Status as of: 2019-09-27

Form GE

DESCRIPTION OF NATIONAL GENETIC EVALUATION SYSTEMS

Country (or countries)	DEU & AUT (DEA)	
Main trait group1	Production (milk, fat, protein)	
Breed(s)	BSW	
Trait definition(s) and unit(s) of measurement2
Attach an appendix if needed	•	1st, 2nd ,and 3rd  lactation defined as correlated traits
•	latter (>3) lactations considered as repeated observation of third lactation
•	separate biological traits milk kg, fat kg and protein kg	
Method of measuring and collecting data	 Milk recording data from Germany and Austria	
Time period for data inclusion	from Jan. 1990 onwards	
Age groups (e.g. parities) included	All lactations included; cows required first lactation TDR in data	
Other criteria (data edits) for inclusion of records	DIM between 8 and 350; 1.5<milk kg<80; 1.5<fat/protein %<8.5; calving age limitations by parity; 	
Criteria for extension of records (if applicable)	-	
Sire categories	All bulls with progeny information in DEU and AUT	
Environmental effects3, pre-adjustments 	-	
Method (model) of genetic evaluation3	reduced rank random regressions for additive genetic effect
ST-ML-RR-TD-AM	
Environmental effects3 in the genetic evaluation model	all F: HTD over lactations, days carried calf (3rd order poly.), calving age (2nd order poly.), production Year-Month-Region-Lactation classes, calving Year-Season-Region-Lactation classes (CYSRL), 2nd  order Leg. plus 2 wilmink terms for DIM correction nested within CYSRL*calving_age_classes	
Adjustment for heterogeneous variance in evaluation model	Simultaneously adjustment for heterogeneous variance when solving the BLUP model applying an adaptation of Meuwissen et al. (1996). 
Variance model: fixed production year*month*region*lactation, and random herd*month*lactation for which an 1st order autoregressive process between herd*year*lactation strata is assumed (Lidauer et al. 2008).	
Use of genetic groups and relationships	Phantom parent groups by selection path, year, and country.	
Blending of foreign/Interbull information in evaluation	-	
Genetic parameters in the evaluation	see Appendix GE_PR	
System validation	Interbull trend validation test I, II, III	
Expression of genetic evaluations
If standardised (e.g. RBV), give standardisation formula in the appendix	305-day Breeding value (DIM 8 to 312) within lactation, Combine ebvs from 1st, 2nd and later lactations with equal weighting. 	
Definition of genetic reference base
Next base change	Rolling genetic reference base defined as 8 to 10 year old bulls with minimum of 10 daughters in minimum of 5 herds. E.g. evaluation August 2017: bulls born between August 2006 and Juli 2009	
Calculation of reliability	Apax99 within the MiX99 program package (Vuori et al. 2006)	
Criteria for official publication of evaluations	For publication of conventional ebvs: daughters in min. 10 herds,
Since introduction of genomic evaluation in December 2011 for all traits: For genotyped animals the genomically enhanced breeding values as a combination of conventional ebvs and genomic ebvs are published for genotyped animals.	
Number of evaluations / publications per year	Three evaluations per year: April, August, December	
Use in total merit index4	Yes; total merit index called ‘Gesamtzuchtwert’ (GZW) expressed on relative scale (mean 100, SD 12)	
Anticipated changes in the near future		
Key reference on methodology applied	Emmerling R., Mäntysaari E.A., Lidauer M. (2002). Reduced rank covariance functions for a multi-lactation test-day model. In: Proc. 7th WCGALP, Montpellier, France, CD-ROM, No 17.03.
Lidauer M., Mäntysaari E.A., Emmerling R., Strandén I. (2002). Effect of heterogeneous variance adjustment in an across country evaluation of Brown Swiss. In: Proc. of the 2002 Interbull Meeting, Interlaaken, Switzerland. Interbull Bull., 29, 84–87.
Lidauer M.H., Emmerling R., Mäntysaari E.A. (2008). Multiplicative Random Regression Model for Heterogeneous Variance Adjustment
in Genetic Evaluation for Milk Yield in Simmental. J. Anim. Breed. Genet. 125:147–159.
Vuori K., Strandén I. and Lidauer M.H. (2006). MiX99 – effective solver for large and complex linear mixed models. In: Proc. 8th WCGALP, Belo Horizonte, Brazil, CD-ROM, No 27: 33.	
Key organisation: name, address, phone, fax, e-mail, web site	Bavarian State Research Center for Agriculture (LfL); Institute of Animal Breeding; Prof. Duerrwaechter Platz 1;85586 Poing-Grub; Germany
phone +49-(0)89-99141-101; fax +49-(0)89-99141-199
Dr. Reiner Emmerling; Dr. Jörg Dodenhoff; Dr. Christian Edel
 Reiner.Emmerling@lfl.bayern.de, Joerg.Dodenhoff@lfl.bayern.de, Christian.Edel@lfl.bayern.de  
homepage: www.lfl.bayern.de/itz	
1) Either: Production (e.g. milk, fat, protein), Conformation, Health (e.g. mastitis resistance, milk somatic cell, resistance to diseases other than mastitis), Longevity, Calving (e.g. stillbirth, calving ease), Female fertility (e.g. non-return rate, interval between reproductive events, number of AI’s, heat strength), Workability (e.g. milking speed, temperament), Beef production, Efficiency (e.g. body weight, energy balance, body conditioning score), or Other traits.
2) Indicate frequencies per category if the trait is categorical and specify transformation of data if practiced.
3) Use abbreviations for most common effects (see document with list of abbreviations at http://www-interbull.slu.se/service_documentation/General/list_of_abbreviations.rtf) and indicate random (R) or fixed (F).
4) Please give economic weights and indicate how they are expressed (preferably in genetic standard deviation units).

 
Form GE	Appendix PR

Parameters for national genetic evaluations for production traits as provided to Interbull

Country (or countries):	DEU & AUT (DEA)	
Main trait group:	Production	
Breed(s):	BSW	

Trait	h2a	genetic
variancea	official proof
standardisation formulab	
Milk yield: 
first to third lact.
first lact.
second lact.
third+latter lact.	
0.46
0.39
0.34
0.33	
295089 kg2
239180 kg2
329683 kg2
351068 kg2	StandEval: eval-a
 (1/3*1st lact.+1/3*2nd lact.+1/3*3rd+later lact.) 	
Fat yield:
first to third lact.
first lact.
second lact.
third+latter lact.	
0.41
0.35
0.32
0.27	
449 kg2
354 kg2
538 kg2
512 kg2	StandEval: eval-a
(1/3*1st lact.+1/3*2nd lact.+1/3*3rd+later lact.)	
Protein yield:
first to third lact.
first lact.
second lact.
third+latter lact.	
0.39
0.30
0.31
0.29	
285 kg2
205 kg2
342 kg2
350 kg2	StandEval: eval-a
(1/3*1st lact.+1/3*2nd lact.+1/3*3rd+later lact.)	
a	If lactations, or part of lactations, are treated as separate traits, provide heritability estimates and genetic variances separately for each lactation, as well as for all lactations pooled, i.e. for the trait submitted to Interbull.
b	Expressed as follows:
StandEval=((eval-a)/b)*c+d where a=mean of the base adjustment, b=standard deviation of the base, c=standard deviation of expression (include sign if scale is reversed), and d=base of expression.