings in competitions for breeding purposes are doing well for sport horses selected for jumping. In this case, BLUP breeding offers a correlation close to 0.40 with the future performance of the horse. This is much higher than traditional methods based on the appreciation of conformation and gaits for which similar efficiency was found between 0.10 and 0.15 by Langlois et al. (1978). In the case of race horses, we can distinguish between flat races, where there was a correlation of 0.33 but where breeding value estimations systematically underestimated the level of performances achieved, and the case of trotting races and steeplechases/hurdle races with, respectively, a correlation of 0.26 and 0.15 and which overestimated the level of performances. In the case of trotting, the underesti-
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mations are certainly not so important because the change of the anniversary date shortened the career of ages 2 and 3 for horses born in 1990 and after. This hardly impacts on the regressions presented for ages 2 and 3 leading to a general underestimation of observed results. Assuming that the values for heritabilities used are true, Table 8 shows that the breeding value estimations and environmental effect on performances have a correlation of only 0.06 in the case of flat races for which such a correlation is often mentioned. On the other hand, it is difficult to understand why we should have a negative correlation ( 0.03 to 0.07) for trotting or steeplechases and hurdle races. This would mean that the best pedigree horses do not have such a good environment or the reverse! It is true, however, that these hypothetical correlations seem very low. It is, therefore, more practical to ignore it and to propose some changes in the heritability values or in the model for indexation. We propose to search for heritability values that make the regression coefficient of performance on breeding value estimations shown here near to one. However, a more thorough discussion on the model is needed.
5. Conclusion Breeding value estimations with the BLUP animal model calculated according to earnings in competitions in France appears to be a very useful tool for breeders. They are suboptimal in the case of jumping and give a practical correlation with the breeding objective of 0.39. They could certainly be improved in the case of race horses. However, in their present state of development, they predict further performances rather well in the case of flat (r = 0.33) and trotting races (r = 0.26). Steeplechases and hurdle races are characterised by a low expected precision in the prediction of the performance level. The correlation achieved with the breeding objective is therefore low (r = 0.15). We would, however, recommend in that case using only a few animals with high accuracy of their breeding value estimation for this breeding objective. For all racing activities, we recommend testing new values of heritability for breeding value estimations.
References Arnason, Th., Bendroth, M., Philipsson, J., Henriksson, K., Darenius, A., 1989. Genetic evaluations of Swedish trotters in state of breeding evaluation in trotters. Proceedings of the EAAP symposium of the Commission on Horse Production, Helsinki, 1 July 1988. EAAP Publication, vol. 42. Pudoc, Wageningen, pp. 106 – 130. Hintz, R.L., 1980. Genetics of performance in the horse. J. Anim. Sci. 51, 582 – 594. Klemetsdal, G., 1989. Norwegian trotter breeding and estimation of breeding values. State of breeding evaluation in trotters. Proceedings of the EAAP symposium of the Commission on Horse Production, Helsinki, 1 July 1988. EAAP Publication, vol. 42. Pudoc, Wageningen, pp. 95 – 105. Klemetsdal, G., 1990. Breeding for performance in horses—a review. Proceedings 4th World Congress on Genetics Applied to Livestock Production XVI. Edinburgh Univ. Ed. Gb, pp. 184 – 193. Langlois, B., 1975a. Analyse statistique et ge´ne´tiques des gains des pur sang anglais de trois ans dans les courses plates francßaises. Ann. Ge´ne´t. Se´l. Anim. 7, 387 – 408. Langlois, B., 1975b. Interpre´tation statistique et