Livestock Production Science, 16 (1987) 407-419 407 Elsevier Science Publishers B.V., Amsterdam - - Printed in The Netherlands

Contr ibut ion of Var ious Fac tors to Genet i c E v a l u a t i o n s o f S ta l l i ons

THORVALDUR .~RNASON

Swedish University o[ Agricultural Sciences, Department of Animal Breeding and Genetics, S-750 07 Uppsala (Sweden)

(Accepted for publication 9 December 1986)

ABSTRACT

Arnason, Th., 1987. Contribution of various factors to genetic evaluations of stallions. Livest. Prod. Sci., 16: 407-419.

Genetic evaluations ( B LUP) of 262 stallions were obtained for the following subjectively scored traits of the Swedish Riding Horse Quality Events: conformation, gaits, temperament in the gait- ing test, jumping ability and temperament in the jumping test. The genetic evaluations were par- titioned into the various factors included in the statistical model applied to the data. The partitioned sire solutions were compared with genetic evaluations obtained from application of an animal model. The differences between the evaluations indicated the influence of the genetic merit of mates. The following correlations were found between the estimated breeding values (from the animal model) of sires and their mates for the five traits in the same order as above: 0.101, 0.046, 0.096, 0.004, 0.020. Evaluations of genetic values within birth years (1973-1979) indicated a slightly negative genetic trend in conformation score and slightly positive genetic trend in the other four traits.

INTRODUCTION

Bes t l inear unb iased p red ic t ion ( B L U P ) p rocedures for eva lua t ing genet ic mer i t of b reed ing an imals have become widely used in r ecen t years in appl ied an imal breeding. In i t ia l ly the p rocedure was used p r e d o m i n a n t l y (on a large scale) in da i ry ca t t le breeding, bu t appl ica t ions in o th e r species have been spreading. P r o g r a m s for p rac t ica l app l ica t ion of B L U P procedures in the eval- ua t ion of G e r m a n t ro t t e r s , Icelandic Toe l t e r Horses , Swedish t ro t t e r s and Swedish Riding Horses are cu r ren t ly being developed (Dist l et al., 1982; K a t o n a a nd Distl , 1984; Arnason , 1983, 1984a; A r n a s o n et al., 1984).

F r o m a theore t i ca l po in t of view, the B L U P m e t h o d is super ior to o the r l inear procedures used for r ank ing breeding animals according to genetic merit . T h i s super io r i ty of B L U P in accuracy an d f lexibi l i ty is usual ly gained at the expense of e labora te and r a t h e r complex c o m p u t i n g efforts . M o r e o v e r the pro- cedure is usual ly r un as a k ind of a "b lack b o x " where the s imul t aneous solu-

0301-6226/87/$03.50 © 1987 Elsevier Science Publishers B.V.

408

TABLE I

Genetic parameters used in the multiple-trait analysis of Swedish Riding Home; heritabilities on the diagonal, genetic correlations above the diagonal, phenotypic correlations below the diagonal

Conformation Gaits Temperament, Jumping Temperament, gaits ability jumping

Conformation 0.20 0.39 0.51 0.21 0.21 Gaits 0.32 0.18 0.87 0.38 0.40 Temperament, gaits 0.23 0.66 0.15 0.38 0.47 Jumping ability 0.14 0.25 0.32 0.17 0.96 Temperament, jumping 0.13 0.23 0.32 0.85 0.18

tions to the random and fixed factors of the model make it impossible to recognize the importance of different effects pertaining to specific animals. The researcher may have the necessary skill and training to grasp the method and perform the computations, confident in the knowledge that for correct model and correct genetic parameters (variance) the procedure will yield the "best" evaluations. Yet he may have difficulty in answering and convincing practical breeders, whose questions often concern specific animals. Schaeffer (1983) showed how BLUP sire evaluations could be split up into contributions from the different factors included in the model. The objective of this paper was to apply the technique to scrutinize genetic evaluations of Swedish riding stallions and to examine the consequences in different models.

MATERIALS AND METHODS

The data comprised records on 2347 horses entered in the Swedish Riding Horse Quality Events (a performance test) between 1973 and 1983. The horses recorded were sired by 262 stallions. Most of the horses were 4 years old when recorded but some 5 year olds were also represented. The following characters were scored on a scale of 0-10 points: (1) conformation; (2) gaits; (3) temper- ament in the gaiting test; (4) jumping ability; (5) temperament in the jumping test.

