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After several years of implementation, the original Welfare Quality scoring model for dairy cows appears to be highly sensitive to the number and cleanliness of drinkers and not enough to the prevalence of diseases, and as a consequence may not fit the opinion of some animal welfare experts. The present paper aims to improve the Welfare Quality calculations for the criteria 'Absence of prolonged thirst' and 'Absence of disease' in dairy cows, so that the results are more sensitive to input data and better fit experts' opinion. First, we modified the calculation of 'Absence of prolonged thirst' by linearising the calculation for drinkers' availability to avoid threshold effects. Second, we modified the calculation of 'Absence of disease' by applying a Choquet integral on the three lowest spline-based scores for each health disorder to limit compensation between health disorders. Third, we performed a global sensitivity analysis of the original and the alternative scoring models. Fourth, we compared the results obtained with the original and the alternative models with eight experts' opinions on two subsets composed of 44 and 60 farms, respectively, inspected using the Welfare Quality protocol and on which experts gave their opinion on the overall level of animal welfare. Results show that the alternative model significantly reduced the 'threshold effects' related to the number of drinkers and the compensation between health disorders. On the first subset, the alternative model fits the experts' opinion slightly better than the original model (P = 0.061). On the second subset, the models performed equally. In conclusion, the proposed refinements for calculating scores are validated since they significantly reduced 'threshold effects' and the influence of measures related to drinkers. It also reduced the compensation between health disorders by considering only the three lowest scores and thus increasing the influence of measures related to health disorders, and slightly improve at overall score level the accordance with experts' opinion., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

The Welfare Quality® consortium has developed and proposed standard protocols for monitoring farm animal welfare. The uptake of the dairy cattle protocol has been below expectation, however, and it has been criticized for the variable quality of the welfare measures and for a limited number of measures having a disproportionally large effect on the integrated welfare categorization. Aiming for a wide uptake by the milk industry, we revised and simplified the Welfare Quality® protocol into a user-friendly tool for cost- and time-efficient on-farm monitoring of dairy cattle welfare with a minimal number of key animal-based measures that are aggregated into a continuous (and thus discriminative) welfare index (WI). The inevitable subjective decisions were based upon expert opinion, as considerable expertise about cattle welfare issues and about the interpretation, importance, and validity of the welfare measures was deemed essential. The WI is calculated as the sum of the severity score (i.e., how severely a welfare problem affects cow welfare) multiplied with the herd prevalence for each measure. The selection of measures (lameness, leanness, mortality, hairless patches, lesions/swellings, somatic cell count) and their severity scores were based on expert surveys (14-17 trained users of the Welfare Quality® cattle protocol). The prevalence of these welfare measures was assessed in 491 European herds. Experts allocated a welfare score (from 0 to 100) to 12 focus herds for which the prevalence of each welfare measure was benchmarked against all 491 herds. Quadratic models indicated a high correspondence between these subjective scores and the WI ( R 2 = 0.91). The WI allows both numerical (0-100) as a qualitative ("not classified" to "excellent") evaluation of welfare. Although it is sensitive to those welfare issues that most adversely affect cattle welfare (as identified by EFSA), the WI should be accompanied with a disclaimer that lists adverse or favorable effects that cannot be detected adequately by the current selection of measures., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Tuyttens, de Graaf, Andreasen, de Boyer des Roches, van Eerdenburg, Haskell, Kirchner, Mounier, Kjosevski, Bijttebier, Lauwers, Verbeke and Ampe.)