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    Network analysis of free-range egg laying hens movements obtained using RFID sensors (2021)

    Art
    Poster
    Autoren
    Belik, Vitaly (WE 16)
    Jarynowski, Andrzej (WE 16)
    Boshoff, Johann
    Schneider, Derek
    Sibanda, Terence
    Ruhnke, Isabelle (WE 15)
    Kongress
    27. DACH-Epidemiologietagung
    Bern, Schweiz, 01. – 03.09.2021
    Quelle
    27. DACH-Epidemiologietagung „Epidemiologie in der ökologischen Landwirtschaft“ : Gemeinsame Tagung des Forums für Epidemiologie und Tiergesundheit Schweiz der DVG-Fachgruppe „Epidemiologie und Dokumentation“ Institut für Öffentliches Veterinärwesen der Vetmeduni Wien in Verbindung mit der Vetsuisse Fakultät der Universität Bern : 1. bis 3. September 2021 — Wissenschaftliche Tagungsleitung: Ass. Prof. Salome Dürr, Prof. Gertraud Schüpbach, Veterinary Public Health Institut (Hrsg.)
    Bern: Veterinary Public Health Institut, 2021 — S. 66
    Sprache
    Englisch
    Verweise
    URL (Volltext): http://dachepi.vphibern.ch/wp-content/uploads/2021/08/Tagungsband_DACH-Epidemiologietagung2021.pdf
    Kontakt
    Institut für Veterinär-Epidemiologie und Biometrie

    Königsweg 67
    14163 Berlin
    +49 30 838 56034
    epi@vetmed.fu-berlin.de

    Abstract / Zusammenfassung

    RFID sensors is a promising technology for wellfare and health conditions assessment in the egg production industry. We analyse the dataset on free-range hens movements in Australia from 18 000 commercial laying hens using a highly innovative custom-built RFID system, which allowed to trace individual hen movements on the range and in the hen house for the entire 56 week duration of the laying period. Based on the data, we construct the
    corresponding individual mobility networks with nodes being locations and links being movements between them. We investigate the resulting networks in terms of degree distribution and higher order correlation structures, such as clustering coefficient, motifs, communities and centrality measures. We also correlate the obtained network measures with activity patterns and health characteristics of the hens. Our study demonstrates that health and performance indicators enriched with the network analysis promise to improve the hens well-being as well as to allow targeted interventions and optimise economical efficiency of the egg production industry.