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TRANSCRIPT
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Estimation of Breeding Values for Milk Production Traits,Somatic Cell Score, Conformation, Productive Life and
Reproduction Traits in German Dairy Cattle
Version: August 2008Last updates:
- 08-2008: New relative weights in RZG for Angler (Red Breed); yearly shift of base forrelative EBVs for calving traits- 04-2008: Introduction daughter fertility index RZR; changes in conformation EBVs; new
weights within RZG; yearly shift of base for relative breeding values and newdefinition of base for small breeds
- 01-2008: Introduction of new model for fertility traits- 05-2007: New relative weight in RZE and RZG for Angler (Red Breed)- 05-2005: Shift of base for traits on natural scale (every 5 years)- 02-2005:New genetic evaluation for milking speed and temperament- 11-2004:New model longevity, correlations used for calculation total merit index RZG
ContentIntroductionBreeding values for milk production traits and somatic cell scores
The Random Regression ModelEBVs for Milk Production TraitsEBVs for Somatic Cell Scores
Breeding values for conformation traitsBreeding values for milking speed and temperamentBreeding values for functional herdlife
Breeding values for reproduction traitsDaughter fertilityCalving traits
Calving easeStill birth rate
Total merit indexFrequency of evaluationPublishing of data
Annex
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Estimation of Breeding Values for Milk Production Traits,
Somatic Cell Score, Conformation, Productive Life andReproduction Traits in German Dairy Cattle
IntroductionIn Germany the authorities of the federal states are responsible for the estimation of official breedingvalues. VIT is responsible for genetic evaluations for the dairy breeds German Holstein (Black & Whiteand Red & White), German Red Cattle and Jersey.
Estimation of breeding values for milk production traits and somatic cellscores with the random regression model
The Random Regression Model
A Multi-Lactation Animal Model (MTDAM) using all results from milk recording on daily base directly inthe evaluation model was introduced by VIT in 1996 to estimate breeding values for somatic cell
scores and in 1998 for milk production traits.In May 2003 VIT changed from the Fixed Regression Model to a new Random Regression Model thatestimates individual genetic lactation curves.
Data baseTest day records of cows with first lactation initiated since 1990 are considered in the geneticevaluation. All official test day records are included, if
Age of calving is: 20 - 40, 30 56 and 44 - 75 month for lactations 1, 2 and 3, respectively
Days in milk: 5. - 330. day after calving (SCS 365 days)
Pedigree informationPedigree information traces back at least four generations from cows with own yield records. If the sire
and/or the dam of an animal are unknown, fixed genetic groups are defined representing all unknownparents of animals based on breed, sex and birth year of animals and on origin (German/westernEuropean HF; eastern European HF plus SMR; North American HF; Jersey; German Red Cattle; otherRed Cattle; genetic conservation population of old German Black&White; others).
MethodThe main advantages of using the test day records directly instead of 305-day lactations in the modelare
Using the original yield record on daily base (day 5 to 330 respectively 365 for SCS) from first threelactations as yield information for evaluation instead of cumulated 305 day yields
Correction of management effects with a herd-day effect and with that the exact management effectfor each cow in each herd at a certain day
Correction of stage of lactation by simultaneously evaluated lactation curves
The special advantages of the new Random Regression Model in comparison to the previous FixedRegression Model are
Test day records within lactation are not considered as a constant trait (rg= 0.5 0.99)
Estimation of individual lactation curves instead of a constant deviation from the beginning to the endof the lactation
The individual lactation curves are predicting the EBVs more flexible, especially when only earlylactation information is available (records in progress).
The genetic parameters used in the Random Regression Model are estimated on the base of arepresentative data set of the German Holstein population (Liu et al., 2000a,b).
The Random Regression Model remains to be a multiple lactation model, i.e. the lactations 1, 2 and 3are considered as genetically different traits.
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Reliability of estimated breeding valuesReliabilities are calculated for the Random Regression Model using the multiple trait effective daughtercontribution method (Liu et al., 2001a).
EBVs for milk production traitsDetails of the evaluation for milk production traits (milk, fat and protein yield) by the RandomRegression Model are described in the following.
Standardisation of intra-herd-test-day variationIntra-herd test day variance is standardised according to production level of herd test day and numberof cows being in the same lactation within the particular herd test day.
DataTable 1 shows the amount of data processed in the evaluation
Table 1: Description of the data set used for evaluation of yield traits
April 2008 1. Laktation1
stlactation
2. Laktation2
ndlactation
3. Laktation3
rdlactation
Gesamttotal
Anzahl ProbemelkenNumber of test day records 116.154.876 83.536.178 55.981.823 255.672.877
Anzahl HerdenkontrolltageNumber of herd testdays
10.017.696 9.693.190 19.710.886
Khe mit LeistungCows with records
14.735.336
BullenSires
287.158
Tiere gesamtAnimals in total
19.901.701
The model for milk production traits
For all animals (with and without records) breeding values of the first three lactations are estimatedwith the Random Regression Model:
ijklo
m
klmklm
m m
klmklmjlmjlmilijklo epbabfhy ++++= == =
3
1
3
1
3
1
where
ijkloy is 24-hour test day yield, adjusted for heterogeneous herd variance of the o-th test day of lac-
tation lof cow k;
ilh is fixed effects of the i-th herd-test-date x milking-frequency (HTD) for lactation l;
jlmf represents the m-th regression coefficient for the j-th fixed lactation curve of lactation l;
jlm is the m-th term of Wilmink function withded
05.0
..32..1.. and,1
=== and ddenoting days
in milk (DIM);
klmklm pa and are the m-th random regression coefficient of lactation lof cow kfor genetic and perma-
nent environmental effects, respectively;
klmb is the m-th term of the third-order Legendre polynomials with
)13(5and3,1 221
3..2..1.. === zbzbb and 1150)5( = dz ; and
ijklmoe is error effect.
Selective 3-times milking is accounted for by creating separate herd-test-day groups within herd
according to milking frequency. Milking frequency is recorded for each test of each cow individually.
The genetic parameters used in the Random Regression Model are estimated on the base of arepresentative data set of the German Holstein population (Liu et al., 2000a,b). In the following table
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parameters for 305-day lactation yields, derived from the original parameters on daily basis, are listed.These cumulated parameters are higher then the parameters on daily base used in the model (seefigures).
Table 2: Genetic parameters for milk, fat and protein yield on 305-day basiswith heritability on diago-nal, genetic correlations above diagonal and phenotypic correlations below diagonal
Merkmal Trait Lakta-
tion
1 2 3
1 .53 .84 .84
Milchmenge-kg /milk-kg 2 .55 .35 .97
3 .52 .54 .34
1 .52 .88 .87
Fettmenge-kg/fat-kg 2 .54 .36 .97
3 .50 .53 .36
1 .51 .86 .84
Eiweimenge-kg/protein-kg 2 .62 .38 .96
3 .57 .64 .38
Figure 1:Genetic parameters on daily base shown on the example of milk kg (heritability values left;selected genetic correlations at the right side)
Milk kg: Heritability values on daily base
0,05
0,10
0,15
0,20
0,25
0,30
0,35
0,40
0,45
0,50
5 30 55 80 105 130 155 180 205 230 255 280 305
Laktationstag
Heritabilitt(Tagesbasis)
1. La
2. La
3. La
Milk kg: Genetic correlations between the sameday of lactation in laktation 1, 2 and 3
0,50
0,55
0,60
0,65
0,70
0,75
0,80
0,85
0,90
0,95
1,00
5 30 55 80 105 130 155 180 205 230 255 280 305
Laktationstag
gen.
