Hair Cortisol Concentration of Dairy Cattle is Unrelated to Automation Level of Dairy Farms – However It Can Reflect Welfare QualityÒ Measures

Lianne Lavrijsen-Kromwijk^1*Ute Müller²Susanne Demba³Ulrike Gimsa⁴Sandra Rose³

• ¹Department of Agricultural Machinery, Hochschule Neubrandenburg, Neubrandenburg, Germany
• ²Institute of Animal Science, Rheinische Friedrich-Wilhelms-Universitat Bonn, Bonn, Germany
• ³Department of Agricultural Process Engineering, Universitat Rostock, Rostock, Germany
• ⁴Psychophysiology Working Group, Forschungsinstitut fur Nutztierbiologie (FBN), Dummerstorf, Germany

Introduction of precision dairy farming has led to increasing automation of core tasks in dairy farming. However, impact of these technologies on animal welfare remains subject of ongoing debate. A previous study using the Welfare Quality ® (WQ) Assessment protocol to examine the impact of dairy farm automation on cattle welfare found an effect on animals’ behavior. While the WQ protocol is widely used to evaluate dairy cattle welfare, it is often criticized for subjectivity. Thus, more objective indicators are demanded. Concurrently, hair cortisol concentration (HCC) has emerged as a promising objective indicator of long-term stress in animals, offering a potential indirect welfare indicator. Thus, the present study aimed to investigate the relationship between farm automation levels and dairy cattle welfare, using HCC as a biomarker of animal stress. Furthermore, associations between HCC, and WQ indicators are examined. Therefore, German farms (n = 32) were categorized into three automation levels based on a newly developed classification system. On each farm welfare assessment was performed using the WQ protocol, and hair samples were collected from 15 cows to determine HCCs. Median HCC values were compared across automation levels using the non-parametric Kruskal-Wallis test. Associations between HCC, and WQ indicators were examined using multiple linear regression analysis. A trend of lower HCC levels with increasing automation was observed. Even so, the differences were not statistically significant, likely due to substantial variabilities in housing, management, and settings of automatic systems such as individual milking intervals or frequencies of feeding, bedding etc. among farms. Significant correlations were found between median HCC per farm and the WQ protocol indicators “percentage of moderately lame cows”, “cows with at least one hairless patch and no lesion”, “tendency to be apathetic”, and “absence of injuries”. However, these indicators are not recommended as standalone measures of welfare. Nevertheless, consistent with the existing literature, our findings support lameness and integument alterations as key indicators of poor welfare in dairy cattle, which was also reflected in elevated HCC levels. As the number of highly automated farms is expected to increase in upcoming years, future studies with larger sample sizes are recommended.