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Gewählte Publikation:

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Publikationstyp: Zeitschriftenaufsatz
Dokumenttyp: Originalarbeit

Jahr: 2020

AutorInnen: Sturm, V; Efrosinin, D; Öhlschuster, M; Gusterer, E; Drillich, M; Iwersen, M

Titel: Combination of sensor data and health monitoring for early detection of subclinical Ketosis in dairy cows.

Quelle: Sensors (Basel). 2020; 20(5):1484



Autor/innen der Vetmeduni Vienna:

Drillich Marc
Gusterer Erika
Iwersen Michael

Beteiligte Vetmed-Organisationseinheiten
Universitätsklinik für Wiederkäuer, Bestandsbetreuung bei Wiederkäuern


Zugehörige(s) Projekt(e): Prozessbezogenes Informationsmanagement in Precision Dairy Farming


Abstract:
Subclinical ketosis is a metabolic disease in early lactation. It contributes to economic losses because of reduced milk yield and may promote the development of secondary diseases. Thus, an early detection seems desirable as it enables the farmer to initiate countermeasures. To support early detection, we examine different types of data recordings and use them to build a flexible algorithm that predicts the occurence of subclinical ketosis. This approach shows promising results and can be seen as a step toward automatic health monitoring in farm animals.


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