Page Banner

United States Department of Agriculture

Agricultural Research Service

Research Project: Improving Genetic Predictions in Dairy Animals Using Phenotypic and Genomic Information

Location: Animal Genomics and Improvement Laboratory

Title: Development of a lifetime merit-based selection index for US dairy grazing systems

item Gay, Keegan
item Widmar, Nicole
item Nennich, Tamilee
item Schinckel, Allan
item Cole, John
item Schutz, Michael

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/11/2014
Publication Date: 7/1/2014
Publication URL:
Citation: Gay, K.D., Widmar, N.J., Nennich, T.D., Schinckel, A.P., Cole, J.B., Schutz, M.M. 2014. Development of a lifetime merit-based selection index for US dairy grazing systems. Journal of Dairy Science. 97(7):4568-4578.

Interpretive Summary: Management practices and environmental influences differ between confinement and pasture-based dairy production and may alter economic values for traits utilized in selection indexes. Development of a selection index utilizing economic values relevant to grazing dairy production demonstrated a need for separate indexes to maximize the genetic gain. Traits and their relative index weights were: milk volume (0%), fat yield (21%), protein yield (17%), productive life (7%), somatic cell count (-9%), feet and leg composite (4%), body size composite (-4%), udder composite (8%), daughter pregnancy rate (20%), calving ability (3%), and dairy form (6%); using prices parallel to Lifetime Net Merit$.

Technical Abstract: Pasture-based dairy producers in the US face costs, revenues and management challenges that differ from those associated with conventional dairy production systems. Three Grazing Merit indexes (GM$1, GM$2, and GM$3), parallel to the US Lifetime Net Merit (NM$) index, were constructed using economic values appropriate for grazing production in the US. Milk prices based on average prices from the previous five yr were used for GM$1, while GM$2 utilized milk prices found in NM$. Cull prices, interest rates, and milk prices from NM$ were used in GM$3. All other inputs remained constant among GM$1, GM$2, and GM$3. Economic costs and revenues were obtained from surveys, recent literature, and farm financial record summaries. Derived weights for GM$ were then multiplied by the Predicted Transmitting Abilities of 584 active Artificial Insemination Holstein bulls to compare with NM$. Spearman rank correlations for NM$ were 0.93 (p <.0001) with GM$1, 0.98 (p<.0001) with GM$2, and 0.98 (p<.0001) with GM$3. Traits included (and their percentage of weight) in GM$1, GM$2, and GM$3 respectively include: Milk Volume (24%, 0%, 0%), Fat Yield (16%, 21%, 21%), Protein Yield (4%, 17%, 17%), Productive Life (7%, 8%, 7%), Somatic Cell Count (-8%, -9%, -9%), Feet and Leg Composite (4%, 4%, 4%), Body Size Composite (-3%, -4%, -4%), Udder Composite (7%, 8%, 8%), Daughter Pregnancy Rate (18%, 20%, 20%), Calving Ability (3%, 3%, 3%), and Dairy Form (6%, 6%. 6%). This compared to NM$ weights of 0, 19, 16, 22, 10, 4, 6, 7, 11, 5, and 0 % for the same traits, respectively. Dairy Form was added to GM$ to offset the decrease in strength associated with selection to reduce stature through selection against Body Size. Emphasis on Productive Life decreased in GM$ because grazing cattle are estimated to remain in the herd considerably longer, diminishing the marginal value of Productive Life. While NM$ provides guidance for grazing dairy producers, a GM$ index based upon appropriate costs and revenues, would allow selection of cows and bulls for more optimal genetic progress.

Last Modified: 10/18/2017
Footer Content Back to Top of Page