ArticleScientific reports2025
Diurnality is consistently different between individuals and decreases with disease or stressful events in dairy calves.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Long-term repeatability and predictability of body temperature in dairy calves explored using reticulorumen temperature boluses.Scientific reports · 2026Article
- Environmental enrichment reduces displacements and reorganises circadian patterns: a putative indicator of positive welfare in dairy calves.Frontiers in veterinary science · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
Changes in behavioural rhythms of livestock can be useful indicators of disease or stress before visible signs appear. Using precision livestock technologies, it is possible to measure behavioural patterns and compute the diurnality, determined by proportion of activity that happens during the daytime. Accounting for individual variation in behaviour due to personality or predictability differences is an essential step for the early detection of disease or stress. Here we aimed to detect individual differences and changes in daily rhythms. We use ultra-wideband location sensors to measure the diurnality of 285 calves across the weaning period and two housings. Calves were shown for the first time to have consistent individual differences in diurnality (the repeatability was 0.29 and 0.39 in each housing) and to differ in their predictability (CVp = 0.15 and CVp = 0.28 in each housing). This was the first time that a decrease in diurnality was detected when calves were experiencing disease or the stress of disbudding, as the diurnality index decreased by 0.07 and 0.45 respectively. Diurnality increased with age and decreased during weaning and in the summer months. These results highlight the importance of studying individual variation and daily rhythms of activity for the development of automated disease detection tools.
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