Korrelation
La. 2 zu 3
La. 1 zu 2
La. 1 zu 3
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Detailed information can be found in
Liu, Z., Reinhardt, F. und Reents, R. 2000a: Estimating parameters of a random regression testday model for first three lactation milk production traits using the covariance function approach.INTERBULL Bulletin No. 25: 74-80
Liu, Z., Reinhardt, F. und Reents, R. 2000b: Parameter estimates of a random regression test daymodel for first three lactations somatic cell scores. INTERBULL Bulletin No. 26: 61-65
Liu, Z., Reinhardt, F. und Reents, R. 2001a: The effective daughter contribution concept
applied to multiple trait models for approximating reliability of estimated breeding values.
INTERBULL Bulletin No. 27: 41-46
Liu, Z., Reinhardt, F., Bnger, A., Dopp, L. und Reents, R. 2001b: Application of a random regres-sion model to genetic evaluations of test day yields and somatic cell scores in dairy cattle. INTER-BULL Bulletin No. 27: 159-166
Definition of estimated breeding valuesThe breeding value on lactation base is the sum of the EBVs from day 1-305. The published breedingvalues for milk, fat and protein yield are defined as the average breeding value of lactation one tothree, and represent the desired breeding goal of high lifetime production.
The BV base 2000 recommended by INTERBULL is used to adjust the level of breeding values withinbreed. That means the average breeding value of all cows of the same breed born in 2000 is set to
zero, and the breeding values of all animals are expressed in relation to their base (base differencessee appendix)
All relative breeding values (RZM, RZS, RZE, RZZ, RZN, RZG) are standardised to a yearly rollingbase with a mean of 100 and a genetic standard deviation of 12 points. The base usually shifts in Mayand comprises the currently progeny tested bulls of a breed (at present the test bulls born in 1997-1999).
Breeding values for fat and protein contentBreeding values for fat and protein contents are calculated on the base of total breeding values for theyield traits and phenotypic means (F%*, P%*, Mkg*) of cows in second lactation included in the base.
*kgmilk-
*kgmilk-kgfat-
%fat+BV
%*BV-100*BV=BV Mkg
F
protein%
protein-kg milk-kg*
milk-kg*BV =
BV * 100 - BV * %
BV +
P
Mkg
*) Phenotypic means for breeds:
German B&W Holstein Mkg 8288 F% 4,10 P% 3,41German R&W Holstein Mkg 7221 F% 4,24 P% 3,39R&W dual purpose Mkg 6490 F% 4,27 P% 3,48German Red Cattle Mkg 7017 F% 4,77 P% 3,66Jersey Mkg 5244 F% 5,74 P% 4,08
Relative breeding value milk production (RZM)The RZM is a selection index combining estimated breeding values for production traits. Theproduction traits are combined with a breed specific weight.
For Holsteins and R&W dual purpose RZM includes fat kg and protein kg in the ratio of 1:4. The RZMfor this breeds includes the protein percentage as well.
The RZM for Jersey Red Cattle (Rotvieh/Angler) weights fat kg and protein kg with a ratio of 1:6.
The RZM for Red Cattle (Rotvieh/Angler) includes only protein kg.
The RZM formulas for May 2006 until February 2007 for the different breeds are: RZM-SBT = 89.3 + 0.140*ZWF-kg+ 0.561*ZWP-kg+ 5.047*ZWP-%
RZM-RBT = 89.6 + 0.140*ZWF-kg+ 0.561*ZWP-kg+ 5.047*ZWP-%
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RZM-DN = 97.5 + 0.140*ZWF-kg+ 0.561*ZWP-kg+ 5.047*ZWP-%
RZM-Jersey = 92.4+ 0.104*ZWF-kg+ 0.622*ZWP-kg
RZM-Angler = 95.7 + 0.700*ZWP-kg
The RZM is standardised within breed to a yearly rolling base with a mean of 100 and a geneticstandard deviation of 12 points (currently test bulls born in 1997-1999).
EBVs for Somatic Cell ScoresGenetic evaluation for somatic cell scores was established at VIT already in 1996 using the FixedRegression Model. Since May 2003, the genetic evaluation model has also changed to the RandomRegression Model.
Logarithmic transformation
Original data from milk recording are cells/ml milk and must be transformed to get a standard normaldistribution:
SCS = log2 (Zellzahl / 100000) + 3
Data
The table shows the amount of SCS data processed in the actual run with the Random RegressionModel.
Table 2: Description of the data set used for evaluation of somatic cell scores
April 20081. Laktation1
stlactation
2. Laktation2
ndlactation
3. Laktation3
rdlactation
Gesamttotal
Anzahl ProbemelkenNumber of test day records
119.678.836 85.728.016 57.629.955 263.036.807
Anzahl HerdenkontrolltageNumber of herd testdays
9.827.467 9.585.731 19.413.198
Khe mit BeobachtungCows with records 14.682.009BullenSires
286.898
Tiere gesamtAnimals in total
19.833.413
The model for Somatic Cell ScoresThe Random Regression Model applied for genetic evaluation of SCC is the same as for productiontraits, except calving interval is not included in the fixed lactation curves because no effect was foundon somatic cell scores.
The genetic parameters used in the Random Regression Model are estimated on the base of arepresentative data set of the German Holstein population (Liu et al., 2000a,b). The table gives derivedparameters on 305-day lactation basis. These cumulated parameters are higher than the originalparameters on daily base (see figure 1).
Table 3: Genetic parameters for somatic cell scores on 305-day base with heritability on diago-nal, genetic correlations above diagonal and phenotypic correlations below diagonal
Laktationlactation
1 2 3
1 .16 .95 .89
2 .34 .16 .97
3 .28 .42 .17
Expression of proofs for Somatic Cell Scores
The model provides separate EBVs for SCS in the first three lactations. These three EBVs arecombined into an overall EBV for SCS by index weights of .26, .37, .37 for EBV for somatic cell scores
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in lactations 1, 2, and 3, respectively.
SCS proofs are expressed as relative EBV Somatic Cell Score, called RZS. The scale of the relativebreeding value RZS is reversed to indicate undesirable proofs with values below 100. It isstandardised to a mean of 100 and a genetic standard deviation of 12 points (at present the test bullsborn 1997 to 1999).
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Estimation of breeding values for conformation traits
Starting in June 1993 linear type traits are routinely evaluated using a Best Linear Unbiased Prediction(BLUP) animal model. The estimation is carried out for German Holstein and German Red Holsteintogether in one run and separately for German Red Cattle.
Data baseThe traits considered are 17 linear type traits between the biological extremes on a scale from 1 to 9.Additionally, the four general characteristics angularity, body, feet & legs and udder are classified witha score of 65 to 88. The heritabilities are shown in table 6.
The evaluation uses classifications of cows in first lactation since 1984.
