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The relationship between common data-based indicators and the welfare of Swiss dairy herds

Barbara Lutz, Barbara Lutz, Sibylle Zwygart and 3 more

Frontiers in Veterinary Science · 2022

doi:10.3389/fvets.2022.991363 (opens in a new tab)

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Abstract

The assessment of dairy cow welfare has become increasingly important in recent years. Welfare assessments that use animal-based indicators, which are considered the most direct indicators, are time consuming and therefore not feasible for assessments on a large number of farms. One approach to reducing this effort is the use of data-based indicators (DBIs) calculated from routine herd data. The aim of this study was to explore the relationship between common DBIs and the welfare of 35 dairy herds to evaluate the feasibility of a data-based welfare prediction method. For this purpose, the WelfareQuality® (WQ) protocol was used to assess the welfare of dairy cows on 35 Swiss farms, for each of which 10 commonly used DBIs were calculated from herd data. Spearman's rank correlations were used to investigate the relationship between DBIs and WQ criteria and measurements. The study found only a few statistically weak associations between DBIs and animal welfare, with no associations for measurements or criteria of resting comfort and appropriate behavior. Thus, the multidimensional welfare definition is insufficiently covered, and the present publication does not support the approach of a purely data-based prediction of dairy welfare status at the farm level. Instead, the regular calculation of DBIs that are indicative of isolated animal welfare problems or metrics of animal health could allow monitoring of these specific areas of animal welfare.

Abstract licence: CC BY

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