Using registry data to identify individual dairy cows with abnormal patterns in routinely recorded somatic cell counts

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt


Data from the Danish milk recording system routinely enter the Danish Cattle Database, including somatic cell counts (SCC) for individual animals. Elevated SCC can signal intramammary inflammation, suggesting subclinical mastitis. Detecting mastitis is pivotal to limit severity, prevent pathogen spread, and target treatment or culling. This study aimed to differentiate normal and abnormal SCC patterns using recorded registry data. We used registry data from 2010 to 2020 for dairy cows in herds with 11 annual milk recordings. To create consistency across herds, we used data from 13,996 unique animals and eight different herds, selected based on the amount of data available, only selecting Holstein animals and conventional herds. We fitted log10-transformed SCC to days in milk (DIM) using the Wilmink and Wood's curve functions, originally developed for milk yield over the lactation. We used Nonlinear Least Square and Nonlinear Mixed Effect models to fit the log10-transformed SCC observations to DIM at animal level. Using mean squared residuals (MSR), we found a consistently better fit using a Wood's style function. Detection of MSR outliers in the model fitting process was used to identify animals with log10(SCC) curves deviating from the expected “normal” curve for that same animal. With this study, we propose a method to identify single animals with SCC patterns that indicate abnormalities, such as mastitis, based on registry data. This method could potentially lead to a registry data-based detection of mastitis cases in larger dairy herds.

TidsskriftJournal of Theoretical Biology
Sider (fra-til)1-7
Antal sider7
StatusUdgivet - 21 feb. 2024

Bibliografisk note

Funding Information:
The authors would like to thank SEGES for have given access to the Danish Cattle Database. The Danish Veterinary and Food Administration (FVST, Glostrup, Denmark) funded this project but did not take part of the planning and conduct of the project.

Publisher Copyright:
© 2023 The Author(s)

Antal downloads er baseret på statistik fra Google Scholar og

Ingen data tilgængelig

ID: 380649011