A more thorough description of the traits was published by Thafvelin et al. (1980). The heritabilities, together with other genetic parameters, were esti- mated by B. Thafvelin (unpublished results, 1983). The genetic variance/co- variance matrix was not positive definite, however, and was therefore modified by the bending procedure (Hayes and Hill, 1981; Arnason, 1984b) before the application of a multivariate model. The use of a bending factor of 0.4 resulted in the genetic parameters shown in Table I.

The following linear model was applied to each of the five traits:

Yijhl = [i + gj + 8h + eijkt (1)

409

where: Y,jk~ is the observed score on t h e / t h progeny, fi the effect of ith scoring event {year/place; i= 1 , . . . , 72), gj the effect o f j t h sex ( l = m a l e ; 2 = m a r e without foal; 3 = mare with foal) , sh the random effect of the kth sire and e~j,~ a random residual term.

The linear model for the sire evaluation can be rewritten in matrix notat ion as:

2 y= ~ X ibi-~-Zs-4- ~ (2)

i=1

where: y is a vector of observed scores, bi is an unknown vector of fixed effects within a particular factor i, s is an unknown vector of sire effects, e is a vector of random residuals and ~Xi and Z are known incidence matrices.

The following mixed model equations were solved for each trait: [ 11.dn 12. n Q 00][ ln ] [01 T 21 .dn z'g+T22.d. Z 'Zl Z'X2 Q 82n Z~'Yn Q' z i g Z l Z 1 Z l Z 2 Q bln ZlYn (3) Q' Z2Z ~Z2 ~Zl ~X2 ~X2 ~ ~2n ~Z2Yn 9' o' .o' !' 0 o "

where dn is the term ( 4 - 2 2 ^ h , ) / h , , s l , is a vector of sire evaluations pertaining to ancestor stallions without progeny records of their own, ~2, is a vector of sire evaluations for the 262 stallions having progeny in the data,

V~- T21 T22 = ~21 ~22 = 4 -1

the inverse of A (328x328) the matrix of additive genetic relationship between stallions in vector ~, = ( ~ , ~ , ) and y is a Lagrange multiplier constraining the sex effects to sum to zero.

The mixed-model equations above were solved by iteration both for a single trait model, where the genetic and environmental correlations were ignored, and for a multi-trait model taking the correlations into account. Since all traits were recorded simultaneously for the same animals, computat ion could be facilitated by canonical t ransformation of the data (Arnason, 1982 ).

For the five runs on the t ransformed data, the d , values, the functions of the t ransformed heritabilities became: dl = 192.57; d2 = 53.44; d3 = 26.07; d4 = 20.03 and d~=17.10, corresponding to the following t ransformed heritabilities:

h .2 ^- h*~=0.02; 2=0.u't; =0.15; =0.19 and =0.22. As shown by Schaeffer (1983) the sire evaluations can be writ ten for each

trait as (ignoring the subscript n) :

q

i=1

410

In this particular study q=6, where: t l - - ( Z ' Z ) - l Z ' y = progeny average, t2=-( .Z ' .Z) . I .Z ' .XI .8°= average year]place effects per offspring, t3 - "- (Z'.Z) -1.Z X2b ° = average sex effects per offspring, t4 = - (.Z'.Z) -'l~°~d = average regression to the population mean per offspring, t5 = - ( .Z' .Z) -1 ( T12S o + Tl1.~o _So ) "d -= average adjustment per offspring due to additive genetic relationship among stallions included in vector $o and ~ ,

( q - - l )

te =Sl*-- ~ ti = average adjustment per offspring due to the application of i = 1

multi-trait sire model. The ~* vector used to calculate t6 is the back-transformed multi-trait solu-

tion vector from the runs on the transformed data. The other solutions b0 and S ° are from the single-trait analyses on untransformed records. Therefore te includes an adjustment both for the genetic evaluations of correlated traits and for the difference in other factors between the single- and multi-trait models.

The sire evaluations were expressed in scaled relative breeding values (RBV). The RBV of the kth sire was calculated for each trait as RBVhn = 100 + ~h, 20/SDAn, where SDAn is the estimated genetic standard deviation of trait n.