Table 4: Description of the data set used in the current evaluation
April 2008Schwarzbunt / Rotbunt
Holstein / Red Holstein
Rotvieh/Angler
Red Breed/Angler
Anzahl Tiere, insgesamt
Animals total3.058.752
davon beurteilte Tiere (Khe)
Animals classified1.493.294 / 223.082 21.351
Bullen mit beurteilten Tchtern
Bulls with classified daughters20.964 / 4.274 452
The statistical model for conformation traitsFor genetic evaluation multi trait animal models within the three composites angularity/body, feet andudder are used. The model includes classifier*year, herd*year or region*herd level*year, age at firstcalving, and stage of lactation fixed effects and a random additive genetic effect. Classifiers differ notonly in their average scores but also in the respective standard deviations. Heterogeneous variancesare pre-standardised within classifier and year.
The statistical model for the genetic evaluation is
Yijklmn= Class*Yeari+ Herd*Year*HF%j+ Agek+ Stage_of_lact.l+ am+ eijklmn
Yijklmn = observed score
Class*Yeari = classifier * year
Herd*Year*HF%j = herd * year for large herds, otherwise region * herd level * year
(HF% account for herd*German Holstein interaction)
Agek = age at first calving
Stage_of_lact.l = stage of lactation
am = random additive genetic effect
eijklmn = random error effect
All known relationships are considered in the evaluation.
Reliability
As shown in table 6, the linear type traits differ substantially in heritability. Therefore reliability differs
between traits within bulls.
Definition of breeding values
The breeding values for linear figures are expressed only as relative breeding values with an average
of 100 and a standard deviation of 12. For Holstein and Red Holstein base is defined according to the
relative breeding values for other traits (at present test bulls born in 1997-1999). The breeds with small
population, Red Cattle-Angler and R&W dual purpose, have a different base definition (all bulls with
EBVs based on classified daughters).
Linear composites and total composites
The breeding values for the single linear traits are combined to linear composites for angularity, body,
feet and udder. For the relative weights of the linear traits within the composites see table 6.
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Table 6: Used heritabilities of type traits and relative weight in the indices
Linearmerkmal
/ Trait
Abkrzung
Abbreviati-on
Extremwerte
/Extremes
h2 Gew. im Index
Weight in in-dex
Milchcharakter/ Dairy character
Milchcharakter/ Dairy character MCh/ DC derb scharf/edel 0,24 1,00
Krper/ Body
Gre/ Stature Gr/ Sta klein gro 0,41 0,20
Krpertiefe/ Body depth KTi / BD wenig viel 0,24 0,25
Strke/ Chest width St/ CW schwach stark 0,18 0,15
Beckenneigung/ Rump angle BNe / RA ansteigend abfallend 0,26 0,20
Beckenbreite/ Rump wide BBr / RW schmal breit 0,28 0,20
Body Condition Score / BCS BCS / BCS mager fett 0,25 -
Fundament/ Feet
Hinterbeinwinkelung
/ Rear leg set side view
HWi
/ RLs
steil gewinkelt0,15 0,20
Klauen/ Foot angle Kla/ FA flach hoch 0,12 0,20
Sprunggelenk/ Hock quality Spr / HQ derb trocken 0,15 0,20
Hinterbeinstellung
/ Rear leg set rear view
HSt
/ RLr
hackeneng parallel0,15 0,20
Bewegung / Locomotion Bew / Loc lahm gut 0,07 0,20
Euter/ Udder
Hintereuter/ Rear udder height HEu / RUH tief/schmal hoch/breit 0,22 0,20
Zentralband/ Central ligament ZBa/ CL schwach stark 0,13 0,10
Strichplatzierung vorne
/ Teat placement front
SPv
/ TPf
auen innen0,22 0,10
Strichplatzierung hinten
/ Teat placement rear
SPh
/ TPr
auen innen0,28 0,10
Vordereuteraufhngung
/ Fore udder attachment
VEu / FUA lose fest0,21 0,20
Eutertiefe/ Udder depth ETi/ UD tief hoch 0,26 0,20
Strichlnge/ Teat lenght SL/ TL kurz lang 0,25 0,10
Einstufungsnoten / Scores
Milchtyp/ Dairy type Mty / DT 0,28
Krper / Body Krp / Body 0,28
Fundament / Feet and legs Fund / F&L 0,17
Euter / Udder Eut / Udder 0,22
In the index 13 linear traits are taken into account as linear maximum traits (as higher EBVs as better).The EBVs for 4 linear traits (Rump Angle, Rear Legs Side View, Teat Placement Rear, Teat Length)are taken into account with an intermediate optimum. For Rump Angle, Teat Placement Rear and TeatLength the optimum is the average (EBV 100) and figures below and above result in the same lowervalues for the composite. For Rear Legs Side View the optimum is not the average but slightly straightlegs as can be shown with the correlation to longevity. In addition more straight legs dont cause prob-lems (within a wide range) but curved legs result in more and earlier culling. The regression betweencurved legs and longevity is not linear but squared. According to this Rear Legs Side View are takeninto account in the composite index Feet&Legs.
Figure: Weighting of stature, depth, strength, rump angle, rear legs side and teat placement frontwithin the corresponding composite index
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-80
-40
0
40
64 70 76 82 88 94 100 106 112 118 124 130 136
Relative breeding value linear trait
Effecton
lineari
ndex
linear
Sta/BD/Str
RA/TPf/TL
RLS
These linear composites and the breeding values for the general characteristics angularity, body,
feet&legs and udder are combined to the total composites.
Table 7: Combining indices for linear traits and scores to composite traits
Index+ ZW Note/
+ EBV score
= verffentlichter Zuchtwert /
= published EBV
Milchtyp/Dairy type
50% Milchtyp 50% Milchtyp
Krper /
Body75% Krper 25% Krper
Fundament /
Feet and legs50% Fundament 50% Fundament
Euter /
Udder75% Euter 25% Euter
All indices are standardised to an average of 100 and a standard deviation of 12.
EBV total conformation (RZE)
The 4 total composites are combined to a relative breeding value for total conformation called RZE
Table 8: Relative weights for combined RZE
Gewicht im RZE /
Weight in RZE (total con-formation)
Abkrzung/
abbreviation
SBT/RBT /
Holstein
DN /
R&W dual purp.
Angler /
Red Breed
Milchtyp/ Dairy type Mtyp 0,10 20* -
Krper / Body Krp. 0,20 20 0,20
Fundament / Feet and legs Fund. 0,30 30 0,40
Euter / Udder Euter 0,40 30 0,40
As all relative breeding values also the RZE is standardised to a mean of 100 and a standard deviation
of 12 (base: A.I. bulls born 1997-1999) within breed.
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EBVs for conformation traits are published for German bulls if min. 20 daughters within 10 herds are
included in the evaluation. EBVs for foreign bulls with German daughters are published and replace the
INTERBULL EBVs if reliability is 85%.
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Milking Speed and Temperament
VIT introduced a genetic evaluation for milking speed and temperament during milking in August 2004for Holstein, Red Holstein, Red&White dual purpose and Red Breed/Angler. Since February 2005 theresults for bulls are published.
Data
Data are all information on milking speed from measuring and subjective classification by the owner.Temperament is based purely on subjective classification. The following data are used in the geneticevaluation:
- linear classification for milkabily (milk flow) and temperament during milking by the owner re-corded during linear description for conformation traits (scale 1 5)
- linear description for teat placement rear and front teat length as predicting traits- measured milk flow (average in kg/min), DMG.
