1. USDA Dairy Goat Genetic Evaluation Program

2. USDA Dairy Goat Evaluations
Evaluations for milk, fat, protein, and type
Yield evaluations in July
Type evaluations in December
Evaluations provided to ADGA, DRPC, and publicly via the Internet

3. Data Flow FARM DHIA DRPC ADGA AIPL COMPONENT TEST LAB INTERNET
Milk Data collected monthly
COMPONENT TEST LAB
FARM
DHIA
Center
Data Sent to AIPL
DRMS – NC
Daily
DHI-Provo – UT
Agri-Tech – CA
2x/week
AgSource – WI
Weekly
Langston - OK
Monthly
DRPC
ADGA
INTERNET
AIPL

4. Does Contributing Data from Test Day Nearest June 30th, 2003 By Processing Center
Herds
Does
Percent of Does
DRMS
142
2529
35.0
DHI-Provo
162
2449
33.8
Agri-Tech 21
835
11.5
AgSource 26
727
10.0
Langston 90
694
9.6
Total
441
7234

5. Alpine Milk Production Lactation Curve

6. Alpine Fat Percentage Lactation Curve

7. Alpine Protein Percentage Lactation Curve

8. Alpine and Nubian Milk Production Second Lactation

9. Nubian Fat and Protein Percentage Second Lactation

10. Genetic Improvement Program
Phenotype = Genotype + Environment
Genetic improvement programs only change genotype
Heritability is the portion of total variation due to genetics
Rate of genetic improvement determined by
generation interval
selection intensity
heritability

11. Factors Affecting Value of Data
Completeness of ID and parentage reporting
Years herd on test
Size of herd
Frequency of testing and component determination

12. Evaluation Calculation
Goal
predict productivity of progeny
Method
separate genetic component from other factors influencing evaluated traits
All relationships are considered
bucks receive evaluations from the records on their female relatives

13. Yield Evaluation Model
MODEL: y = hys + hs + pe + a + e
y = yield of milk, fat, or protein during a lactation
hys = herd-year-season
- accounts for environmental effects common to does kidding in the same herd in the same season
hs = herd-sire
- effect common to daughters of a buck in the same herd
pe = permanent environment
- effect common to all a doe's lactations that is not genetic
a = animal genetic effect (breeding value)
e = unexplained residual

14. Index of Yield Evaluations
Milk-Fat-Protein Dollars (MFP$) combines evaluations into a single number
MFP$ = (0.010  PTAM) +
(1.15  PTAF) + (2.55  PTAP)

15. Breeding Value Trend for Milk

16. Breeding Value Trend for Fat

17. Breeding Value Trend for Protein

18. Type Traits Measure of similarity to ideal
Final Score (overall assessment)
scored  50-99
Linear traits (13 defined traits)
scored 1-50

19. Linear Traits Stature - Height at withers
Strength - Width and depth of chest, width of muzzle
Dairyness - Sharpness and flatness of bone, etc.
Teat diameter - Measured at base
Rear Legs - Angle of the hock, side view

20. Linear Traits Rump Angle - Angle from hips to pins
Rump Width - Width of pelvis
Fore Udder Attachment - Strength of attachment
Rear Udder Height - Distance from vulva to top of udder

21. Linear Traits
Rear Udder Arch - Width and shape of rear udder attachment
Udder Depth - Measured relative to hocks
Medial Suspensory Ligament - Measure of udder cleft
Teat Placement - Distance between teats

22. Type Evaluation Model MODEL: y = h + a + p + e
y = adjusted type record
h = herd appraisal date
a = animal genetic effect (breeding value)
p = permanent environment
- effect common to all a doe's lactations that is not genetic
e = unexplained residual
Multi-trait evaluation allows scores from one trait to affect the evaluation of another trait through the genetic correlations among the traits.

23. Recent Type Appraisal Data
1998
1999
2000
2001
2002
Alpine
1293
1050
1072
1341
1038
Nubian
1393
1286
1319
1299
1081
Toggenburg
592
587
473
672
474
LaMancha
875
635
719
667
627
Saanen
426
459
389
659
502
Oberhasli
370
216
254
323
301
Experimental
253
198
191
269
210

24. Type Trait Genetic Correlations
Final Score
Strength
Dairyness
Fore Udder Attachment
1.00
.30
-.15
.66
-.51
.15
-.16
F. Udder Att.

25. Breeding Value Trend for Type

26. Accuracy of Evaluations
Number of does kidding in same hys
more records  better estimate of hys effect
Number of bucks with daughters having records in same hys
more direct comparisons  better ranking of bucks
Number of lactation records
Number of daughters
Completeness of pedigree data

27. Selection is a Continuous Decision Making Process
Which does to breed
Which bucks to use
Which specific matings
Avoiding inbreeding
Correction of faults
Which kids to raise
Which kids to breed
Which does to milk

28. Selection is a Continuous Decision Making Process
The greatest impact on progress is from selection of bucks

29. Program for Genetic Improvement
Dairy cattle program based on:
Artificial insemination (AI)
Allows for many progeny from superior males
Allows semen to be used in geographically diverse locations
Progeny testing (PT)
Use young males to get a representative group of daughters
Wait until those daughters are milking
Based on the evaluations, return the best males to heavy use

30. Dairy Cattle Improvement Program
About 1 in 10 PT bulls become active
Bulls remain active only a few years
Young bulls waiting for daughter records are not active
Intensive selection program

31. Steps to Increase Rate of Improvement in Goats
Employ AI to use better bucks in more herds
Focus on larger herds to improve accuracy
Identify young bucks for PT

32. Alternative to Waiting for PT
Use young bucks for most breedings
Replace bucks quickly
Bank semen of young bucks
Use frozen semen from superior proven bucks as sires of next generation of young bucks

33. AIPL Web Services Queries provide display of:
Queries provide display of:
pedigree information
yield records
herd test characteristics
genetic evaluations of does & bucks
yield
Type
Access information using:
ID number
animal name
herd code

34. http://aipl. arsusda. gov/cgi-bin/general/Qpublic/do. Q. cgi

36. http://aipl. arsusda. gov/cgi-bin/general/Qpublic/do. Q. cgi

38. http://aipl. arsusda. gov/cgi-bin/general/Qpublic/do. Q. cgi

41. http://aipl. arsusda. gov/cgi-bin/general/Qpublic/do. Q. cgi

43. Recent Changes New web query for accessing data by animal name
Yield data since 1998 extracted from the master file each run
incorporates corrections, deletions, and ID changes
Standardized yields back to 1974 available

44. Possible Enhancements
Add evaluations for more traits
Productive Life
Somatic Cell Score
Daughter Pregnancy Rate
Switch to test day model
Provides better accounting for environment
Accounts for genetic differences in shape of lactation curve