A multi-trait animal model (Henderson and Quaas, 1976; Arnason, 1984a) was applied to the data. The s vector of sire effects was replaced by a vector a in the model, where a represents breeding values of the 2347 individual animals with records in the data set plus 2323 breeding values of unrecorded sires, dams, maternal grandsires and other unrecorded ancestors.

The relative breeding values from the animal model were expressed for each animal as RBVhn = 100 + dh, 10/SDA, so that the distribution scale of breeding values from the animal model and the sire models were directly comparable.

The data, y*, were transformed canonically and the following mixed-model equations were set up for each trait:

T n . d Tin.d*

T21.d * I + T22.d* n ~ ~ t l

o' x'l O '

5'

0 0 0]i, ] [ ] ~ I n 0 ¢ kl 32 6 X{.X~ .X{X2 5 b*~l,, ---- ,~{:y* (4) X Xl x. i i. O' 1' 5 y 0

__ g* g* * * where: d.-Ro.,dGo,.~= 1/gonn'Ro is the random environmental variance/co- variance matrix of the five traits, transformed to be an identity matrix and G~ is the corresponding genetic variance/covariance matrix transformed to diagonal form..T is the partitioned, A. - 1, inverse of the additive genetic rela- tionship between the 4670 individual animals included in vector .~*'= (.dT~ ^ * r ~ a 2 n ) •

The sires included in the sire evaluations, vector S. in eqn. (3), were all represented in vector d* of the animal model genetic evaluations (eqn. 4) ~ l n •

The difference in genetic evaluations of sires between the two models was the result of including dams in the animal model. Most dams lacked individual records, but they were related to other recorded animals. By their pedigree ties

TABLE II

Estimates of sex differences

411

Sex classes Traits

Confor- Gaits Temperament , Jumping Temperament, mation gaits jumping

Male 0.03 0.20 0.15 0.11 0.11 Mare with foal - 0.08 - 0.08 - 0.05 - 0.01 0.01 Mare without foal 0.05 - 0 . 1 3 - 0 . 0 9 - 0 . 1 0 - 0 . 1 2

they received predictions of genetic merit which influenced the genetic predic- tion of their mates. In other words, the solutions from the animal model, per- taining to stallions with progeny in the data set, were simultaneously corrected for the predicted genetic merit of the mated mares. Therefore t7 = (the part of ~* pertaining to sires of recorded horses) -.sl = the average adjustment per off- spring for estimated genetic merit of mates.

The variance of elements in ti was calculated in order to observe the impact of different factors on the genetic evaluations.

Correlations between the estimated breeding values ( from the animal model) of mates were calculated for all traits to see if there might be any indication of genetic assortative (or disassortative) matings.

Correlations between breeding values computed from the different models applied were computed. The mean breeding values of mates were also calcu- lated ( and listed for inspection) for each sire represented in the data.

Finally, the average breeding values of recorded animals within different birth years were computed. The genetic trend was estimated by simple regres- sions of annual genetic merit on years. Animals born before 1973 were so few that they were excluded from the calculation of genetic trend.

RESULTS AND DISCUSSION

The best linear unbiased estimates (BLUE) of the sex effects obtained by the analysis on the sire model are shown in Table II. The estimates were con- strained to sum to zero for each trait. The males were superior to the other sex classes as far as gaits, jumping ability and temperament in gaits and jumping trials were concerned. The mares with foals were the most inferior as regards the same traits. On the other hand, mares with foals received the highest scores for conformation, while mares without foals formed the inferior class and males were intermediate.

The partitioned sire evaluations, together with genetic evaluations from the animal model, are illustrated for three stallions in Table III. Nepal 390 for

TA

BL

E III

Exam

ple

of sire e

valuations partitioned into co

mpon

ents

for th

e following five tr

aits: 1 = co

nfor

mati

on;

2 = gaits; 3 --t

empe

rame

nt in gaiting test;

4 =j

umpi

ng a

bility; a

nd 5 = t

empe

rame

nt in jum

ping

test

~=~

t,D

Sire

name

No. of

and herd-

off-

book

num

ber

spring

Tra

it

Eval

uati

on c

ompo

nent

s

Pro

g

Yea

r/

Sex

R

egre

s-

Rel

atio

n-

Co

rrel

a-

~ ti

M

ate

s A

nim

al

aver

ages

p

lace

si

on

sh

ip

tio

ns

i= 1

m

od

el

Jarr

amas

367

12

89

9

1 0.