Only data from 1stlactation since 1990 are included.
Since data recording for milking speed and temperament showed a wide range for amount and formacross regions, the database differs a lot between bulls. In the western regions mainly owners classifi-cation can be found, sometimes added by measures. In the eastern regions with the big herds own-ers/milkers scoring is difficult and mainly measures of milk flow are found. In Bavaria and Schleswig-Holstein official milk recording is carried out with Lactocorders giving measures for milk flow fromevery test. These are included as repeated information. The table shows the amount of data in themodel.
Table: Data base for genetic evaluation of milking speed and temperament during milking
April 2008SBT, RBT, DN und AnglerHol, Red Hol, R&W, Angler
Leistungsrecords gesamtdata records total
3.501.122
DMG-Messungenmeasures miking speed 2.907.345
- davon Lactocordermessungen- from that with Lactocorder
2.470.514
Tiere MBK/MVH-Befragunganimals with scores
649.071
Tiere mit Eigenleistunganimals with data
1.257.071
Tiere im Modell gesamtanimals total in model
2.229.849
Model
The applied method is a Multiple Trait-BLUP-Animal Model. For the trait Measured milk flow, DMGrepeated measures are included as well. The genetic parameters are shown in the table.
Table: Genetic parameters (Heritability on diagonal, genetic correlations off-diagonal)
Melkbarkeitmiking speed
Melkverhaltentemperament
Hilfsmerkmalepredicting traits
DMGmeasures
MBKscores
MVHscores
SPvteat placem.
Slteat length
DMG 0,28* 0,79 -0,03 0,10 -0,19
MBK 0,10 0,00 0,10 -0,23
MVH 0,07 0,05 -0,09
SPv 0,25 -0,26
SL 0,29
*) repeatability for measures within 1stLa. = 0,47
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The statistical models are:
for measured milk flow, DMG:
Yijklmn= B * T * Mi+ LTj+ EKAk+ al+ apm+ eijklmn
Yijklmn observationB*T*Mi herd*day*milking frequency (fix)LTj days in milk at measure (fix)
EKAk age at first calving (fix)al breeding value (random)apm permanent effect of animaleijklmn error (random)
for scores milking speed, temperament, front teat placement and front teat length
Yijklmn = B * Ti+ LTj+ EKAk+ Be * Jl+ am+ eijklmn
Yijklmn observationB*Ti herd*day (fix)LTj days in milk (fix)EKAk age at first calving (fix)Be*Jl classifier*year (fix)am breeding value (random)eijklmn error (random)
The Relative Breeding Values Milking speed (RZD) and Temperament (MVH)
The breeding values for measured milking speed and owner scored milking speed are combined to atotal relative breeding value milking speed, RZD. Within this relative breeding value milking speed,RZD, the EBV measured milking speed and EBV scored milking speed each get a weight of 50%. Therelative breeding value Temperament, MVH, includes only the EBV for scored temperament duringmilking.
The base for the two relative breeding values RZD (milking speed) and MVH (temperament) is definedaccording to all other relative breeding values, i.e. all A.I. bulls from the most recent three years withcompleted test (actually A.I. bulls born 1997-1999). The average within the base is 100 and the geneticstandard deviation is 12.
Holstein, Red Holstein and Red&White Dual Purpose are expressed on the same base. The RedBreed/Angler has its own base.
Reliability and Publication
The reliability is calculated with the Effective-Daughter-Contribution Method. The published reliabilityfor the combined relative breeding value milking speed, RZD, is the highest of the two included traits.
Published are the relative breeding values RZD (milking speed) and MVH (temperament) for bulls withat least
RZD: 10 daughters with milking speed measures in 5 herds,or 20 daughters with milking speed scores in 10 herds
MVH: 20 daughters with temperament scores in 10 herds.
The genetic evaluation is carried out two times a year in February and August together with the
evaluation for the other traits. Results are published via the bull data base in the VIT homepage
(www.vit.de) and are included as well in the BULLI-CD with all breeding values for published A.I. bulls.
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Genetic evaluation for functional herd life (fHL)
Functional herd life (fHL) is considered to be a characteristic describing the health and constitution ofa cow and is evaluated at VIT since 1996.
DataThe data consists of records of the productive life of all cows with a first calving on or after 1
stJanuary
1980 and with A.I. sire and A.I. maternal grand sire. Cows from West-Germany were considered forevaluation when alive on or after 1stJanuary 1985, cows from East-Germany only when alive on orafter 1
stJanuary 1991. Data of heifers, that calved less than 365 days before data collection, is not
included in the evaluation. Breeding values for Black-and-White and Red-and-White bulls are esti-mated in one combined run.
Cows sold for dairy purposes are treated as censored observations. The programs recognizes cowschanging herds if the information can be derived from the data. The observed length of productive lifefor these cows is the actual herd life in all herds.
Trait definitionDifference has to be made between voluntary culling and culling related to health (involuntary). Forbreeding purposes herd life corrected for voluntary culling is more informative, because it is then amore precise indicator of the genetic vitality, health, robustness and fertility. Voluntary culling is mainlyrelated to the relative level of production within herd (high yielding cows get more chances e.g. treat-ments, re-inseminations etc.). Therefore the productive life is corrected for the yield deviation withinherd (protein + fat kg) to achieve an unbiased trait for the genetic ability of a cow to resist involuntaryculling, called functional herd life.
A problem for selection for longevity and breeding value estimation for fHL is that for cows still alive thedefinitive life span is unknown. Animals currently interesting for breeding would be excluded from theevaluation by waiting until culling has occurred. Thus generation interval would be extremely long andgenetic improvement would practically be impossible. Therefore cows still alive are included in theevaluation as censored observations.
Method
Survival analysis offers the possibility, to consider the longevity of animals alive up to a certain date(date of estimation of breeding values) statistically as a censored observation. Thus animals alive areinformative as well as culled animals, but are given less weight in the evaluation because their informa-tion is not yet complete. The Weibull regression model is a well-known method of survival analysis andcan therefore be used for estimation of breeding values for fHL. Ducrocq of INRA in France and Slk-ner of the University of Vienna developed in co-operation a set of programs for routine breedingevaluation of fHL, which also was made available to the German computing centres.
The distribution of the observed random variable fHL is described through the hazard function
h(tj,l,s,z)j= h0(tj,l,s) * e(x'(t)b+zu)
with
h(t,z)i as relative risk of culling at time (t) for animal (j) under occurrence of the factorsconsidered in the vectors x(t) and z
h0(tj,l,s) as base hazard function in year (j) for a cow in lactation (l)and lactation stage (s)
b as solution vector for all environmental effects considered in x(t)
u as solution vector for all genetic effects
The common average risk of culling for all animals in year (j), lactation (l) and lactation stage (s) at
time (t),h0(tj,l,s)is multiplied for every animal with an individual multiplication factor e(x(t)b+zu)
, which isdefined by all additional environmental and genetic effects. Changes over time in the environmental
effects can be taken into account in vector x(t). Estimation of the solutions for h0(tj,l,s),(b) and (u) oc-curs through maximizing a probability-function. The solutions reflect the relative risk of culling in alleffect-classes.
