Document type: systematic review of the literature, published in Italian Journal of Animal Science
Authors: Luisa Magrin, Barbara Contiero, Giulio Cozzi, Flaviana Gottardo, Severino Segato
Preview: Lameness is a widespread multifactorial condition affecting the health and performance of dairy cows. Despite the growing support by precision farming technologies, farmers still lack reliable data-driven tools to early identify lame cows. This study used a synthesis of reviews to identify cow's behavioural and productive parameters most related to lameness and estimate their deviation due to a lameness event. The methodological approach used reviews as starting point to identify the most pertinent studies with the intention of extracting and analysing data from these primary studies. The final dataset used information collected from 31 research papers, cited in 15 reviews, and involved more than 25,000 dairy cows. Five parameters were suitable for the meta-analysis: one about eating behaviour (eating time), three regarding activity and resting behaviour (lying bouts, lying bout duration and lying time) and milk yield. The meta-analysis revealed that all parameters had a significant deviation in cows affected by lameness. The calculation of the pooled means allowed to quantify a mean value for the deviation imposed by a severe lameness event from the value recorded on nonlame cows. Compared to a nonlame animal, a lame cow had a significant negative deviation for eating time (-39 min/day), number of lying bouts (-0.5/day), and milk yield (-3 kg/day). Lame cows had positive deviations for lying bout duration (+12 min/bout) and daily lying time (+42 min/day). The individual or combined use of these mean deviation values as alarm reference thresholds could improve the accuracy of the current automated lameness detection systems.
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