UBC Theses and Dissertations
Behavioural changes associated with early identification of disease in dairy cows Sahar, Mohammad
Lameness and transition cow disease are important welfare issues associated with dairy farming. The aim of this thesis was to develop models and assess their predictive ability for the early identification of cows at increased risk of becoming sick or lame, using behavioural and milk production data. The first aim of my thesis was to investigate whether the association between feeding and agonistic behaviours and postpartum disease using data collected from commercial farms could be used to build predictive models for early identification of cows at risk of becoming sick. Another aim of this thesis was to develop predictive models of cows at risk for lameness based on longitudinal measures of feeding and agonistic behaviour. In Chapter 1, I conducted a literature review on previous research. In Chapter 2, I tested the association of feeding and agonistic behaviours and transition disease on commercial farms; my findings confirm the presence of these associations. In Chapter 3, I used prepartum behaviours to build predictive models for disease postpartum; the resulting models were successful in identifying cows at increased risk of becoming sick. In Chapter 4, I conducted a longitudinal study on lameness and report greater prevalence of lameness compared to a one-time prevalence assessment, suggesting that the dairy industry, which has relied predominantly on prevalence estimates, may in fact be underestimating the extent of this malady. Whilst cows in all parities experience lameness, older cows struggle more than younger cows to recover once lame, and the longer they remain lame, the higher the probability that they will continue to remain lame. In Chapter 5, I combined milk production data with the feeding and agonistic behaviours to build predictive models for lameness; the resulting model successfully identified lame cows at earlier stages of lameness. In conclusion, predictive models developed using behavioural data and milk production can identify cows at higher risk of becoming sick or lame.
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