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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #382549

Research Project: Improving Dairy Animals by Increasing Accuracy of Genomic Prediction, Evaluating New Traits, and Redefining Selection Goals

Location: Animal Genomics and Improvement Laboratory

Title: Improving dairy feed efficiency, sustainability, and profitability by impacting farmer's breeding and culling decisions

item VANDEHAAR, MIKE - Michigan State University
item TEMPELMAN, ROBERT J - Michigan State University
item KOLTES, JAMES - Iowa State University
item APPUHAMY, RANGA - Iowa State University
item WHITE, H - University Of Wisconsin
item WEIGEL, KENT - University Of Wisconsin
item Baldwin, Ransom - Randy
item Vanraden, Paul
item PENAGARICANO, FRANCISCO - University Of Wisconsin
item SANTOS, JOSE - University Of Florida
item DURR, JOAO - Council On Dairy Cattle Breeding
item NICOLAZZI, EZEQUIEL - Council On Dairy Cattle Breeding
item BURCHARD, JAVIER - Council On Dairy Cattle Breeding
item PARKER GADDIS, KRISTEN - Council On Dairy Cattle Breeding

Submitted to: International Committee on Animal Recording(ICAR)
Publication Type: Abstract Only
Publication Acceptance Date: 3/15/2021
Publication Date: 4/26/2021
Citation: Vandehaar, M.J., Tempelman, R., Koltes, J.E., Appuhamy, R., White, H.M., Weigel, K.A., Baldwin, R.L., Van Raden, P.M., Penagaricano, F., Santos, J.E., Durr, J.W., Nicolazzi, E., Burchard, J.F., Parker Gaddis, K.L. 2021. Improving dairy feed efficiency, sustainability, and profitability by impacting farmer's breeding and culling decisions [abstract]. International Committee on Animal Recording(ICAR), April 26-30, Leeuwarden, The Netherlands. Abstract 8.6.

Interpretive Summary:

Technical Abstract: Enhancing feed efficiency should improve the profitability and sustainability of dairy farming due to reduced use of feed and land resources while potentially reducing emissions of greenhouse gas (GG) per liter of milk. The selection of animals that are genetically superior for feed efficiency requires precise measurements of feed energy intake and milk energy output from enough cows to predict genetic merit for feed efficiency with reasonable reliability. Previously, a consortium of experts in nutrition, management, population genetics, and genomics of dairy cattle from North America and Europe created a pool of data including 5,000 cows genotyped and phenotyped for feed intake and related traits (Tempelman et al., 2015; VandeHaar et al., 2016). Using this database, the researchers showed that dry matter intake and residual feed intake had sufficient heritability to enhance genetic progress for feed efficiency. Data from that study projected that the US dairy sector could save $540 million/year with maintained milk production by breeding for more efficient cows. The project presented herein was launched in 2019 to build on previous results and is the next logical step for implementing the selection for feed efficiency in the US and to address concerns about greenhouse gas emissions. Specific objectives are to 1) increase the reliability of genomic predictions for feed efficiency, 2) develop a feed intake index that uses sensors to predict feed intake on individual cows, 3) initiate a long-term program for updating genomic predictions of feed efficiency, and 4) determine if genomic predictions of feed efficiency can decrease methane emissions. The project protocol calls for the acquisition of data related to feed intake, milk yield and composition, and body weight for 42 days in 3600 mid-lactation cows (50-200 DIM) over a 5-year period. Additionally, a subset of cows will be fitted with sensors to monitor body temperature, feeding behavior, and locomotion. Mid-infrared spectral profiles will be collected from all milk samples. Methane emission will be measured in 300 cows. Data collection is in progress at all research stations. These data will be used to develop a genomic evaluation for feed efficiency in U.S. Holsteins and support the development of management tools.