[Use of milk haptoglobin concentration as an indicator in animal health monitoring of dairy cows].

Objective: The aim of the present study was to investigate relationships between elevated haptoglobin concentrations in milk and clinical as well as laboratory parameters in early lactating dairy cows. Furthermore, cut-off values should be identified for the differentiation of healthy and affected animals.

Material and methods: 1462 dairy cows between 5.-65. days in milk were examined on 68 Bavarian farms. Milk and blood samples were taken once a week for a 7-week period per farm and body-condition-scoring, backfat thickness measurement and Metricheck examination, to evaluate uterine health, were performed. Milk samples were analysed for milk fat, milk protein, lactose, urea, ß-hydroxybutyrate and non-esterified fatty acids (indirect measurement, based on IR spectra), cell count, and milk haptoglobin. Blood samples were analysed for creatinine, aspartate aminotransferase, gamma-glutamyl transferase, glutamate dehydrogenase, total protein, albumin, creatine kinase, ß-hydroxybutyrate, non-esterified fatty acids, and blood haptoglobin.Cluster analyses were performed to determine cut-off values for haptoglobin.

Results: Besides milk haptoglobin (µg/ml) and blood haptoglobin (µg/ml), cell count (cells/ml milk), milk fat (%), milk protein (%), non-esterified fatty acids in blood (mmol/l), lactation number, days in milk, breed, season, and milk yield (kg) were included as significant input variables (p<0.005) in the cluster analyses. Cluster analysis, using k-means resp. k-prototypes algorithms, resulted in 5 (clusters 1-5 M¹) resp. 4 different clusters (clusters 0-3 M² and 0-3 B).A cut-off value of 0.5 µg/ml haptoglobin in milk was determined for the differentiation of healthy and affected animals.

Conclusion and clinical relevance: As milk is an easily available substrate, routine determination of haptoglobin in milk might be a suitable parameter for animal health monitoring. Using the detected cut-off value, apparently healthy animals with subclinical inflammatory diseases can be identified more quickly.