Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 550684
Title Review of sensor technologies in animal breeding: Phenotyping behaviors of laying hens to select against feather pecking
Author(s) Ellen, Esther D.; Sluis, Malou Van Der; Siegford, Janice; Guzhva, Oleksiy; Toscano, Michael J.; Bennewitz, Jörn; Zande, Lisette E. Van Der; Eijk, Jerine A.J. Van Der; Haas, Elske N. de; Norton, Tomas; Piette, Deborah; Tetens, Jens; Klerk, Britt de; Visser, Bram; Bas Rodenburg, T.
Source Animals 9 (2019)3. - ISSN 2076-2615
Department(s) Animal Breeding & Genomics
Adaptation Physiology
Behavioral Ecology
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) -omics - Computer vision - Damaging behavior - Genetic selection - Identification - Measuring behavior - Radio frequency identification - Ultra-wideband

Damaging behaviors, like feather pecking (FP), have large economic and welfare consequences in the commercial laying hen industry. Selective breeding can be used to obtain animals that are less likely to perform damaging behavior on their pen-mates. However, with the growing tendency to keep birds in large groups, identifying specific birds that are performing or receiving FP is difficult. With current developments in sensor technologies, it may now be possible to identify laying hens in large groups that show less FP behavior and select them for breeding. We propose using a combination of sensor technology and genomic methods to identify feather peckers and victims in groups. In this review, we will describe the use of “-omics” approaches to understand FP and give an overview of sensor technologies that can be used for animal monitoring, such as ultra-wideband, radio frequency identification, and computer vision. We will then discuss the identification of indicator traits from both sensor technologies and genomics approaches that can be used to select animals for breeding against damaging behavior.

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