5 0.

5 0

100

8 10

8 11

3 -0

.5

-3

-5.5

0

0 10

4 1

105

121

1 -2

-

13.5

-4

.5

1 10

3 3

106

96

14.5

-

1 -6

-0

.5

0 10

3 4

107

94.5

14

.5

--1

.5

-4.5

-

1 0

102

6 10

8

Nep

al 3

90

114

112

7 0.

5 -2

.5

3 1

121

1 12

2 10

8 4

-3

-1

0 1

109

1 11

0 10

5 8

-2

-2

-2

3 11

0 1

111

101

5 -1

-

1 0

2 10

6 0

106

101

6.5

- 1

- 1

0.5

0 10

6 0

106

Utr

illo

432

76

10

7 3

1 -2

5

0 11

4 -3

11

1 10

7 3

-4

- 1

3 1

109

1 11

0 10

3.5

0 -3

-0

1.

5 2

104

- 1

105

123

- 1.

5 -0

.5

-4.5

-

1.5

1 11

6 1

117

114.

5 1.

5 -

1.5

-2.5

-2

2

112

0 11

2

413

example, had 114 progeny recorded in the data. His relative breeding value from the sire evaluation for conformation was 121 points, which included 112 from his raw progeny average; he gained 7 for the year/place effects (his off- spring have commonly been judged at scoring events where the judges have generally awarded low scoring marks for conformation); he received 0.5 points for sex effects as he had many female progeny; he was regressed downwards 2.5 points (positive evaluations, corrected for fixed effects, are regressed down- wards and negative evaluations upwards. The size of the regression is domi- nated by the size of the heritability and by the number of progeny on which the evaluation is based.) He gained 3 points through the relationship matrix and he gained 1 point from positive genetic evaluations on correlated traits.

The slight difference in estimated breeding values of Nepal 390 for confor- mation, obtained from the animal model versus the sire model shows that his mates were almost average in genetic merit for body conformation.

The variances of the elements of the partitioned factors are shown in Table IV. The difference in progeny averages was clearly the most important source of variation in the sire evaluations. The regression and the year/place adjust- ments were of great importance too. The variance in the genetic evaluations of the stallions was dominated by variances among the three factors tl, t2 and h. Inclusion of inaccurately evaluated sires with few recorded offspring~inflated the variation in sire evaluations. By comparing the figures in Table IV outside and within the parentheses, the variations in progeny averages, year/place effects, sex effects and in the regressions towards the population mean, were substantially reduced when sires with small progeny groups were excluded. The variations in adjustments for relationship, correlations and genetic merit of mates were less affected by the size of progeny groups.

The means and variation of breeding values obtained from sire vis-a-vis ani- mal model for the five different traits are shown in Table V. If all animals were unrelated the mean breeding value of all animals included in the solution vec- tors would be 100 for all traits. When the relationship matrix is included, the mean breeding value of 100 refers to the "base" population of animals without registered parentage in the data (Henderson, 1976). The estimated breeding values were weighted by the elements of the inverse of the relationship matrix, which causes a slight average deviation from 100, according to the selection intensity achieved and the genetic parameters assumed. The relative breeding values were scaled so that 10 units would equal one genetic standard deviation. The standard deviations of the estimated breeding values were approximately 50% of the genetic standard deviation for all traits. The first trait, body con- formation, had slightly higher heritability (see Table I) and this may be reflected in a slightly larger variation in estimated breeding values for this particular trait.

For the animal model the following correlations were found between the estimated breeding values of sires and their mates. For conformation, r-- 0.101;

TA

BL

E I

V

Var

ianc

es o

f ele

men

ts w

ithi

n ea

ch p

arti

tion

ed c

ompo

nent

(ti

) fo

r th

e va

riou

s tr

aits

. V

aria

nces

of

all

262

sire

eva

luat

ions

are

out

side

the

par

en-

thes

es; w

ithi

n th

e pa

rent

hese

s on

ly e

valu

atio

ns o

n 18

7 si

res

wit

h 15

or

mor

e of

fspr

ing

wer

e in

clud

ed

Partition c

ompo

nent

Traits

Conformation

Gaits

Temp

eram

ent,

Ju

mpin

g Te

mper

amen

t,

gaits

jump

ing

tl=

Pro

geny

aver

age

1022

.9 (

160.

