Form GE

Status as of: May 1, 2007

Form GE

DESCRIPTION OF NATIONAL GENETIC EVALUATION SYSTEMS

Country (or countries)	United States of America
Main trait group¹	Yield – milk, fat, and protein production
Breed(s)	Holstein, Jersey, Brown Swiss, Guernsey, Ayrshire, Milking Shorthorn All breeds and crossbred cows are evaluated together in a multi-breed animal model
Trait definition(s) and unit(s) of measurement²	Milk (lb), fat and protein (lb, %) 305-day lactation yields
Method of measuring and collecting data	Collected by Dairy Herd Improvement Associations using ICAR approved methods and Quality Certification standards administered by the Council on Dairy Cattle Breeding.
Time period for data inclusion	First calving 1960 and later plus pedigree from birth year 1950 and later.
Age groups (e.g. parities) included	First five parities are included (a first lactation is required before later lactations can contribute to sire evaluations).
Other criteria (data edits) for inclusion of records	Valid sire ID required. Lactations from cows >40 DIM and cows removed from the herd >15 DIM are included. TD by 90 DIM required. Owner sampler records are used from herds that meet identification, outlier, and bulk tank comparison limits.
Criteria for extension of records (if applicable)	Records < 305 d are extended to 305 d using best prediction.
Sire categories	All sires are evaluated together. About 1950 AI and 1885 natural service new bulls evaluated each year.
Environmental effects³, pre-adjustments	Multiplicative adjustments for age at calving and month of calving within each breed, times milked per day (adjusted to twice daily milking), previous days open, and heterogeneous variance. The base age for mean and variance adjustments is 36-month-old second parity cows. Unequal variances across time, across herds, and across breeds are adjusted to the Holstein base variance calculated from standardized records of first lactation cows that calved in 2002.
Method (model) of genetic evaluation³	ST BLUP repeatability animal model.
Environmental effects³ in the genetic evaluation model	Fixed: management group [flexible herd-year-season (2-12 months), includes registry status for HOL], parity by age, regression on inbreeding, and regression on general heterosis. Random: permanent environment, herd by sire interaction. This model produces PTA adjusted to 0 inbreeding and 0 heterosis, but published PTA include the regressions multiplied by expected future inbreeding (EFI) and by coefficient of heterosis when mated to purebreds as a post-processing step.
Adjustment for heterogeneous variance in evaluation model	Pre-adjustments are applied.
Use of genetic groups and relationships	Unknown parents are grouped by year, breed, and, for Holsteins, separately for U.S. and foreign animals. Unknown sires and dams of cows are grouped separately, but unknown parents of bulls are in a combined group. Separate unknown parent groups are used for red and white or black and white Holsteins. The relationship matrix accounts for effects of inbreeding on Mendelian sampling variance.
Blending of foreign/Interbull information in evaluation	Interbull sire evaluations and converted foreign dam evaluations from the previous evaluation with higher reliability than the current US evaluation are used to update parent averages and calculate evaluations.
Genetic parameters in the evaluation	See PART 2 for heritability/genetic variance estimates and calculation of reliability section below for use in calculation. Permanent environment variance 18%, herd by sire interaction 7%, repeatability 55%
System validation	Means and SD for all variables are calculated and examined overall. Means for new bulls, changes for high bulls, largest changes, and key statistics for recent AI bulls are checked. Genetic trends for each breed are validated by methods 1, 2, and 3.
Expression of genetic evaluations If standardised (e.g. RBV), give standardisation formula in the appendix	PTA, lb and component % All-breed PTAs are adjusted to within-breed bases as follows: within-breed PTA = (all-breed PTA – breed mean) * (breed SD / Holstein SD)
Definition of genetic reference base Next base change	Cows born in 2000, (stepwise, 5 year). February 2010 (when the base will be cows born in 2005).
Calculation of reliability	Daughter equivalents from parents and from progeny are summed by processing progeny from the youngest to oldest generation and then parents from oldest to youngest. Starting values for mate reliability are from the previous evaluation. Cows sired by Jersey or Brown Swiss bulls are assumed to have heritability of .35 instead of .30. Instead of using differing heritabilities within animal model and reliability calculations, lactation weights for such cows are increased to reflect their decreased error variance.
Criteria for official publication of evaluations	At least 10 daughters with usable lactation record. Interbull evaluations are reported as official in the US if: they include data from an additional country; the US has no evaluation; or Interbull excludes US data and the Interbull evaluation has a higher reliability.
Number of evaluations / publications per year	Three, in February, May, and August of 2007, and in January, April, and August beginning 2008.
Use in total merit index⁴	Lifetime net merit dollars (NM$) = 3.55* protein + 2.70fat + 29productive life - 150(SCS-3) + 28udder composite + 13* feet & leg composite - 14size composite + 21daughter pregnancy rate + calving ability dollars (CA$). Relative values of the traits are 23%, 23%, 17%, -9%, 6%, 3%, -4%, 9%, and 6%, respectively. Traits are expressed as PTA, and weights are lifetime $ / PTA unit. CA$ and SCS are deviations from the base, i.e. not the published PTA which include a population average. The CA$ includes service sire calving ease, daughter calving ease, service sire stillbirth, and daughter stillbirth with relative weights of 25%, 15%, 15%, and 45%, respectively.
Anticipated changes in the near future	None
Key reference on methodology applied	· VanRaden, P.M. 1997. Lactation yields and accuracies computed from test day yields and (co)variances by best prediction. J. Dairy Sci. 80:3015. · VanRaden, P.M., and L.A. Smith. 1999. Selection and mating considering expected inbreeding of future progeny. J. Dairy Sci. 82:2771. · VanRaden, P.M., M.E. Tooker, J.B. Cole, G.R. Wiggans, and J.H. Megonigal, Jr. 2007. Genetic evaluations for mixed-breed populations. J. Dairy Sci. 90:2434. · VanRaden, P.M., and G.R. Wiggans. 1991. Derivation, calculation, and use of national animal model information. J. Dairy Sci. 74:2737. · VanRaden, P.M., G.R. Wiggans, and C.A. Ernst. 1991. Expansion of projected lactation yield to stabilize genetic variance. J. Dairy Sci. 74:4344. · Wiggans, G.R., I. Misztal, and L.D. Van Vleck. 1988. Implementation of an animal model for genetic evaluation of dairy cattle in the United States. J. Dairy Sci. 71(Suppl. 2):54. · Wiggans, G.R., and P.M. VanRaden. 1991. Method and effect of adjustment for heterogeneous variance. J. Dairy Sci. 74:4350.
Key organisation: name, address, phone, fax, e-mail, web site	United States Department of Agriculture Agricultural Research Service Animal Improvement Programs Laboratory Building 005, BARC-West 10300 Baltimore Avenue Beltsville, Maryland 20705-2350 U.S.A. Voice: 301-504-8334 Fax: 301-504-8092 E-mail: inquiry@aipl.arsusda.gov web site: http://aipl.arsusda.gov