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Statistical ModelThe evaluation in VIT is based on a model, in which a combined effect of a bull is estimated as sireand maternal grand-sire. Relationships among bulls are taken into account through their sires andmaternal grand-sires. The assumed heritability (h
2) of fHL is 0.10.
The following information is taken into account through the base hazard function and in theargument of the e - function of (x(t)b+zu) as effects on fHL.
Parameter for shape of base hazard function'
- year * lactation * lactation stage
Random time-dependent effect through the base hazard function
herd * year
Fixed time-independent effect as class variable in (x(t)b)
age of first calving
Fixed time-dependent effects as class variables in (x(t)b)
parity * stage-of-lactation
relative milk yield within herd * region * year(the selection pressure within herd is taken into account when estimating fHL. The relative de-
viation for fat and protein yield (with weights of 1:4) of the cow from the herd average adjustedfor parity is defined as effect. Because selection pressure may be different between regionsand years and within years, the interaction of relative milk yield with region*year-season istaken into account)
relative change of herd size within year(the change of herd size relative to the herd size at 1
stJanuary is defined as effect in classes of
10 %)
Random genetic effect as class variable in (zu)
the combined genetic effect of a bull as sire and maternal grand-sire
Heritability for functional herd life is 0.16.
The solutions from this estimation system relate exclusively to the direct fHL (based on culling/survivalinformation). These solutions are not published, but are summarised with information from auxiliarytraits to combined proofs for fHL.
Combined breeding value for functional Herd LifeThe solutions from the direct evaluation of length of productive life are combined with evaluations ofauxiliary traits through selection index to increase the accuracy of the estimated breeding value. Traitdefinition and scale are not affected by this combination.
Genetic correlations and the reliability of the information (estimated breeding values) are consideredfor selection index. Currently, estimated breeding values for somatic cell score, body depth, feet & legsscore, fore udder attachment and maternal calving ease are considered as auxiliary traits.
Table 9: Used correlations for information traits on direct longevity and among each other(Black Holstein above, Red Holstein below diagonal)
ND Fund. KTi ETi RZS mTGNutzungsdauer direkt(ND) /funct. herdlife direct
- 0,26 -0,27 0,30 0,39 0,16
Fundamentnote (Fund.) /feet&leg score
- -0,06 0,17 0,02 0,09
Krpertiefe (Kti) /body depth
- -0,32 -0,13 -0,08
Eutertiefe (ETi) /udder depth
- 0,29 -0,01
RZS /
Udder health (SCS*-1)- 0,04
Rel. ZW mat. Totgeburten (mTg)maternal still birth rate *-1
-
*reversed scale against SCS (higher values RZS = lower SCS)
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The following figure shows schematically, how the importance of the auxiliary traits in the combinedRZN decreases with increasing reliability until in the end culling/survival information is determining RZNexclusively at maximum reliability. The estimated breeding value for somatic cell score clearly is mostimportant, because it has a relatively close relation to fHL and is estimated accurately already early.
Figure 3: Importance of source of information in combined RZN dependent on reliability
0
1 0 0
5 0 % 9 9 % re l
P I - R Z N d i r
R Z N d i r
T y p e
S C S
m a t . C a lv .
E a s e
Correlations and the trait combination are checked regularly and changed if necessary.
Breeding value definition and relative breeding value functional herd lifeBreeding values of bulls are published in lists and direct data access as relative breeding value fHL(RZN). For interpretation purposes approximated fHL in days is published as well. For the approximatederivation of the survival curves and the breeding values in days-LPL, the average culling rate in thefirst lactation for all cows was assumed to be 20 %.
Table 10: Average herd life (years/days) with different RZN (culling rate in 1. lactation: 20%)
RZNZW-Ausfallrisko
Relativskala
ZW-NutzungsdauerEBV herd life
Jahre/years (Tage/days)
Zeitpunkt 50% T. gemerzttime until 50% are culled
Jahre/years (Tage/days)
88 1,221 - 0,49 ( - 179 ) 2,83 ( 1033 )
100 1,000 0,00 ( 0 ) 3,08 ( 1124 )
112 0,819 +0,53 ( +193 ) 3,48 ( 1273 )
The table shows that the EBVs for culling risk and for the approximate days fHL are not linear relatedto the relative breeding value RZN.
The base for the relative breeding values consists of the A.I. bulls born from 1997 to 1999 with a mini-mum reliability of the breeding value of 50%. Relative breeding values of bulls in the base are stan-dardized to a mean of 100 and a genetic standard deviation (of the true breeding values) of 12. Reli-abilities are calculated as the approximate percentage of determination (rgi
2) between real breeding
values and estimated breeding values.
Breeding values for fHL are calculated with every German routine run. The data base for the mostrecent run is given in the following table.
Table 11: Data base for evaluation of functional herdlife
April 2008Tiere gesamt /animals total
Bullen gesamt /bulls total
Bullen verffentlicht /Bulls published
Funkt. Nutzungsdauerfunctional herdlife
7.059.705 42.931 25.270
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Non-Returnrate Khe (NRc)Non-Return-Rate cows (NRc)
7.713.804 11.585.269
Verzgerungszeit Khe (VZc)First to successful insemination (FLc)
5.746.217 8.347.585
Rastzeit Khe (RZc)Calving to first insemination (CFc)
7.824.917 11.762.236
MethodThe new model developed by VIT is a BLUP-Multi trait-Animal-Model with repeated observations. Thebreeding values for daughter fertility are calculated with correction for the following fixed non-geneticeffects:
- Herd*year- Month of insemination- Age at insemination- Parity*age at insemination- Status of insemination bull
(young sire/proven sire)*AI-stud of bull*insemination season- Effect of insemination bull
The used genetic parameters (evaluated on German data) are shown in the table.
Tabelle: Genetische Parameter in der Zuchtwertschtzung Tchterfruchtbarkeit (Korrelationenim zchterischen Sinne; z.B. NRk/VZk +0,39 = eine hhere Non-Returnrate Khe istmit krzerer Verzgerungszeit bei Khen verbunden)Used parameters in evaluation for daughter fertility
h2(Diagonale) u. Korrelationen
h2(diagonal) and correlations
RZkCFc
NRrNRh
NRkNRc
VZrFLh
VZkFLc
gen. Streu.genetic s
Rastzeit (RZc)Calving to first insemination (CFc)
3,9% 0,02 -0,05 0,14 0,37 6,9 Tg.
Non-Return-Rate Rinder (NRr)Non-Return-Rate heifers (NRh)
1,2% 0,63 0,53 0,15 4,8 %
Non-Return-Rate Khe (NRk)Non-Return-Rate cows (NRc)
1,5% 0,25 0,39 6,0 %
Verzgerungszeit Rinder (VZr)First to successful insemination (FLh)
1,4% 0,48 7,4 Tg.
Verzgerungszeit Khe (VZk)First to successful insemination (FLc)
1,0% 4,9 Tg.
The daughter fertility index RZR and the conception indexWithin the summarizing daughter fertility index RZR (R=Reproduction) the four conception traits themselves summarized in the conception index CON get a relative weight of 75%. The ability torecycle after calving represented by the trait Time Calving to 1
st Insemination gets 25% weight.
