Which new traits are expected to be available in the near future?


  • Christa Egger-Danner ZuchtData EDV-Dienstleistungen GmbH, Dresdner Str. 89/19, A-1200 Vienna, Austria
  • John B. Cole Animal Improvement Programs Laboratory, ARS, USDA, 10300 Baltimore Avenue, Beltsville, Maryland 20705-2350, USA
  • Jennie E. Pryce Department of Environment and Primary Industries, Agribio, 5 Ring Road, Bundoora, Victoria 3083, Australia
  • Nicolas Gengler University of Liège, Gembloux Agro-Bio Tech (GxABT), Animal Science, Passage des Déportés, 2, B-5030 Gembloux, Belgium
  • Bjorg Heringstad Norwegian University of Life Sciences, Department of Animal and Aquacultural Sciences, P.O. Box 5003, N-1432 Ås, Norway
  • Andrew Bradley Quality Milk Management Services Ltd, Cedar Barn, Easton Hill, Easton, Wells, Somerset, BA5 1EY, United Kingdom
  • Kathrin F. Stock Vereinigte Informationssysteme Tierhaltung w.V. (vit), Heideweg 1, D-27283 Verden, Germany


phenotypes, novel traits, genomics


For several decades breeding goals in cattle were strongly linked to increases in milk production. Many functional traits have unfavourable genetic correlations with milk yield, which has led to an accompanying reduction in genetic merit for functional traits. Herd management has been challenged to compensate for these effects, and to balance fertility, udder health, and metabolic diseases in order to maximise profit without compromising long-term welfare. Functional traits, such as direct information on cow health, have also become more important because of consumer interest in animal well-being and demands for healthy and natural products. There are major concerns about the impact of drugs used in veterinary medicine on the spread of antibiotic-resistant strains of bacteria that can negatively impact human health. Sustainability and efficiency are also increasing in importance because of growing competition for high-quality, plant-based sources of energy and protein. Disruptions in global inventories due to climate change also may encourage more emphasis on these traits. For data recording efforts to succeed it is crucial that there is a balance of effort with benefits. The motivation of farmers and other stakeholders involved in documentation and recording is essential to ensure that data quality is high. To keep down the labor costs associated with recording to a reasonable level it is important that to utilize existing data sources. Examples include the use of milk composition data to provide additional information about the metabolic status or energy balance of the animals. Recent advances in the indirect use of mid-infrared spectroscopy to measure the required fine milk composition (e.g., fatty acid composition) have shown considerable promise. There are other valuable data sources in countries with compulsory recording of veterinary treatments and drug use. For countries that rely on recording on a voluntary basis there are also quality assurance systems requesting more documentation. Sources of data outside of the farm include slaughter houses and veterinary laboratories. At the farm level huge amounts of data are increasingly available from automated and semi-automated milking and management systems. Electronic devices measuring physiological or activity parameters can predict physiological status such as estrus, and can also record behavioural traits. In order to develop effective selection programs for new traits, the development of large databases is necessary in order to produce high-reliability predicted transmitting abilities which can be used as inputs for genomic evaluation.