2)

1073

.4 (

167.

6)

1593

.5 (

183.

9)

976.

1 (1

37.8

) 96

2.0

(124

.7)

t2=

Ave

rage

year

/pla

ce

146.

5 (3

0.3)

13

2.6

(30.

4)

291.

6 (4

0.6)

14

9.5

(35.

8)

210.

8 (5

0.7)

ad

just

men

ts

t3 =

Ave

rage

sex

cla

ss

4.7

(0.3

) 19

.6

(1.9

) 11

.0

(1.1

) 1.

5 (0

.2)

1.1

(0.1

) ad

just

men

ts

t4=

Ave

rage

regr

essi

on

670.

0 (2

0.7)

78

7.5

(30.

8)

991.

7 (4

1.3)

66

4.6

(17.

1)

574.

8 (1

2.5)

ad

just

men

ts

t5 =

Ave

rage

rela

tion

ship

9.

7 (4

.7)

3.7

(2.9

) 2.

9 (2

.6)

3.9

(3.1

) 3.

0 (3

.0)

mat

rix

adju

stm

ents

te

= A

vera

ge a

djus

tmen

ts

0.7

(0.7

) 0.

6 (0

.4)

3.6

(4.7

) 1.

6 (2

.1)

0.5

(0.6

) fo

r cor

rela

ted

trai

ts

t7 =

Ave

rage

adj

ustm

ents

5.

4 (3

.2)

2.3

(1.8

) 2.

5 (2

.4)

3.5

(3.1

) 2.

5 (3

.3)

for g

enet

ic m

erit

of

mat

es

415

TABLE V

Number {N), mean (2), standard deviation (S.D,), minimum (Min.) and maximum {Max.) values of relative breeding value estimations (BLUP) from sire and animal model respectively

Trait N 2 S.D. Min. Max.

Conformation Sire model 326 102 6 67 121 Animal model 4670 103 5 81 122 Stallions in animal model 442 102 5 85 122

Gaits Sire model 32~ 100 4 81 115 Animal model 4670 101 4 84 116 Stallions in animal model 442 100 4 85 115

Temperament, gaits Sire model 326 100 4 79 113 Animal model 4670 101 4 84 117 Stallions in animal model 442 101 4 86 115

Jumping Sire model 326 100 4 75 116 Aaimal model 4670 101 4 85 117 Stallions in animal model 442 100 4 88 117

Temperament, jumping Sire model 326 100 4 85 112 Animal model 4670 101 4 85 114 Stallions in animal model 442 100 3 87 114

for gaits, r = 0.046; for temperament in gaiting test, r = 0.096; for jumping abil- ity, r = 0.004; and for temperament in jumping trial, r = 0.020. The very low correlations for the jumping events indicate an absence of significant genetic assortative mating for jumping talent, though some slight genetic assortative mating might be taking place for body conformation and gaiting temperament.

Product moment and rank correlations between breeding values of sires for four different models are shown in Table VI for the traits conformation, gaits and jumping. Rank correlations and the product moment correlations are of similar magnitude, ranging from r = 0.82 to r = 0.99. The correlations between breeding values from single and multiple trait sire models, respectively, are very high. Inclusion of correlated traits had in this case only a minor effect on the predicted breeding values. It is well known that the expected improvement from inclusion of positive genetic and environmental covariance is less marked for sires having many offspring in the data than for non-parents in individual animal models (Schaeffer, 1984 ). The extra computational labour associated with multiple trait and the canonical transformation is trivial, however.

