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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Record number 508936
Title Eindrapportage Veerkracht van Melkvee I : verandering van dynamiek, voorspellende kracht
Author(s) Dixhoorn, Ingrid van; Mol, Rudi de; Werf, Joop van der; Reenen, Kees van
Source Wageningen : Wageningen UR Livestock Research (Livestock Research rapport 956) - 94
Department(s) LR - Animal Behaviour & Welfare
WIAS
Publication type Research report
Publication year 2016
Keyword(s) melkkoeien - melkvee - gustperiode - lactatie - rundveeziekten - diergezondheid - diergedrag - dierfysiologie - gegevens verzamelen - voorspelling - rundveeteelt - dairy cows - dairy cattle - dry period - lactation - cattle diseases - animal health - animal behaviour - animal physiology - data collection - prediction - cattle farming
Categories Cattle / Animal Health and Welfare
Abstract The transition period is a critical phase in the life of dairy cows. Early identification of cows at risk for disease would allow for early intervention and optimization of the transition period. Based on the theory of resilience of biological systems we hypothesize that the level of vulnerability of an individual cow can be quantified by describing dynamical aspects of continuously measured physiological and behavioural variables. To examine the relationship between the risk to develop diseases early in lactation and dynamic patterns of high-resolution, physiological and behavioural data, were continuously recorded in individual cows before calving. Dynamic, quantitative parameters for high-resolution physiological and behavioural measures, continuously acquired during the dry period have predictive value for the risk of cows to develop diseases during the early lactation period. Our results suggest that quantitative parameters derived from sensor data may reflect the level of resilience of individual cows.
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