Welfare Assessment: Correspondence Analysis of Welfare Score and Hematological and Biochemical Profiles of Dairy Cows in Sardinia, Italy

SIMPLE SUMMARY: Defining animal welfare definition is still controversial, and a definition is difficult to establish. Furthermore, welfare detection is often complicated and subject to different interpretations. This work aimed to provide valid indicators to evaluate the welfare of dairy cows. The Animal Welfare and Biosecurity Evaluation form (AWB-EF) checklist developed and validated by the Italian National Centre of Reference for Animal Welfare (CReNBA) was submitted to 16 Sardinian dairy cattle farms. Blood samples from the 230 Holstein breed dairy cattle housed in these farms were analyzed for hematological parameters. Correlation analysis revealed a strong association between AWB-EF (considered as gold standard) and laboratory parameters, indicating correspondence between the health and welfare status of the animals. Our study clearly indicates that the use of a validated checklist in combination with the identification of well-known laboratory parameters can be a fundamental tool for veterinarians to detect stress conditions early. ABSTRACT: The need for animal welfare definition and assessment is increasing worldwide, and several studies have been conducted to help fill the knowledge gaps regarding the welfare of cattle. However, further studies are needed to provide valid synthetized measures for welfare evaluation. The aim of this study was to assess the welfare status of 16 Sardinian dairy cattle farms, based on the developed Animal Welfare and Biosecurity Evaluation checklist (AWB-EF) and the corresponding hematological, biochemical, and electrophoretic profiles of these animals. Considering the AWB-EF as gold standard, blood samples were collected from 230 Holstein breed dairy cattle, aged between 3 and 8 years, out of the periparturient period, and with no clinical signs of specific pathologies. Principal Component (PC) and correlation analyses were performed to simplify phenomena interpretation and assess positive/negative associations. Four PCs were able to explain 76% of the total variability, and six laboratory parameters were strongly associated with the AWB-EF score (Spearman’s correlation coefficient ≥ 0.40, p-Value < 0.05), reflecting the real health status of the animals. Given the complexity of animal welfare as a multidimensional concept and the need to include both animal-based and non-based measures in welfare evaluation, the present work represents a sound basis for future evaluation and veterinary health planning.