Early detection of subclinical ketosis and clinical diseases in dairy cows using peripartum motion activity

Ahrens, Charlotte; Martin, Rainer; Zablotski, Yury und Zerbe, Holm (2025): Early detection of subclinical ketosis and clinical diseases in dairy cows using peripartum motion activity. In: Preventive Veterinary Medicine, Bd. 242, 106574

Abstract

Early detection of metabolic diseases like subclinical ketosis (SCK) and other disorders is crucial for animal welfare and economic efficiency. Automated monitoring systems become increasingly important here. This study examined motion activity of cows around calving and its suitability for early detection of SCK and clinical disorders. Activity data of 136 cows were collected over two weeks before to three weeks after calving and analyzed alongside blood test results for beta-hydroxybutyric acid (BHBA). Cows were categorized as clinically sick (S) or healthy (H), with group H further subdivided into group SCK (at least one BHBA result ≥ 1.2 mmol/L) and group non-SCK (BHBA consistently < 1.2 mmol/L). Antepartum, activity levels hardly differed between groups. Postpartum, groups H and non-SCK were significantly more active than groups S and SCK, respectively (mixed effects regression; estimated mean difference of 11.37, 95 % CI (Confidence Interval) [5.847, 16.9], P = 0.0001 for H vs. S, and estimated mean difference of 7.90, 95 % CI [0.544, 15.25], P = 0.0353 for non-SCK vs. SCK). Comparing antepartum and postpartum activity, a significant increase was observed only in groups H and non-SCK (mixed effects regression; estimated mean difference of –8.46, 95 % CI [–10.60, –6.327], P < 0.0001 and estimated mean difference of –12.35, 95 % CI [–15.18, –9.52], P < 0.0001, respectively). A lack of postpartum activity increase could serve as early warning indicator for cows at risk of disease and, with the development of animal-specific thresholds, may be integrated into automated monitoring systems.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Tiermedizin > Zentrum für Klinische Tiermedizin
• Themengebiete: 500 Naturwissenschaften und Mathematik > 590 Tiere (Zoologie)
• ISSN: 01675877
• Sprache: Englisch