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United States Department of Agriculture

Agricultural Research Service

Title: Use of (Co)variance Functions to Describe (Co)variances for Test Day Yield

Authors
item Tijani, Aziz - FAC UNIV SCI AGR0 BELGIUM
item Wiggans, George
item Van Tassell, Curtis
item Lake, Jill
item Gengler, Nicolas - FAC UNIV SCI AGRO BELGIUM

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 5, 1998
Publication Date: N/A

Interpretive Summary: The use of test-day yields instead of 305-day lactation yields recently has become the focus of much research on evaluation systems for dairy genetics. A genetic evaluation system based on a test-day statistical model can account for environmental effects more accurately than models based on 305-day lactations and also can accommodate greater variability in milk recording plans. However, such a statistical model requires information on how the test-day yields are related to one another over the course of lactation. Mathematical functions were developed to interpolate and to extend previously calculated estimates of relationships among test- day milk, fat, and protein yields during first lactation. This methodology provides information crucial to the development of improved genetic evaluation systems based on test-day yield information, which will allow dairy breeders to select more accurately for desired yield traits.

Technical Abstract: (Co)variance functions for milk, fat, and protein yields during first lactation were developed based on estimates of (co)variance components from test day data from 17,190 Holstein cows from 37 herds in Pennsylvania and Wisconsin and four 75-day lactation stages. (Co)variance components were estimated for twelve 25-day lactation stages starting at day 6 using those (co)variance functions. Residuals were subdivided into time- dependent and temporary environmental effects for estimation of (co)variance functions. Mean relative variance (portion of total variance) for time-dependent environmental effects was .50 for milk yield and .51 for fat and protein yields. Heritability estimates generally were lower at start and end of lactation and were highest for milk yield; mean heritability estimates were .20 for milk, .16 for fat, and .17 for protein yields. Phenotypic and genetic correlations were higher between milk and protein yields than between milk and fat yields. Within yield trait, genetic correlations declined from .93 or higher for adjacent lactation stages to .52 for milk, .58 for fat, and .60 for protein between initial and final lactation stages. Within lactation stage, mean genetic correlations were .40 between milk and fat yields, .78 between milk and protein yields, and .55 between fat and protein yields; corresponding mean phenotypic correlations were .65, .92, and .67. The (co)variance function methodology allowed increased density of (co)variance estimation over the entire lactation.

Last Modified: 11/22/2014
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