ge´ne´tique des gains des chevaux dans les compe´titions e´questres franc¸ais. Livest. Prod. Sci. 2, 191 – 205. Langlois, B., Froidevaux, J., Lamarche, L., Legault, C., Legault, P., Tassencourt, L., Theret, M., 1978. Analyse des liaisons entre la morphologie et l’aptitude au galop, au trot et au saut d’obstacles chez le cheval. Ann. Ge´ne´t. Se´l. Anim. 10, 443 – 474. Langlois, B., 1980a. Estimation de la valeur ge´ne´tique des chevaux de sport d’apre`s les sommes gagne´es dans les compe´titions e´questres franc¸ais. Ann. Ge´ne´t. Se´l. Anim. 12, 15 – 31. Langlois, B., 1980b. Heritability of racing ability in thoroughbreds. A review. Livest. Prod. Sci. 7, 591 – 605. Langlois, B., 1982. L’he´ritabilite´ des performances chez le trotteur une revue bibliographique. Ann. Ge´ne´t. Se´l. Anim. 14 (3), 399 – 414. Langlois, B., 1984a. He´ritabilite´ et corre´lations ge´ne´tiques des temps records et des gains e´tablis par les trotteurs francßais de 2 a` 6 ans. Proceedings of the 35th annual meeting of the European Association for Animal Production, 6 – 9 August, Commission on horse production, session I. Den Haag, Netherlands. 11 pp. Langlois, B., 1984b. L’he´ritabilite´ des performances chez le trotteur. une revue bibliographique. In: Jarrige, R., Martin-Rosset, W. (re´d.), Le Cheval. Reproduction, Se´lection, Alimentation, Exploitation. INRA, Paris, pp. 409 – 422. Langlois, B., 1986. Evaluation ge´ne´tique des trotteurs franc¸ais d’apre`s leurs gains. Proceedings of the Journe´e de la recherche chevaline. CEREOPA, Paris, pp. 14 – 29. 12 March. Langlois, B., 1989. Breeding evaluation of French trotters according to their race earnings—present situation. EAAP Publication, vol. 42. Pudoc, Wageningen, pp. 24 – 40. Langlois, B., 1993. Registration systems concerning breeding and performance. The situation of France. Proceedings of the 44th Annual meeting European Association for Animal Production, 16 – 19 August, Commission on Horse production Session II, Aarhus, Denmark. 4 pp.
B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107 Langlois, B., 1996a. Me´thodes objectives de se´lection dans l’espe`ce e´quine. Rev. Port. Zootec. 3 (2), 13 – 29. Langlois, B., 1996b. A consideration of genetic aspects of some current practices in thoroughbred horse breeding. Ann. Zootech. 45, 41 – 51. Langlois, B., Blouin, C., Tavernier, A., 1996. Nouveaux re´sultats d’estimation de l’he´ritabilite´ des gains en course des pur sang en France. Genet. Sel. Evol. 28, 275 – 283. Minkema, D., 1979. Studies on the genetics of trotting performances in Dutch trotters: I. Heritability of trotting performance. Ann. Ge´ne´t. Se´l. Anim. 8, 511 – 526. Tavernier, A., 1986. Donne´es nouvelles sur les performances des chevaux de sport: pre´cocite´, effets maternels, influence du type ge´ne´tique. Proceedings of the Journe´e de la recherche chevaline. CEREOPA, Paris, pp. 31 – 57. 12 March. Tavernier, A., 1988. Advantages of BLUP animal model for breeding value estimation in horses. Livest. Prod. Sci. 20, 149 – 160. Tavernier, A., 1989a. Caracte´risation de la population des Trotteurs
107
Francßais d’apre`s leur estimation ge´ne´tique par un Blup mode`le animal. Ann. Zootech. 38, 145 – 155. Tavernier, A., 1989b. Breeding evaluation of French trotters according to their race earnings: 2. Prospects. Proceedings of the EAAP Symposium of the commission on horse production, Helsinki, Finland, June 27 July 1988. EAAP Publication, vol. 42, pp. 41 – 54. Tavernier, A., 1990a. Caracte´risation des chevaux de concours hippique franc¸ais d’apre`s leur estimation ge´ne´tique par un Blup mode`le animal. Ann. Zootech. 39, 27 – 44. Tavernier, A., 1990b. Estimation of breeding value of jumping horses from their ranks. Livest. Prod. Sci. 26, 277 – 290. Tavernier, A., 1994. Special problems in genetic evaluation of performance traits in horse. Proceedings of the 5th World Congress on Genetics Applied to Livestock Production, vol. 17. Guelph Univ. Ed., Ontario, Canada, pp. 450 – 457. Tolley, E.A., Notter, D.R., Marlowe, T.J., 1985. A review of the inheritance of racing performance in horses. Anim. Breed. Abstr. 53, 163 – 185.