Both complexes cause about half of the genetic variation for calving interval, but the costs for a pro-
longed calving interval by bad conception are higher. Beside the lower milk yield longer calving intervalfrom bad conception causes extra costs for the (re-)insemination. The composition of the daughterfertility index RZR is shown in the figure.
Figure: Relative weights within the fertility index RZR (R=reproduction)
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Re-
Cycle Time Calving to
1st Ins. (CF)25%
Heifer
Cow
Heifer
Cow
Cow
Relativ-EBV
Reproduction
RZR
Conception
NRR 56 (NR)
12,5 %
Relativ-EBV
Conception
(CON)
75 %
25 %
Days Open (DO)
12,5 %
25 %
Definition of relative breeding values and publicationAll breeding values are published as relative breeding values with an average of 100 in the base (cur-rently A.I. bulls born 1998-2000) and a genetic standard deviation (true breeding values) of 12 in thebase. Because relative breeding values above 100 are defined as positive compared to the breeding
goal, the time values have to be reversed in scale (e.g. relative breeding values above 100 for time ofcalving to fist insemination mean less days). The breeding value for each of the five original traits ispublished if the reliability is minimum 30% and the EBV is based on at least 10 daughters in 10 herds.The daughter fertility index RZR and the relative EBV CON are published if at least one cow concep-tion trait (NR cows) is published.
Interbull conversion for daughter fertility traits
Interbull converts the following daughter fertility traits- Heifer conception (Heifers ability to conceive, confirmed conception)Non-Return-Rate cows
(Cows ability to conceive, % trait )- Cows conception (Cows ability to conceive, interval trait)- Time from calving to first insemination (Cows ability to recycle)- Days open/calving interval (Cows calving to conception).
VIT provides all the single traits according to the definition (Days Open as sum of Time Calving to 1stInsemination plus First to Successful Insemination).
Because many other countries have only one national fertility trait or at least not all traits converted byInterbull many international bulls have not all EBVs for daughter fertility on German base. If EBVs forsome traits in the daughter fertility index RZR are missing the index is calculated using the pedigreeindex for that trait. The reliability of indices calculated with pedigree indices is therefore lower.
Calving traits
Calving easeThe difficulty of calving is recorded in five classes for all cows under milk recording in all parities. Theproportions of the calving ease classes are transformed to class means on the standard normal distri-bution for every region*year*month.
Stillbirth rateStillbirth is defined as "All-or-None" trait. A calving where the calf was born dead or died within 48hours is considered as stillbirth.
Data
Calving data of all cows/heifers under milk recording for German Holstein, Red Holstein, RedBreed/Angler and Jersey cows are included. Data from 1990 onwards was considered for estimation ofbreeding values (amount of data see table 13). The actual time span of the data is regionally differentaccording to the availability of the data.
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Statistical Method and modelsEstimation is carried out by a BLUP animal model developed at the Bavarian State Institute for AnimalProduction (BLT) for calving traits was adapted by VIT for the breeds included in the model. Direct andmaternal genetic effects on the traits are considered in the models. The direct or paternal effect forcalving ease and still birth is the effect of the calf itself (form, size) and the maternal effect is the effectof the cow (form and size of rump). Subsequent calvings of a cow are taken into account by includinga permanent environmental effect.
Factors considered in the models for calving difficulties and stillbirth are:- Fixed environmental effects
herd-year
calving month
age-of-calving * parity
sex of calf
- Random permanent environmental effects of the cow
permanent environmental effect of the cow (e.g. consequences of sub-optimal rearing)
- Random genetic effects
direct genetic effect of the calf (size, shape)
maternal genetic effect of the dam (bearing qualities)
The genetic parameters used in the evaluation for calving ease, stillbirth and NRR 90 are presented inthe following table.
Table 9: Used parameters for reproduction traits
Merkmal /
trait
h2
pat. u. mat. Effekt
Wiederholbarkeit( w )
gen. Korr. pat./mat.( rg (pat/mat))
Kalbeverlauf /
calving ease0,05 0,15 -0,10
Totgeburtenrate /
still birth rate0,05 0,15 -0,10
Relative breeding valuesThe breeding values on the original scale are based on the cows born in 2000 (mean is 0). The basefor the relative breeding values is defined as for the other traits (currently A.I. bulls born from 1998 to2000). Relative breeding values of basis bulls are standardized to a mean of 100 and a genetic stan-dard deviation (of the true breeding values) of 12. For calving difficulties and stillbirth, the breedingvalues have to be inverted to obtain desirable breeding values above 100.
Reliabilities are calculated as the approximate percentage of determination (r(gi)) between real breed-ing values and estimated breeding values. Reliabilities are calculated for direct and maternal effectsseparately. Reliabilities for the two calving traits are equal, because the data for the two evaluations arebased on the same calving data, and the same genetic parameters are assumed.
Breeding values for reproduction traits are estimated once a year with the August run. The data baseof the most recent evaluation run is given in the table.
Table 13: Data base for evaluation of reproduction traits (1x per year in August)
August 2008 Bullen / bulls
Merkmal /Trait
Beobachtungen /observations
Tiere /animals
Geschtzt/evaluated
Verffentlicht/publishedpaternal
Verffentlicht/publishedmaternal
KV, TG /CE, SB 29.448.835 38.549.539 191.862 22.306 26.412
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The total merit index (RZG)
To achieve the maximum overall genetic gain in dairy cattle breeding, a Total Merit Index is applied toimprove all traits according to their relative importance in the breeding goal. This Total Merit Index iscalled RZG (Relativ Zuchtwert Gesamt) and is applied to Holstein, Red Holstein, Red and White dualpurpose and Red Cattle-Angler. Relative weights for included traits were revised in August 2002 and
are different for Red Cattle-Angler and the other breeds (see table).
Calculation of total merit index (RZG)
The derivation of the Total Merit Index (RZG) is based on selection index theory. This is providing the
optimum overall selection response in all traits. The relative breeding values (composites) are
considered as information traits. Included traits, relative weights and genetic parameters are given in
the table.
Within the index program using this parameters and the reliability of the EBVs, for each bull RZG is
calculated with an individual formula. All official EBVs (reliability 50%) are included and RZN when
based on at least daughter information for the auxiliary traits (RZS, conformation).
Table 15: Parameters and relative weights of traits in RZG
Merkmalskomplexcomposite
Gen. KorrelationenRZM RZN RZE* RZS RZR
SBT/RBT /Holstein
DN /R&W dual p.
Angler /Red Breed
MilchleistungYield
RZM 45 % 45 % 40 %
NutzungsdauerFuncti. herd life
RZN -0,10 20 % 20 % 20 %
Exterieurconformation
RZE 0,15 0,30 15 % 15 % 20 %
ZellzahlSomatic cells
RZS -0,10 0,40** 0,20 7 % 7 % 10 %
FruchtbarkeitFertility
RZR -0,30 0,40 0,05 0,15 10 % 10 % 10 %
Kalbemerkm.Calving traits
0,00 0,20 0,10 0,10 0,15 3 % 3 % -
*)already taken into account in combined RZN
The RZG is standardised to a mean of 100 (base: A.I. bulls born 1997-1999) and a genetic standard
deviation of 12.
Publication of RZG
The RZG is only published, if a bull has an official index for production (RZM), somatic cell score (RZS)
and conformation traits (RZE). For evaluation runs without new calving and fertility EBVs RZZ is
calculated with the most recent EBVs.
