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.

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    Assessing the activity of individual group-housed broilers throughout life using a passive radio frequency identification system—a validation study
    Sluis, Malou van der; Haas, Yvette de; Klerk, Britt de; Rodenburg, T.B. ; Ellen, Esther D. - \ 2020
    Sensors 20 (2020)13. - ISSN 1424-8220 - p. 1 - 21.
    Activity - Broilers - Radio frequency identification - Tracking - Ultra-wideband - Video

    Individual data are valuable for assessing the health, welfare and performance of broilers. In particular, data on the first few days of life are needed to study the predictive value of traits recorded early in life for later life performance. However, broilers are generally kept in groups, which hampers individual identification and monitoring of animals. Sensor technologies may aid in identifying and monitoring individual animals. In this study, a passive radio frequency identification (RFID) system was implemented to record broiler activity, in combination with traditional video recordings. The two main objectives were 1) to validate the output of the RFID system by comparing it to the recorded locations on video, and 2) to assess whether the number of antennas visited per unit time could serve as a measure of activity, by comparing it to the distance recorded on video and to the distance moved as recorded using a validated ultra-wideband (UWB) tracking system. The locations recorded by the RFID system exactly matched the video in 62.5% of the cases, and in 99.2% of the cases when allowing for a deviation of one antenna grid cell. There were moderately strong Spearman rank correlations between the distance recorded with the RFID system and the distance recorded from video (rs = 0.82) and between UWB and RFID (rs = 0.70) in approximately one-hour recordings, indicating that the RFID system can adequately track relative individual broiler activity, i.e., the activity level of a broiler in comparison to its group members. As the RFID tags are small and lightweight, the RFID system is well suited for monitoring the individual activity of group-housed broilers throughout life.

    Review of sensor technologies in animal breeding: Phenotyping behaviors of laying hens to select against feather pecking
    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. - \ 2019
    Animals 9 (2019)3. - ISSN 2076-2615
    -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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