Practical efficiency of breeding value estimations based on annual earnings of horses for jumping, trotting, and galloping races in France B. Langlois *, C. Blouin INRA, Station de Ge´ne´tique Quantitative et Applique´e, Domaine de Vilvert, 78352 Jouy-en-Josas Cedex, France Received 19 November 2002; received in revised form 27 August 2003; accepted 14 October 2003
Abstract In France, breeding value estimations for horses are calculated according to a BLUP animal model fitted to the log of annual earnings in jumping, trotting races, flat races, steeplechases and hurdle races. The regression b p/I0 and correlation R between the breeding value estimation at the moment of conception with the mean of future performances P make it possible to check the practical efficiency of the method of indexation used. The expected regression is one and the expected correlation depends on heritability and the mean of the determination coefficient of the index I0. The results are the following. Discipline
Number
b p/I0
Expected R
Obtained R
Jumping Trotting Flat races Steeplechases and hurdle races
9569 7029 4383 1986
0.95 0.79 1.18 0.80
0.25 0.33 0.27 0.22
0.39 0.26 0.33 0.15
The situation appears to be suboptimal in the case of jumping but improvements are certainly possible in the case of races. The obtained results, however, confirm the usefulness of these tools for trotting and flat races. The case of steeplechases and hurdle races is not as effective mainly because of the low precision of the estimations. Other predictors of performance, BLUP for yearlings or at 3 years of age for jumpers, confirm this first analysis and the results, age per age, are detailed in the text. D 2003 Elsevier B.V. All rights reserved. Keywords: Horse; Performance; Breeding value; Earnings; BLUP; Animal model; Performance prediction; Sport competitions; Races
Re´sume´ Efficacite´ pratique des indices de se´lection fonde´s sur les gains annuels en concours hippique et dans les courses de trot et de galop en France.
* Corresponding author. Tel.: +33-0-1-34-65-21-10; fax: +33-0-1-34-65-22-10. E-mail address: [email protected] (B. Langlois). 0301-6226/$ - see front matter D 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.livprodsci.2003.10.003
100
B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107
L’estimation de la valeur ge´ne´tique des chevaux est calcule´e en France par un BLUP en mode`le animal ajuste´ sur le logarithme des gains annuels en concours hippique, en courses au trot et au galop, en plat et a` l’obstacle. La re´gression b p/I0 et la corre´lation R entre l’estimation de la valeur ge´ne´tique au moment de la conception, avec la moyenne des futures performances P autorise a` ve´rifier l’efficacite´ the´orique et pratique de la me´thode d’indexation mise en œuvre. La re´gression attendue est de 1 et la corre´lation attendue de´pend de l’he´ritabilite´ et du coefficient de de´termination moyen de l’indice I0. Les re´sultats obtenus sont les suivants: Discipline
Effectif
b p/I0
R attendu
R obtenu
Concours hippique Courses au trot Courses plates Courses a` obstacles
9569 7029 4383 1986
0.95 0.79 1.18 0.80
0.25 0.33 0.27 0.22
0.39 0.26 0.33 0.15
La situation apparaıˆt eˆtre suboptimale dans le cas du concours hippique mais des ame´liorations sont tre`s certainement envisageables dans le cas des courses. Toutefois, les re´sultats obtenus confirment l’utilite´ de ces outils de se´lection pour les courses au trot et les courses plates. Dans le cas des courses a` obstacles c’est moins e´vident principalement a` cause de la faible pre´cision moyenne des estimations. D’autres pre´dicteurs de la performance, le BLUP des yearling ou des 3 ans pour les chevaux de sport confirment cette premie`re analyse et les re´sultats aˆge par aˆge sont de´taille´s dans le texte. Mots cle´s: Cheval/Valeur ge´ne´tique/Gains/BLUP/Mode`le animal/Pre´diction des performances/Compe´titions e´questres/ Courses D 2003 Elsevier B.V. All rights reserved.
