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USDA Dairy Goat Genetic Evaluation Program Status and Plans. 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. Data Flow.
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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
Data Flow Milk Data collected monthly COMPONENT TEST LAB FARM DHIA DRPC ADGA INTERNET AIPL
Does Contributing Data from Test Day Nearest June 30th, 2002 By Processing Center
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
Issues Affecting Value of Data • Completeness of ID and parentage reporting • Years herd on test • Size of herd • Frequency of testing and component determination
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
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
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.
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 • Accuracy of pedigree data
Longevity Evaluation Dairy Cattle Program Productive Life (PL) • Number of months in milk up to: • 10mo per lactation • 84mo in age • Estimated for cows still in milk • Reliability increased using correlated traits: • type composites • yield traits
AIPL Web Services http://aipl.arsusda.gov/query/public/tdb.shtml#GoatsTBL • 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
Get goat pedigree and yield information http://aipl.arsusda.gov/cgi-bin/general/Qpublic/do.Q.cgi?qname=shgoat&single
Get yield and type evaluation http://aipl.arsusda.gov/cgi-bin/general/Qpublic/do.Q.cgi?qname=getbuck&single
Get goat error records by herd - output http://aipl.arsusda.gov/cgi-bin/general/Qpublic/do.Q.cgi?qname=goatherderr&single
Additional AIPL Web Resources http://aipl.arsusda.gov/docs/goatsfs.html • Documentation of evaluation process • Data requirements • Statistical models • Trait definitions http://aipl.arsusda.gov/links.html • Links to other resources including DHI, DRPC, and ADGA
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
Future Plans • Move calculations of goat evaluations to new computer • Possible use of dairy cattle programs • Add Productive Life and somatic cell score evaluations for goats • Value to producers • Staff resources required
Test Day Model • Test day replaces lactation yield in evaluation model • Advantages • Improved accounting of environmental effect • Allows for genetic differences in persistency and rate of maturity • Impeded by Cornell Research Foundation Patent • Currently challenged in Canada and EU • No licensing agreement has been reached