Fit-for-purpose validation of hair cortisol concentration as a biomarker of dairy cow welfare

Abstract

In recent years, measuring hair cortisol concentration in dairy cows has gained popularity as a welfare indicator. The aim of this study was to evaluate the usefulness of measuring hair cortisol concentration (HCC) in dairy cows as an indicator of dairy cow welfare. A total of 290 cows from six commercial herds located in Spain, Italy and Finland (two herds each) were included in the study. A hair sample was taken from each cow and cut into two parts (study period T1 and T2). HCC was measured using an automated assay based on a competitive solid phase chemiluminescent enzyme immunoassay. Data relevant to each animal and its welfare (animal-based assessment according to the Welfare Quality protocol, veterinary treatments, meteorological data, cows’ parity and stage of lactation) were collected during the study. The welfare data were used to categorize cows into three welfare classes at each study period (T1 and T2), representing animals with good, medium and poor welfare. Analytical validation of the HCC automated assay was performed on a sub-sample of collected hair and included determination of accuracy, precision, sensitivity and stability of the method. A linear mixed model was fitted to explore the associations between log transferred HCC and welfare class, herd, stage of lactation, parity and season. The results of analytical validation showed that the HCC automated assay method was accurate and able to measure HCC in a linear manner with inter- and intra-assay precision with CVs less than 15%. HCC was explained by the variables herd, cow parity and study period (T1 or T2). We found no evidence that lactation stage and welfare class explained HCC at the individual animal level. This study highlights the challenges of using HCC as an indicator of animal welfare on commercial farms.