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Volume 49, issue 6
Arch. Anim. Breed., 49, 532–544, 2006
https://doi.org/10.5194/aab-49-532-2006
© Author(s) 2006. This work is distributed under
the Creative Commons Attribution 3.0 License.
Arch. Anim. Breed., 49, 532–544, 2006
https://doi.org/10.5194/aab-49-532-2006
© Author(s) 2006. This work is distributed under
the Creative Commons Attribution 3.0 License.

  10 Oct 2006

10 Oct 2006

Improving the monitoring of animal genetic resources on National and International level

Z. Duchev1,2 and E. Groeneveld1 Z. Duchev and E. Groeneveld
  • 1Institute for Animal Breeding, Federal Agricultural Research Center (FAL), Neustadt, Germany
  • 2Department of Animal Breeding and Genetics, University of Veterinary Medicine, Hannover, Germany

Abstract. The Farm Animal Biodiversity Network (FABISnet) is a new biodiversity network for collecting domestic animal breeds data from the European countries. Data are collected on National, Regional and Global level and can be automatically transferred between the levels. As a successor of the Animal Genetic Data Bank of the European Association for Animal Production (EAAP-AGDB) and the Domestic Animal Diversity Information System (DAD-IS) of the Food and Agricultural Organization (FAO), it has taken their historic data and integrated them in a network of databases. However, the data are incomplete. For example the general description of 57% of the registered European breeds are very sparse and for more than 3900 breeds the population size and structure statistics are outdated. A set of 13 management support reports and a methodology for their application has been developed. The reports present summarized information about the degree of completeness of the breeds descriptions by country, missing or incomplete population records, reminders for updating data and the status of data translation. Various monitoring/reporting tasks of the National and Regional Coordinators for management of animal genetic resources can be organized in a systematic manner using these reports. Such an organizational scheme can reduce the time spent in completing data and improve the content of each database in the network.

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