Status as of: 2019-04-02

Form GE

DESCRIPTION OF NATIONAL GENETIC EVALUATION SYSTEMS

Country (or countries)	Germany, Austria and Luxembourg	
Main trait group1
NOTE! Only one trait group per form!	Production	
Breed(s)	HOLstein (Black & White, Red & White), Red dairy cattle (RDC), 
JERsey	
Trait definition(s) and unit(s) of measurement2
Attach an appendix if needed	Milk (kg), fat (kg), protein (kg) on 24-hour daily basis	
Method of measuring and collecting data	All production data collected by official milk recording agencies using ICAR certified milk recording methods	
Time period for data inclusion	All test day records from 1990 onwards 	
Age groups (e.g. parities) included	First three lactations	
Other criteria (data edits) for inclusion of records	Allowed ranges of age of calving for first three lactations are 20-40, 30-56 and 44-75 months, respectively. Range of days in milk is 5 to 330. Every test day record must have three yield traits and somatic cell score data available. Only lactations with at least 2 test day records are included in genetic evaluation.	
Criteria for extension of records (if applicable)	Yields from single milking schemes are converted to 24-hour daily yield basis (Liu et al. 2000), prior to being included in genetic evaluation. The estimated daily yields from single milking schemes are assigned with lower accuracy than the standard A4 milk recording scheme.	
Sire categories	All categories of bulls are evaluated jointly	
Environmental effects3, pre-adjustments 	No pre-adjustments for environmental effects	
Method (model) of genetic evaluation3	ST – ML – RR – TD – BLUP – AM	
Environmental effects3 in the genetic evaluation model	Fixed effects: herd-test-date-parity-milking-frequency effects for first lactation and combined second and third lactations, fixed lactation curves defined by lactation number * region/breed * calving age class * calving year class * calving season * calving interval class 
Random effects: permanent environmental effects by lactation	
Adjustment for heterogeneous variance in evaluation model	Standardization of heterogeneous variances within herd-test-date-parity-milking-frequency effect is performed prior to solving mixed model equations	
Use of genetic groups and relationships	Genetic groups are defined for unknown parents of animals based on breed, selection path, birth year and country of origin of the animal. Ancestors of the cows in test day data set are traced back as far as possible in pedigree.  	
Blending of foreign/Interbull information in evaluation	No	
Genetic parameters in the evaluation	Use Appendix GE for heritability/genetic variance estimates; for multiple-trait genetic evaluations, provide genetic correlation estimates between traits separately.
Use also appendices PR, CO, BCO, SM, LO, CA, as applicable, if you participate in the international genetic evaluations of Interbull	
System validation	- Regularly performing trend validation using Interbull methods II and III 
- Routinely checking stability of genetic evaluations over time
- Routinely checking quality of input data and pedigree 
- Residual and Mendelian sampling analyses 	
Expression of genetic evaluations
If standardised (e.g. RBV), give standardisation formula in the appendix	EBV for five production traits: milk, fat, protein yields, fat and protein contents are expressed on the base of a cow population
EBV on a combined lactation is calculated as a linear function of lactation EBV with equal weights:
     EBVcomb = (EBV1 + EBV2 + EBV3)/3. 
EBV for fat and protein contents are derived from EBV of the three yield traits and phenotypic yield averages (MKG, F% and P%) of all the base cows in second lactation:
      EBVF% = (EBVfat * 100 – EBVmil * F%) / (EBVmil + MKG)
      EBVP% = (EBVpro * 100 – EBVmil*P%) / (EBVmil + MKG)
Milk production index (RZM) is defined based on a cow population that is updated yearly and has an average of 100. 	
Definition of genetic reference base

Next base change	A cow genetic base for production trait EBV includes all active cows of last three birth years, separately for each breed. 
Base cows have an average of 100 for the milk production index RZM, by breed.  
April 2020  	
Calculation of reliability	Using the multi-trait effective daughter contribution method (Liu et al. 2004)	
Criteria for official publication of evaluations	AI Bulls with daughters in at least 10 herds are published. 	
Number of evaluations / publications per year	3 / April, August and December 	
Use in total merit index4	RZM (relative breeding value milk) separately for breeds:
Holstein (Black & White, Red & White and MRY):
       100 + 0.24*EBVfat + 0.48*EBVpro 
Red  Dairy Cattle:     
       100 + 0.29*EBVfat + 0.58*EBVpro
Jersey:
       100 + 0.24*EBVfat + 0.48*EBVpro
The production index RZM has a weight of 45% in German total merit index RZG for Holstein and 40% for RDC.  	
Anticipated changes in the near future		
Key reference on methodology applied	Liu, Z., Reinhardt, F., and Reents, R. 2000. Estimating parameters of a random regression test day model for first three lactation milk production traits using the covariance function approach. Interbull Bulletin 25:74-80.
Liu, Z., Reents, R., Reinhardt, F., and Kuwan, K. 2000. Approaches to estimating daily yield from single milking testing schemes and use of a.m.-p.m. records in test-day model genetic evaluation in dairy cattle. J. Dairy Sci. 83:2672-2682.
Liu, Z., F. Reinhardt, A. Bünger, and R. Reents 2004. Derivation and calculation of approximate reliabilities and daughter yield-deviations of a random regression test-day model for genetic evaluation of dairy cattle. J. Dairy Sci. 87:1896-1907.	
Key organisation: name, address, phone, fax, e-mail, web site	Vereinigte Informationssysteme Tierhaltung w. V. (vit), 
Genetic Evaluation and Biometrics Division,
Heinrich-Schröder-Weg 1, 27283 Verden/Aller, GERMANY
Phone: +49  4231  955 10
Fax:     +49  4231  955 166
e-mail: ge@vit.de or info@vit.de,  website: http://www.vit.de	
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):	Germany, Austria and Luxembourg	
Main trait group:	Production	
Breed(s):	HOLstein (Black & White, Red & White), Red Dairy Cattle (RDC), 
JERsey	

Trait	h2a	genetic
variancea	official proof
standardisation formulab	
Milk yield:
	0.39 
on a combined lactation basis	373,052 (HOL)
337,015 (RDC)
238,955 (JER)		
Fat yield:
	0.30 
	526 (HOL)
532 (RDC)
464 (JER)		
Protein yield:
	0.30 
	277 (HOL)
295 (RDC)
238 (JER)		
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.

Table 1: Genetic parameters for milk, fat and protein yield with heritabilities on diagonal, genetic correlations above & phenotypic correlations below diagonal (Holsteins)

Trait	
Lactation	Genetic variance (kg2)	Lactation	
			1	2	3	Combined	
	1		.43	.84	.84		
Milk yield 	2		.55	.26	.97		
	3		.52	.54	.25		
	Combined 	373,052				.39	
	1		.33	.87	.86		
Fat	2		.55	.19	.97		
	3		.50	.54	.19		
	Combined	526				.30	
	1		.33	.84	.81		
Protein	2		.56	.38	.96		
	3		.49	.57	.38		
	Combined	277				.30