TY - JOUR
T1 - Short communication
T2 - Variance estimates among herds stratified by individual herd heritability
AU - Dechow, C. D.
AU - Norman, H. D.
AU - Pelensky, C. A.
N1 - Funding Information:
The authors appreciate funding from the Agricultural Research Service, USDA. The cooperation of AgriTech Analytics (Visalia, CA), AgSource Cooperative Services (Verona, WI), Dairy Records Management Systems (Raleigh, NC), DHI Computing Services (Provo, UT), and Texas DHIA (College Station, TX) in supplying yield data through the National Genetic Improvement Program was invaluable.
PY - 2008/4
Y1 - 2008/4
N2 - The objectives of this study were to compare (co)variance parameter estimates among subsets of data that were pooled from herds with high, medium, or low individual herd heritability estimates and to compare individual herd heritability estimates to REML heritability estimates for pooled data sets. A regression model was applied to milk yield, fat yield, protein yield, and somatic cell score (SCS) records from 20,902 herds to generate individual-herd heritability estimates. Herds representing the 5th percentile or less (P5), 47th through the 53rd percentile (P50), and the 95th percentile or higher (P95) for herd heritability were randomly selected. Yield or SCS from the selected herds were pooled for each percentile group and treated as separate traits. Records from P5, P50, and P95 were then analyzed with a 3-trait animal model. Heritability estimates were 23, 31, 26, and 8% higher in P95 than in P5 for milk yield, fat yield, protein yield, and SCS, respectively. The regression techniques successfully stratified individual herds by heritability, and additive genetic variance increased progressively, whereas permanent environmental variance decreased progressively as herd heritability increased.
AB - The objectives of this study were to compare (co)variance parameter estimates among subsets of data that were pooled from herds with high, medium, or low individual herd heritability estimates and to compare individual herd heritability estimates to REML heritability estimates for pooled data sets. A regression model was applied to milk yield, fat yield, protein yield, and somatic cell score (SCS) records from 20,902 herds to generate individual-herd heritability estimates. Herds representing the 5th percentile or less (P5), 47th through the 53rd percentile (P50), and the 95th percentile or higher (P95) for herd heritability were randomly selected. Yield or SCS from the selected herds were pooled for each percentile group and treated as separate traits. Records from P5, P50, and P95 were then analyzed with a 3-trait animal model. Heritability estimates were 23, 31, 26, and 8% higher in P95 than in P5 for milk yield, fat yield, protein yield, and SCS, respectively. The regression techniques successfully stratified individual herds by heritability, and additive genetic variance increased progressively, whereas permanent environmental variance decreased progressively as herd heritability increased.
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U2 - 10.3168/jds.2007-0622
DO - 10.3168/jds.2007-0622
M3 - Article
C2 - 18349257
AN - SCOPUS:42449156335
SN - 0022-0302
VL - 91
SP - 1648
EP - 1651
JO - Journal of dairy science
JF - Journal of dairy science
IS - 4
ER -