The official ranking for top bulls is by RZG.
Standard deviations of evaluated breeding values for RZG and the included traits are given in the
appendix.
Estimation frequency
In 2001 the German Holstein Association decided to cancel the evaluation in November. So, since2001, breeding values are estimated three times a year (except conformation for Red Cattle/Angler
only May and August). Proofs are published in the beginning of February, May and August according tothe INTERBULL runs. Calving and fertility traits are only estimated in August.
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Publishing of data
Bulls get EBVs, if reliability is 50%. All EBVs for all bulls and cows are available in the herd book data
base. The results for the published A.I. bulls (yield: 75% Rel., 20 daughters with 120 days in milk;
conformation: 20 daughters in 10 herds) are published via internet (www.vit.de) and the CD BULLI(subscription [email protected]).
In the sire data base in www.vit.deand the BULLI CD EBVs for all bulls are published, that
are test bulls born not earlier than 12 years before (year of actual run minus 12 years) all other bulls with 20 new daughters within the last 2 years
and if their EBVs fulfil
Production: 75% reliability (foreign bulls 85%) and 20 daughters with 120 days in milk
Conformation: 20 daughters in 10 herds (foreign bulls 85%).
To be ranked in the official breed top list by RZG the bull must be officially A.I. tested in Germany andhave RZM, RZE and RZS from the national VIT evaluation.
Minimum figures a bull has to fulfil to be ranked ...% are printed in table 21 in the annex.
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Tabellenanhang/ Annex
Table 16: Average EBVs of bulls within year of birth (reliability > 50 %)
a) German Holsteins
April 2008 Anzahl
Bullen
Milch-kg Fett-% Fett-kg Eiwei-% Eiwei-kg RZM
1993 777 37 0,01 1,0 -0,04 -2,4 84,71994 860 119 -0,03 1,5 -0,03 0,9 86,71995 951 219 -0,07 2,1 -0,03 4,5 88,81996 1017 392 -0,08 8,0 -0,03 10,4 92,91997 1059 372 -0,06 9,1 -0,01 11,8 93,91998 932 478 -0,06 13,4 -0,01 15,2 96,41999 890 635 -0,07 19,2 -0,01 20,5 100,22000 853 877 -0,16 20,6 -0,04 26,2 103,52001 826 894 -0,14 23,1 -0,03 27,6 104,72002* 817 857 -0,12 23,7 -0,03 25,8 103,72003* 222 882 -0,15 21,7 -0,07 23,3 101,8
b) German Red Holstein
April 2008 AnzahlBullen
Milch-kg Fett-% Fett-kg Eiwei-% Eiwei-kg RZM
1993 154 -13 0,03 -0,2 -0,02 -2,5 86,11994 167 74 -0,02 0,3 -0,03 -0,4 87,31995 147 35 0,08 5,8 0,01 1,2 89,11996 149 295 0,04 14,6 0,02 11,3 96,11997 164 348 -0,03 11,7 0,01 11,9 96,01998 133 492 0,00 19,9 -0,01 15,4 99,01999 152 520 0,02 22,4 -0,03 15,4 99,3
2000 141 727 -0,09 22,6 -0,05 20,1 101,82001 184 674 -0,01 26,9 0,00 22,3 103,82002* 108 862 0,02 37,4 0,00 28,8 109,02003* 9 968 -0,12 30,2 -0,01 31,8 109,6
c) Red and White Dual Purpose
April 2008 AnzahlBullen
Milch-kg Fett-% Fett-kg Eiwei-% Eiwei-kg RZM
1992 21 -658 0,10 -22,8 0,07 -18,9 84,01993 19 -311 0,08 -8,5 0,07 -6,8 92,9
1994 15 -304 0,21 -0,8 0,13 -2,3 96,81995 12 -158 0,14 0,8 0,06 -2,3 96,71996 13 -103 -0,03 -6,6 0,08 1,5 97,81997 9 -149 0,14 2,4 0,13 2,8 100,11998 14 85 -0,03 1,7 0,10 9,8 103,81999 7 98 0,10 10,7 0,09 8,6 104,32000* 4 -31 0,02 -0,7 0,09 4,4 100,32001* 4 221 0,03 9,7 0,15 17,1 109,2
d) Red Cattle / Angler
April 2008AnzahlBullen
Milch-kg Fett-% Fett-kg Eiwei-% Eiwei-kg RZM
1992 10 -392 0,19 -7,6 0,04 -11,8 87,11993 12 -158 -0,07 -12,8 -0,02 -7,0 90,5
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Table 19: Base differences between breeds for yield traits and somatic cell count (RZS)
Mai 2008Milch-kgmilk kg
Fett-%fat %
Fett-kgfat kg
Eiwei-%protein %
Eiwei-kgprotein kg
RZM RZS
Sbt RbtHolstein Red Hol.
+388 kg -0,05 +12,5 kg -0,02 +11,8 kg 7,2 -1,2
Rbt - Rotv./Ang.Red Hol. Red Breed:
+530 kg -0,36 -2,2 kg -0,15 +8,2 kg * -3,0
Rbt Rbt/DNRed Hol. R&W dualpurp.
+307 kg -0,01 +12,7 kg -0,04 +7,9 kg 13,5 +1,3
*) no average base difference because different traits/weights in RZM
Table 20: Base differences between Holstein and Red Holstein for conformation traits
April 2008Abkrz.
abbrev.