1. Introduction
2. Material and methods
In France, the performance of horses in races and equestrian competitions is measured by different performance indices (Langlois, 1993). These indices are based on transformations of the annual earnings and they produce normally distributed values with a mean of 100 and a standard deviation of 20. These indices are corrected intra-year of performance for age and sex. Breeding value estimations were calculated according to a BLUP animal model fitted to the log of annual earnings in jumping (Tavernier, 1990a), trotting races (earnings per start) (Tavernier, 1989a,b), flat races, and steeplechases and hurdle races. Evaluations were made every year. In the future, additional information based on ranking will be used (Tavernier, 1990b). It is, therefore, possible to check, discipline by discipline, the BLUP obtained at certain moments of decision-making by the breeder with the mean of its future performances evaluated by annual indices. In this paper, the regression and the correlation between the breeding value estimation at the moment of conception (first choice of the breeder) and at the moment of the sale, as a yearling for race horses or as 3 year olds for sport horses, with future performances were studied.
2.1. Measuring performances The choice of annual earnings as criteria to measure horse performances has often been discussed (for reviews, see Hintz, 1980; Klemetsdal, 1990; Langlois, 1980b, 1982, 1984b, 1996a,b; Tolley et al., 1985). In France, the criteria for jumping are the logarithm of annual earnings. The same applies for gallop races (flat and steeplechases and hurdles). For trotting, it is the log of annual average earnings per start. Other transformations of earnings have been proposed with similar effect as log (Minkema, 1979; Arnason et al., 1989; Klemetsdal, 1989). 2.2. Model of analysis Measure of performance is fitted to the following linear model according to Tavernier (1988a): y ¼ Xb þ Zu þ Wm þ Zp þ e with: y = vector of observations, b = vector of fixed effects (sex and age year classes), u = vector of individual additive genetic values, m = vector of ‘‘ma-
B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107
ternal’’ effects: common environment to the offsprings of a same mare, p = vector of common environment ef-fects on different performances of the same horse, e = vector of residual error, X, Z, W are incidence matrices. Fixed effects were sex (female and male or gelding) and an age by year interaction. There were five age classes: 4, 5, 6 – 7, 8 –10, 11 years old and more for jumping; 2, 3, 4, 5, 6– 10 years old for trotters. There were four age classes for gallop races: 2, 3, 4, 5 years old and more for flat races and 3, 4, 5, 6 years old and more for steeplechases and hurdle races. These age classes were cross classified with year of performance starting in 1972 for jumping, 1968 for trotting and 1950 for gallop races. The effects of age with year is significant and can be explained by the policy of allocating money for age classes changes with time and combines its effect with that of money inflation. The ‘‘maternal’’ effect is an interpretation of the difference found between the paternal and maternal components of variance. This difference is due to the common environment of the offspring of the same mare because, in the great majority of cases, an owner only has one mare; the maternal effect (sensu stricto) is confounded with the influence of the breeder. Common environment on different performances of the same horse represents the difference between the correlations between two performances (repeatability) and heritability added to the ‘‘maternal’’ component, and is explained by the permanent environment of the horse after the rearing period. Expectation (E) and variance– covariance matrix (V) of this linear model are: 2
y
3 2
6 7 6 6 7 6 6 7 6 6u7 6 6 7 6 6 7 6 6 7 6 6 7 6 7 6 E6 6 m 7¼6 6 7 6 6 7 6 6 7 6 6p7 6 6 7 6 6 7 6 4 5 4 e
Xb
3
7 2 u 3 2 Ar 2 7 7 6 7 6 u 0 7 7 6 7 6 7 6 7 6 6 6 0 7 6m7 6 7 6 7 7 6 0 7 7¼6 7V6 7 6 7 6 7 6 0 7 6p7 6 7 6 7 6 6 7 0 7 4 5 4 7 0 e 5 0
0
0
Ir2m
0
0
Ir2p
0
0
0
3
7 7 7 0 7 7 7 7 7 0 7 7 7 5 2 Ire
101
2 with ru2 =h2ry2,rm =vry2,rp2,rp2 =(rvh2)ry2, r2e =(1r) 2 ry , A: relationship matrix, I: identity matrix, h2: heritability, r: repeatability, v: ‘‘maternal’’ component of variance. Relationship matrix includes all animal performers and nonperformers, reproducers and nonreproducers. Lines of the Z matrix corresponding to nonperformers are filled with zeros.