416

TABLE VI

Correlat ions between breeding values of sires for four different models and three trai ts . Product momen t correlat ions above the diagonal. Rank correlat ions below the diagonal

Models

Single t ra i t Mult iple t ra i t Animal model (4) wi th A - 1

(1) Wi thou t A 1 Wi th A -1 (2) (3)

Trait Conformation

Gaits

Jumping

(1) - 0.836 0.990 0.927 (2) 0.816 - 0.841 0.849 (3) 0.987 0.827 0.925 (4) 0.922 0.818 0.932 -

( 1 ) - 0.907 0.987 0.936 (2) 0.880 - 0.911 0.902 (3) 0.979 0.891 0.947 (4) 0.913 0.880 0.934 -

( 1 ) - 0.839 0.959 0.861 (2) 0.824 - 0.886 0.887 (3) 0.938 0.867 - 0.911 (4) 0.861 0.850 0.920 -

The correlations between breeding values from multiple-trait sire models with and without inclusion of the inverse of the relationship matrix, respec- tively, were somewhat lower. The values ranged from r = 0.83 to r = 0.91 indi- cating that ranking of sires is in some cases considerably affected by the genetic evaluations of related sires.

The high correlations between breeding values of sires from multiple trait sire models including A - 1 and from the animal models, respectively, indicate very little change in ranking. As assortative mating does not generally seem to be an important source of bias in this material, the use of the animal model solely for evaluation of sires is hardly worthwhile. The problems of non-ran- dom mating structure may be more serious in some other horse populations (Katona and Distl, 1986; Tavernier, 1986). However, the main potential advantage of the animal model compared with sire models is its ability to give early predictions of breeding values of young stallions and broodmares.

The average genetic values within birth years 1973-1979, from the animal model, are displayed in Fig. 1. The results show a slightly negative trend in conformation score and a somewhat more prominent positive genetic trend in the other four traits. The following linear regression coefficients of the annual average genetic merit on birth years were found. For conformation, b = 0.003

417

Average genetic value

0.15

01&

013

0.12

0.11

010

009

O.OB

0.07

006

005

004

0.03

002

001

0 O0

-001

Conformation

x .Io

Temper gaits

Gaits

TemPer jumping

Jumping

m i h

1973 7& 7'5 76 ?17 7~8 719 Year of birth

Fig. 1. Genetic trends exhibited as average breeding values of horses born in the years 1973-1979.

NS; for gaits, b = 0.008**; for temperament in gaiting test, b = 0.004*; for jump- ing ability, b=0.012*; and for temperament in jumping trial, b=0.010* ( **P < 0.01; *P < 0.05; NS = not significant). These results span a short period and are therefore hardly conclusive; however, they do suggest the possibility that during the last 15 years, selection has become more intense for the quality of gaits and for jumping performance at the expense of selection for body con- formation in the population of the Swedish Riding Horse.

ACKNOWLEDGEMENT

Erik Philip-S6rensen's Foundation is acknowledged for financial support of this work.

REFERENCES

Arnason, Th., 1982. Prediction of breeding values for multiple traits in small non-random mating (horse) populations. Acta Agric. Scand., 31:171-176.

Arnason, Th., 1983. Genetic Studies on Conformation and Performance of Icelandic Toelter Horses.

418

Report 59, Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics, Uppsala.

Arnason, Th., 1984a. Genetic studies on conformation and performance of Icelandic Toelter Horses. IV. Best linear unbiased prediction of ten correlated traits by use of an "animal model". Acta Agric. Scand., 34: 450-462.

Arnason, Th., 1984b. Genetic studies on conformation and performance of Icelandic Toelter Horses. II. Construction of multitrait selection indices and modification of covariance matrices by the "bending" method. Acta Agric. Scand., 34" 428-439.

Arnason, Th., Bendroth, M. and Philipsson, J., 1984. Genetic evaluation of Swedish Trotter stal- lions by the BLUP-method. Paper presented at 35th Annual EAAP Meeting, The Hague.

Distl, van O., Katona, O. and Kr~iusslich, H., 1982. Vergleich der Zuchtvertsch~itzmethoden BLUP und CC beim Traber ( Comparison of the BLUP and CC methods in the German trotter pop- ulation). Zfichtungskunde, 54:157 - 164.

Hayes, J.F. and Hill, W.G., 1980. Modification of estimates of parameters in the construction of genetic selection indices ("bending"). Biometrics, 37: 483-493.

Henderson, C.R., 1976. A simple method for computing the inverse of a numerator relationship matrix used in prediction of breeding values. Biometrics, 32: 69-83.