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 used in genetic evaluation

Country (or countries):	United States of America
Main trait group:	Production (Yield)
Breed (repeat as necessary):	AYS, GUE, HOL, MSH, BSW, JER

Trait	Def	ITB^a		h^2b	genetic St.Dev.^b	official proof standardisation formula^c
Milk yield		X	Varies with herd variance. 0.25 to 0.35, mean = 0.30		GUE 1393 HOL 1444 RDC 1132	Conversions from the all-breed base to the within-breed bases will be updated on the AIPL web site. March 2007 formulas were: GUE PTA = (all-breed PTA + 2800).858 HOL PTA = (all-breed PTA – 252)1.000 MSH PTA = (all-breed PTA + 3015).711 RDC PTA = (all-breed PTA + 2355).719
Fat yield		X	Varies with herd variance. 0.25 to 0.35, mean = 0.30		GUE 51 HOL 52 RDC 39	GUE PTA = (all-breed PTA + 37).858 HOL PTA = (all-breed PTA – 3)1.000 MSH PTA = (all-breed PTA + 119).711 RDC PTA = (all-breed PTA + 64).719
Protein yield		X	Varies with herd variance. 0.25 to 0.35, mean = 0.30		GUE 38 HOL 37 RDC 30	GUE PTA = (all-breed PTA + 63).858 HOL PTA = (all-breed PTA – 4)1.000 MSH PTA = (all-breed PTA + 95).711 RDC PTA = (all-breed PTA + 60).719
Milk yield		X	Varies with herd variance. 0.30 to 0.40, mean = 0.35		BSW 1317 JER 1204	BSW PTA = (all-breed PTA + 1846).951 JER PTA = (all-breed PTA + 3015).888
Fat yield		X	Varies with herd variance. 0.30 to 0.40, mean = 0.35		BSW 52 JER 50	BSW PTA = (all-breed PTA + 36).951 JER PTA = (all-breed PTA + 33).888
Protein yield		X	Varies with herd variance. 0.30 to 0.40, mean = 0.35		BSW 40 JER 36	BSW PTA = (all-breed PTA + 31).951 JER PTA = (all-breed PTA + 48).888

^a Indicate, with X, traits that are submitted to Interbull for international genetic evaluations.

^b If repeated records are treated as separate traits, provide heritability estimates and genetic variances separately for each trait, as well as for all traits pooled, i.e. for the trait submitted to Interbull.

^c 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.