2.3. Estimating breeding values Equations obtained by minimisation of the error variance for estimating the effects of the model described above are as follows: 2
XVX
XVZ
XVW
6 6 6 6 ZVX ZVZ þ t1 A1 ZVW 6 6 6 6 6 WVX WVZ WVW þ t2 I 6 6 4 ZVW ZVZ ZVW 3 2 3 2 XVy b 7 6 7 6 7 6 7 6 7 6 7 6 6 u 7 6 ZVy 7 7 6 7 6 7 6 7 6 6 7¼6 7 7 6 7 6 6 m 7 6 WVy 7 7 6 7 6 7 6 7 6 5 4 5 4 ZVy p
XVZ ZVZ WVZ
3 7 7 7 7 7 7 7 7 7 7 7 5
ZVZ þ t3 I
with: t 1 =(1 r)/h 2 , t 2 =(1 r)/v, t 3 =(1 r)/(r h2 v), resolution of these equations and calculation of the precision are shown in Tavernier (1988). Genetic parameters for jumping have been estimated by Langlois (1975b, 1980a) and Tavernier (1986). Repeatability is 0.45, maternal component of variance 0.05, and heritability 0.20. For trotting, the genetic parameters have been estimated by Langlois (1984a, 1986, 1989) and [Tavernier (1989a,b). Heritability is 0.26, repeatability 0.36, and maternal component of variance 0.04. For gallop races, the genetic parameters used are the last estimated by Langlois et al. (1996). In flat
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Table 1 Percentage of born horses having earnings at a given age Activity
Breed
Age (years) 2
Jumping
SF + AA (% of the total)a
Trotting Flat races Steeplechases and hurdle races
TF Thoroughbred Thoroughbred
Career 3
–
–
0.04 0.16 –
0.25 0.32 0.08
4
5
6
0.22 (0.90) 0.27 – 0.10
0.29 (0.82) 0.18 – 0.07
0.29 (0.76) – – –
0.42 (0.75) 0.32 0.35 0.16
Abbreviations: SF = ‘‘Selle Francßais’’; AA = Anglo-Arab; TF = ‘‘Trotteur Francßais’’. a Jumping competitions are open to racing breeds.
races, such as steeplechases and hurdle races, heritability is 0.25 and maternal component of variance is 0.05, repeatability being 0.38 and 0.44, respectively. They are in concordance with our previous results (Langlois 1975a, 1980b). 2.4. Expected regressions and correlations between breeding value and future performances
where R is the precision of I (correlation of I with A) and c is the correlation of I with E rI ¼ RrA ¼ RhrP rE ¼ erP By definition of e, which lead to CovðI; PÞ ¼ R2 r2A þ cRher2P
Let I be the animal model BLUP Index estimator of the additive genetic value A of a horse for the aptitude to a given discipline (jumping, trotting races, flat races, hurdle races and steeple chases). Let P be the measure of the horse performance: P ¼AþE where E is a residual error mainly due to the effect of environment. We can write: CovðI; PÞ ¼ CovðI; AÞ þ CovðI; EÞ CovðI; AÞ ¼ RrI rA and Cov(I, E) = crIrE
and to the regression of performance P on I bP =I ¼
CovðI; PÞ R2 h2 r2P cRher2P ¼ 2 2 2 þ 2 2 2 r2I R h rP R h rP
which give after simplifications bP =I ¼ 1 þ c
1 e R h
If c = 0 the value of that regression is 1 and deviation from 1 gives a tool to evaluate c the correlation between BLUP evaluation and environmental effect on performance. If such a correlation exists, it induces a genotype by environment correlation s = Rc between A and E.