Sbt-Rbt
Hol-Red Hol
Rbt-DN
R. Hol - DP
Rbt-Angler
Red Hol - Ang
Milchcharakter/ Dairy character
Milchcharakter/ Dairy character MCh/ DC 2,9 18,5 13,2
Krper/ Body
Gre/ Stature Gr/ Sta 5,2 29,6 18,7
Krpertiefe/ Body depth KTi / BD 1,0 0,2 8,8
Strke/ Strength St/ Str 2,7 -16,9 6,3
Beckenneigung/ Rump angle BNe / RA 3,0 -28,1 -6,1
Beckenbreite/ Rump wide BBr / RW 2,1 -5,5 7,8
Body Condition Score /BCS BCS /BCS -2,7 -27,1 -6,5
Fundament/ Feet
Hinterbeinwinkel./ Rear leg set side view HWi / LSS -0,8 9,0 -3,3
Klauen/ Foot angle Kla/ Ft 5,8 -4,4 -6,6
Sprunggelenk/ hocks Spr / HQ 2,8 6,2 -8,2
Hinterbeinstellung
/ Rear leg set rear viewHSt / LSR 2,0 -7,2
-2,5
Bewegung /Locomotion Bew /Loc 4,6 -11,6 -13,1
Euter/ Udder
Hintereuter/ Rear udder height HEu / RUH 5,4 23,9 6,2
Zentralband/ Suspensory ligament ZBa/ SL 9,0 16,7 5,0
Strichplatz. vorne / Teat placement front SPv / TPf 5,9 16,2 4,3
Strichplatzierung hinten / Teat placem. rear SPh / TPr 9,4 17,2 4,7
Vordereuteraufhng. / Fore udder attach. VEu / FUA 1,5 14,9 3,9
Eutertiefe/ Udder depth ETi/ DU 2,6 16,7 1,9
Strichlnge/ Teat lenght SL/ TL -0,3 -8,6 3,2
Bewerternoten/ Scores
Milchtyp/ Dairy type Mty / DT 3,3 19,1 16,4
Krper / Body Krp/ Body 4,2 14,9 17,6
Fundament / Feet and legs Fund /Feet 3,4 3,0 -1,9
Euter / Udder Eut /Udder 6,6 20,5 10,1
Exterieur ges./ composite total conformation
RZE 8,5 20,6 7,9
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Table 21: Minimum figures a bull has to have to be ranked %
German Holstein
August 2008% Grenzerank ... %
RZM RZE RZS RZN RZR RZG ZWMkg
ZWF %
ZWFkg
ZWE %
ZWEkg
99 125 126 125 123 124 126 1999 0.67 67 0.26 58
98 122 122 122 120 121 122 1829 0.56 61 0.22 53
97 120 120 121 118 120 120 1723 0.50 57 0.20 50
96 118 118 120 117 118 119 1626 0.45 54 0.18 48
95 117 117 118 116 117 117 1560 0.41 51 0.17 46
90 113 113 115 113 114 113 1322 0.28 42 0.13 39
85 109 110 112 111 111 110 1155 0.22 36 0.09 34
80 106 108 110 109 110 107 1025 0.15 31 0.07 30
75 104 106 108 107 108 105 920 0.10 27 0.05 26
70 102 104 107 106 107 103 833 0.06 24 0.03 24
65 100 102 105 105 105 101 746 0.02 21 0.02 21
60 98 101 104 103 104 99 658 -0.02 18 0.00 18
55 97 100 102 102 103 98 581 -0.06 15 -0.01 16
50 95 98 101 101 102 96 498 -0.09 11 -0.03 14
German Red Holstein
August 2008% Grenzerank ... %
RZM RZE RZS RZN RZR RZG ZWMkg
ZWF %
ZWFkg
ZWE %
ZWEkg
99 128 127 123 119 128 126 1900 0.78 75 0.33 57
98 123 123 121 117 126 124 1601 0.70 67 0.28 51
97 121 121 120 116 125 122 1507 0.65 63 0.25 48
96 120 120 118 115 124 120 1463 0.59 59 0.24 45
95 118 118 117 114 122 119 1398 0.56 57 0.22 43
90 114 113 113 111 119 113 1203 0.43 47 0.16 37
85 110 111 111 109 117 110 1065 0.34 42 0.13 32
80 107 108 110 108 115 108 944 0.27 37 0.10 28
75 105 106 108 106 113 106 834 0.21 32 0.08 25
70 103 105 106 105 112 104 747 0.16 28 0.06 22
65 101 103 105 104 110 103 661 0.12 24 0.05 19
60 99 101 104 103 109 101 572 0.07 21 0.03 16
55 98 99 103 102 108 100 493 0.03 18 0.01 14
50 96 98 101 100 106 99 418 -0.01 15 -0.01 12
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Table 22: Besitzerverzeichnis (Owner address)
Abbreviation: Adress
BG G. BesamungsgenossenschaftGttingenGtzenbreite 1037124 Rosdorf
Greif. Besamungsstation Greifenberg
Hochenwanger 1086926 Greifenberg
Grub Prf- und BesamungsstationMnchen Grub eVSenator Gerauer Strae 1983536 Grub
Hoech. BesamungsvereinigungNordschwaben eV89420 Hoechstaedt / Donau
Lands. BesamungsgenossenschaftNiederbayern eGGut Altenbach84036 Landshut
LTR Landesverband Thringer Rinderzch-ter eGStotternheimer Strae 1999084 Erfurt
MAR Masterrind GmbHOsterkrug 2027283 Verden / Aller
Meg. Meggle MilchindustrieRottmoos83512 Reitmehring
Memm. Rinderbesamungsgenossensch.Memmingen eGBuxheimer Strae 10487700 Memmingen
Neust. Besamungszentrale Neustadt eGKarl-Eibl- Strae 172791413 Neustadt / Aisch
OHG Osnabrcker Herdbuch eGFckinghausen49324 Melle
RBB RinderproduktionBerlin-Brandenburg GmbHMielestrae 214542 Werder
RBG A. Rinderbesamungsgenossen-schaft Albersdorf eGBahnhofstrae 1525767 Albersdorf
RBW RinderunionBaden-Wrttemberg e.V.Erisdorfer Strae 42-4470599 Stuttgart
RMV RinderzuchtMecklenburg-Vorpommern GmbHAm Bullenberg 117348 Woldegk
Rosen. Besamungsstation RosenheimSchnfelderstrae 1283022 Rosenheim
RSA Rinderzuchtverband
Sachsen-Anhalt eGBahnhofstrae 3239576 Stendal
RSH RinderzuchtSchleswig- Holstein eGRendsburger Strae 17824537 Neumnster
RUW Rinder-Union West eGSchiffahrterdamm 23548147 Mnster
VOSt Verein OstfriesischerStammviehzchterOstfriesische Viehverwertung eGViehhof26770 Leer
WEU Weser-Ems Union eGKayhauserfeldFeldlinie 2a26160 Bad Zwischenahn
ZBH Zucht- und BesamungsunionHessen eGAn der Hessenhalle 136304 Alsfeld
Abbildung:Zuchtwerttrend der Besamungsbullen (Schwarzbunt, Rotbunt) fr wichtige MerkmaleTrend of EBVs by birth year for A.I. bulls (Holstein, Red Holstein)
Schwarzbunt (Holstein)
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80,0
85,0
90,0
95,0
100,0
105,0
110,0
92 93 94 95 96 97 98 99 00 01 02 03
RZM SBT
80,0
85,0
90,0
95,0
100,0
105,0
110,0
92 93 94 95 96 97 98 99 00 01 02 03
RZE SBT
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29/44
80,0
85,0
90,0
95,0
100,0
105,0
110,0
92 93 94 95 96 97 98 99 00 01 02 03
RZN SBT
80,0
85,0
90,0
95,0
100,0
105,0
110,0
92 93 94 95 96 97 98 99 00 01 02 03
RZS SBT
-
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30/44
80,0
85,0
90,0
95,0
100,0
105,0
110,0
92 93 94 95 96 97 98 99 00 01 02 03
RZR SBT
80,0
85,0
90,0
95,0
100,0
105,0
110,0
92 93 94 95 96 97 98 99 00 01 02 03
RZG SBT
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31/44
-
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32/44
85,0
90,0
95,0
100,0
105,0
110,0
115,0
92 93 94 95 96 97 98 99 00 01 02 03
RZN RBT
85,0
90,0
95,0
100,0
105,0
110,0
115,0
92 93 94 95 96 97 98 99 00 01 02 03
RZS RBT
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33/44
85,0
90,0
95,0
100,0
105,0
110,0
115,0
92 93 94 95 96 97 98 99 00 01 02 03
RZR RBT
85,0
90,0
95,0
100,0
105,0
110,0
115,0
92 93 94 95 96 97 98 99 00 01 02 03
RZG RBT
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34/44
Figure 5: Description of 18 linear traits
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35/44
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36/44
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37/44
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38/44
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39/44
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40/44
-
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41/44
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42/44
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43/44
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44/44