Henderson, C.R. and Quaas, R.L., 1976. Multiple trait evaluation using relatives records. J. Anim. Sci., 43: 1188-1197.

Katona, 0. and Distl, von O., 1984. The influence of mating structure on progeny test results (estimated breeding values) in the German trotter population. A paper presented at 35th Annual EAAP meeting, The Hague.

Katona, O. and Distl, von 0., 1986. Adjusting procedures in sire evaluation to the non-random mating structure in the German trotter population. A paper presented at 37th Annual EAAP meeting, Budapest.

Schaeffer, L.R., 1983. Technique for partitioning sire evaluations. J. Dairy Sci., 66: 1519-1527. Schaeffer, L.R., 1984. Sire and cow evaluation under multiple trait models. J. Dairy Sci., 67:

1567-1580. Tavernier, A., 1986. Advantage of BLUP animal model for the qualification of broodmares. A

paper presented at 37th Annual EAAP meeting, Budapest. Thafvelin, B., Philipsson, J. and Darenius, A., 1980. Genetic studies on riding horse traits under

field conditions. A paper presented at 31st Annual EAAP Meeting, Munich.

RESUME

Arnason, T., 1987. Contribution de diff~rents facteurs h l'~valuation g~nStique des Stalons. Livest. Prod. Sci., 16:407-419 (en anglais).

II a ~t~ proc~ig ~ l'estimation de la valeur g~n~tique (BLUP) de 262 ~talons pour les caract~res suivants notes subjectivement dans les concours de chevaux de selle su~dois: le module, les allures, le temperament jug~ d'apr~s les allures, l 'aptitude au saut et le tempdrament jug~ dans l'~preuve de saut. Les estimations ont ~t~ fragment~es pour chaque ~talon en fonction de l'incidence des diff~rents facteurs de variations pris en compte clans le module statistique appliqu~ aux donn~es permettant ainsi de chiffrer dans chaque cas leur influence respective sur le r~sultat. Ces estima- tions fragment~es ont ~t~ compar~es avec les valeurs g~n~tiques r~sultant de l'application d'un module animal. Les differences entre les estimations indiquent l'influence du m~rite g~n~tique des juments. On a trouv~ les correlations g~n~tiques suivantes entre la valeur g~n~tique estim~e (~ partir du module animal) des ~talons et des juments pour les caract~res indiqu~s dans l'ordre ci- dessous: 0.101, 0.046, 0.096, 0.004, 0.020. L'~volution des valeur g~n~tiques en fonction de l'ann~e de naissance entre 1973 et 1979 indique une tendance l~g~rement n~gative du progr~s g~n~tique pour la note de conformation et l~g~rement positive pour les 4 autres caract~res.

419

KURZFASSUNG

Arnason, Th., 1987. Einflul~ verschiedener Faktoren auf die Zuchtwertsch~itzung yon Hengsten. Livest. Prod. Sci., 16:407-419 (aufenglisch).

Eine BLUP-Zuchtwertschiitzung ftir 262 Hengste wurde anhand der folgenden, subjektiv bei den schwedischen Reitqualit~'tspriifungen bewerteten Merkmalen durchgefiihrt: Ktirperbau, Grundgangarten, Temperament wiihrend der Priifung der Grundgangarten, SpringvermSgen und Temperament wiihrend der Priifung des Springvermtigens. Die Ergebnisse der Zuchtwertsch~it- zung wurden in die verschiedenen, im statistischen Modell vorhandenen Faktoren aufgeteilt. Die Schtitzwerte der Vatereffekte wurden verglichen mit den Zuchtwertschiitzergebnissen aus einem Tiermodell. Die Unterschiede in den Schiitzwerten deuten auf den genetischen Einfluf~ der ange- paarten Stuten hin. Folgende Korrelationen zwischen den geschiitzten Zuchtwerten der V~iter (aus dem Tiermodell) und ihrer Paarungspartner wurden in den o.g. Merkmalen berechnet: 0.10 i, 0.046, 0.096, 0.004, 0.020. Die Analyse der Zuchtwerte innerhalb Geburtsjahren (1973-1979) zeigt einen geringfLigig negativen genetischen Trend in der Gebiiudenote und einen leicht positiven genetischen Trend in den anderen vier Merkmalen.