Table 2 Population structure Breed
SF + AA
TF
Thoroughbred
Activity
Jumping
Trotting
Flat races
Steeplechases and hurdle races
Considered career (years) Mean number of yearly performances per horse having earnings Mean yearly number of offsprings born per stallion Mean age of reproducers
4–6 1.9 9.3 11.6
2–5 2.3 14.0 11.3
2–3 1.4
3–5 1.6
Abbreviations: SF ‘‘Selle Francßais’’; AA = Anglo-Arab = TF = ‘‘Trotteur Francßais’’.
6.6 10.6
B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107 Table 3 BLUP at birth and their coefficients of determination (CD) of placed (1) versus unplaced (0) of horses born in the first year of the studya Breed and birth year
Placed = 1, Variable n unplaced = 0
Saddle breeds in jumping (1988)
1 1 0 0
BLUP CD BLUP CD
3628 3628 4462 4462
7.3 0.21 4.3 0.19
All breeds in jumping (1988)
1 1
BLUP CD
4869 4869
5.4 6.1 0.18 0.08
‘‘Trotteur Francßais’’ 1 in trotting 1 (1989) 0 0
BLUP CD BLUP CD
3549 21.0 3549 0.30 7171 18.5 7171 0.29
5.9 0.04 5.8 0.04
Thoroughbred in flat races (1991)
1 1 0 0
BLUP CD BLUP CD
2345 21.9 2345 0.26 3212 18.6 3212 0.25
5.3 0.07 6.3 0.07
Thoroughbred in steeplechases and hurdle races (1990)
1 1 0 0
BLUP CD BLUP CD
1009 1009 4612 4612
3.5 0.08 3.0 0.07
For trotting, birth years 1989 and 1990 were chosen to check the performances from 1991 to 1996. For flat races, birth years 1991 and 1992 were chosen to check the performances from 1993 to 1996. For steeplechases and hurdle races, birth years 1990 and 1991 were chosen to check the performances from 1993 to 1996. BLUP breeding value estimations at the moment of conception do not include the performances from the year before the birth to 1996. The same principle is applied + 1 year for yearlings and + 3 years for 3year-old sport horses. Table 1 gives the percentage of horses born with obtaining earnings at given ages in the studied disciplines. Table 2 gives information on the population structure. This is similar to that currently encountered for horse populations: too many stallions, a low replacement rate leading to animals that are too old with few offspring per reproducer, and a long generation interval. Table 3 allows estimation of the selection pressure realised when considering only horses with earnings. As a first example, the overall mean for saddle breeds (SF + AA) can be calculated from lines 1 and 3 of Table 3; i.e. 5.6. Intensity of selection i=(7.3 5.6)/ 5.5 = 0.309, which implies a selection rate p = 0.83, is far from the percentage of selection 0.42 presented in Table 1. The same calculation for trotters gives i = 0.288 which implies a selection rate p = 0.85 which is far from the 0.32 presented in Table 1.
Mean S.D.
6.9 0.18 5.8 0.13
103
5.5 0.06 5.6 0.07
a The results for the second birth year and for BLUP as yearling or as 3 year olds are very similar and are not given.
2.5. Birth year tested For jumping, birth years 1988 and 1989 were chosen to check the performances from 1992 to 1996.
Table 4 Linear relationship between the annual phenotypic index and the BLUP breeding value estimation at the moment of conception and at 3 years of age for jumping horses (all breeds) (mean for birth years 1988 and 1989) Performance at 4 years of age
Performance at 5 years of age
Performance at 6 years of age
Mean performance of the career
Number of horses
4203
6031
6385
9569
Regression coefficient on the BLUP at conception Expected correlationa Obtained correlation
0.76
1.03
1.02
0.95
0.20 0.35
0.20 0.36
0.20 0.34
0.25 0.39
0.75
1.00
1.02
0.93
0.21 0.36
0.21 0.38
0.21 0.36
0.28 0.40
Regression coefficient on the BLUP at 3 years of age Expected correlationa Obtained correlation a
Calculated from heritability, accuracy of the Blup and the reduction of variance in the mean performance of the career.
