title: Harnessing the genetics of the modern dairy cow to continue improvements in feed efficiency.
abstract: Feed efficiency, as defined by the fraction of feed energy or dry matter captured in products, has more than doubled for the US dairy industry in the past 100 yr. This increased feed efficiency was the result of increased milk production per cow achieved through genetic selection, nutrition, and management with the desired goal being greater profitability. With increased milk production per cow, more feed is consumed per cow, but a greater portion of the feed is partitioned toward milk instead of maintenance and body growth. This dilution of maintenance has been the overwhelming driver of enhanced feed efficiency in the past, but its effect diminishes with each successive increment in production relative to body size and therefore will be less important in the future. Instead, we must also focus on new ways to enhance digestive and metabolic efficiency. One way to examine variation in efficiency among animals is residual feed intake (RFI), a measure of efficiency that is independent of the dilution of maintenance. Cows that convert feed gross energy to net energy more efficiently or have lower maintenance requirements than expected based on body weight use less feed than expected and thus have negative RFI. Cows with low RFI likely digest and metabolize nutrients more efficiently and should have overall greater efficiency and profitability if they are also healthy, fertile, and produce at a high multiple of maintenance. Genomic technologies will help to identify these animals for selection programs. Nutrition and management also will continue to play a major role in farm-level feed efficiency. Management practices such as grouping and total mixed ration feeding have improved rumen function and therefore efficiency, but they have also decreased our attention on individual cow needs. Nutritional grouping is key to helping each cow reach its genetic potential. Perhaps new computer-driven technologies, combined with genomics, will enable us to optimize management for each individual cow within a herd, or to optimize animal selection to match management environments. In the future, availability of feed resources may shift as competition for land increases. New approaches combining genetic, nutrition, and other management practices will help optimize feed efficiency, profitability, and environmental sustainability.
authors.affiliation: Department of Animal Science, Michigan State University, East Lansing 48824. Electronic address: mikevh@msu.edu.
authors.forename: M J
authors.initials: MJ
authors.lastname: VandeHaar
authors.affiliation: Department of Dairy Science, University of Wisconsin, Madison 53706.
authors.forename: L E
authors.initials: LE
authors.lastname: Armentano
authors.affiliation: Department of Dairy Science, University of Wisconsin, Madison 53706.
authors.forename: K
authors.initials: K
authors.lastname: Weigel
authors.affiliation: Department of Animal Sciences, Iowa State University, Ames 50011.
authors.forename: D M
authors.initials: DM
authors.lastname: Spurlock
authors.affiliation: Department of Animal Science, Michigan State University, East Lansing 48824.
authors.forename: R J
authors.initials: RJ
authors.lastname: Tempelman
authors.affiliation: Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, PO Box 65, NL-8200 AB Lelystad, the Netherlands.
authors.forename: R
authors.initials: R
authors.lastname: Veerkamp
mesh_terms: D000821:Animal Feed / Q000032:analysis*; D000824:Animal Nutritional Physiological Phenomena; D000818:Animals; D002417:Cattle / Q000235:genetics*; D003612:Dairying; D004032:Diet / Q000662:veterinary; D005260:Female; D005298:Fertility; D023281:Genomics; D060005:Genotyping Techniques; D008892:Milk / Q000737:chemistry
keywords: dairy cattle; feed efficiency; genetics