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B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107
Table 5 Linear relationship between the annual phenotypic index and the BLUP breeding value estimation at the moment of conception and as yearling for trotters (mean for birth years 1989 and 1990) Performance at 2 years of age
Performance at 3 years of age
Performance at 4 years of age
Performance at 5 years of age
Mean performance of the career
Number of horses
808
5402
5837
3923
7029
Regression coefficient on the BLUP at conception Expected correlationa Obtained correlation
0.60
0.76
0.89
0.75
0.79
0.28 0.17
0.28 0.22
0.28 0.26
0.28 0.21
0.33 0.26
0.59
0.79
0.92
0.76
0.81
0.28 0.17
0.28 0.23
0.28 0.26
0.28 0.22
0.33 0.26
Regression coefficient on the BLUP as a yearling Expected correlationa Obtained correlation a
Calculated from heritability, accuracy of the BLUP and the reduction of variance in the mean performance of the career.
For thoroughbreds in flat races, i = 0.189 which implies a selection rate p = 0.90, also far from the 0.35 presented in Table 1. The situation in steeplechases and hurdle races gives i = 0.257 which implies a selection rate p = 0.86, again far from the 0.16 presented in Table 1. One can observe from this data that the selection bias is not as important as it first appears. We can also note that the other birth years and BLUP as yearling or as 3 year olds gave similar results.
performance. Table 8 gives the estimates of these correlations from the observed data. It reveals that they are quite low, if they exist. From a practical point of view, breeding value estimation at the moment of conception has a correlation of 0.39 with further performances in jumping and 0.33 with those of flat races. In these two cases, the correlations exceed the expected values (0.25 and 0.27, respectively). In the case of trotting races, steeplechases and hurdle races, correlations of 0.33
3. Results
Table 6 Linear relationship between the annual phenotypic index and the BLUP breeding value estimation at the moment of conception and as yearling for flat races (mean for birth years 1991 and 1992)
Tables 4 –7 give the detailed results for jumping, trotting races, flat races and steeplechases and hurdle races, respectively. Predicting performance through breeding value evaluation at the moment of conception overevaluated the level of performance actually achieved by 5%, 21% and 20%, respectively, for jumping, trotting, and steeplechases and hurdle races. On the contrary, it underevaluated by 18% in the case of flat races. The situation was similar for predicting performance at the moment of the sale (as yearlings or as 3-year-old sport horses). For jumping it was suboptimal, as already discussed by Tavernier (1994). In the other cases, we have either an over- or underestimation of the realised heritability or we have to take into account a correlation between breeding value estimation at the beginning of the career and further environmental effects on
Performance Performance Mean at 2 years at 3 years performance of age of age of the career Number of horses
1928
3792
4383
Regression 0.77 coefficient on the BLUP at conception Expected correlationa 0.26 Obtained correlation 0.21
1.23
1.18
0.26 0.31
0.27 0.33
0.79
1.25
1.21
0.26 0.23
0.26 0.33
0.28 0.34
Regression coefficient on the BLUP as a yearling Expected correlationa Obtained correlation
a Calculated from heritability, accuracy of the BLUP and the reduction of variance in the mean performance of the career.
B. Langlois, C. Blouin / Livestock Production Science 87 (2004) 99–107
105
Table 7 Linear relationship between the annual phenotypic index and the BLUP breeding value estimation at the moment of conception and as yearling for steeplechases and hurdle races (mean for birth years 1990 and 1991) Performance at 3 years of age
Performance at 4 years of age
Performance at 5 years of age
Mean performance of the career
Number of horses
1013
1296
856
1986
Regression coefficient on the BLUP at conception Expected correlationa Obtained correlation
0.71
0.90
0.69
0.80
0.20 0.13
0.20 0.16
0.20 0.12
0.22 0.15
0.86
0.88
0.78
0.86
0.22 0.17
0.22 0.15
0.22 0.15
0.24 0.17
Regression coefficient on the BLUP as a yearling Expected correlationa Obtained correlation a
Calculated from heritability, accuracy of the BLUP and the reduction of variance in the mean performance of the career.
and 0.22 were expected but only 0.26 and 0.15 are obtained, respectively. Age by age, the results showed that agreement between expected and obtained values were generally better for performances obtained in older horses. Total expression of the performance potential was probably not regularly achieved in young animals. For the two birth years tested, agreement was generally good. The rare exceptions (2-year-old trot-
Table 8 Interpretation of the difference to 1 of the regression coefficient of the mean performance (P) on the BLUP at conception and as yearlings or 3 years old (I ) for jumpers in terms of genetic/ environment correlation Discipline
bP/I
CD
c
s
Jumping Conception 3 years old
0.95 0.93
0.19 0.22
0.01 0.01
0.00 0.00
Trotting races Conception Yearling
0.79 0.81
0.31 0.30
0.07 0.06
0.04 0.04
Flat races Conception Yearling
1.18 1.21
0.27 0.28
+ 0.06 + 0.06
+ 0.03 + 0.03
Steeplechases and hurdle races Conception 0.80 0.19 Yearling 0.86 0.18
0.05 0.03
0.02 0.02
CD: mean coefficient of determination of the BLUP; c: estimated correlation of the BLUP and environmental effect on performance; s: induced genetic/environment correlation.
ters) can easily be explained by certain changes in data management (anniversary date changing from December 31 to September 15 in 1992). Between the moment of conception and that of sale, the slight increase in accuracy and in efficacy is surprising. This is due to a large dispersion of the annual information over too many stallions. This is a characteristic of horse breeding structures (small number of mated mares per stallion and great variance of family size).
4. Discussion The results of this study indicate that breeding value estimations proposed in France to optimise the use of earnings in competitions for breeding purposes are doing well for sport horses selected for jumping. In this case, BLUP breeding offers a correlation close to 0.40 with the future performance of the horse. This is much higher than traditional methods based on the appreciation of conformation and gaits for which similar efficiency was found between 0.10 and 0.15 by Langlois et al. (1978). In the case of race horses, we can distinguish between flat races, where there was a correlation of 0.33 but where breeding value estimations systematically underestimated the level of performances achieved, and the case of trotting races and steeplechases/hurdle races with, respectively, a correlation of 0.26 and 0.15 and which overestimated the level of performances. In the case of trotting, the underesti-
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mations are certainly not so important because the change of the anniversary date shortened the career of ages 2 and 3 for horses born in 1990 and after. This hardly impacts on the regressions presented for ages 2 and 3 leading to a general underestimation of observed results. Assuming that the values for heritabilities used are true, Table 8 shows that the breeding value estimations and environmental effect on performances have a correlation of only 0.06 in the case of flat races for which such a correlation is often mentioned. On the other hand, it is difficult to understand why we should have a negative correlation ( 0.03 to 0.07) for trotting or steeplechases and hurdle races. This would mean that the best pedigree horses do not have such a good environment or the reverse! It is true, however, that these hypothetical correlations seem very low. It is, therefore, more practical to ignore it and to propose some changes in the heritability values or in the model for indexation. We propose to search for heritability values that make the regression coefficient of performance on breeding value estimations shown here near to one. However, a more thorough discussion on the model is needed.
5. Conclusion Breeding value estimations with the BLUP animal model calculated according to earnings in competitions in France appears to be a very useful tool for breeders. They are suboptimal in the case of jumping and give a practical correlation with the breeding objective of 0.39. They could certainly be improved in the case of race horses. However, in their present state of development, they predict further performances rather well in the case of flat (r = 0.33) and trotting races (r = 0.26). Steeplechases and hurdle races are characterised by a low expected precision in the prediction of the performance level. The correlation achieved with the breeding objective is therefore low (r = 0.15). We would, however, recommend in that case using only a few animals with high accuracy of their breeding value estimation for this breeding objective. For all racing activities, we recommend testing new values of heritability for breeding value estimations.
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