J Dairy Sci. 2025 Oct 30:S0022-0302(25)00894-X. doi: 10.3168/jds.2025-27382. Online ahead of print.
ABSTRACT
Consumer demand for animal welfare is rising, leading to the use of welfare labels that emphasize enhanced conditions for farm animals. However, on the farmers' side, complying with these standards often requires extensive and burdensome documentation. Precision livestock farming (PLF) technologies can simplify the collection of animal welfare data, such as health, behavior, and environmental conditions, thus reducing the documentation burden and enhancing transparency. To investigate current practices in animal welfare data collection on dairy farms and evaluate farmers' willingness to share this data with relevant institutions, a survey among 269 dairy farmers in Germany was conducted between June and September 2024. Partial least squares structural equation modeling (PLS-SEqM) was applied. Trust in data security and clear on-farm benefits-such as time savings and reduced documentation workload-emerge as the strongest drivers, whereas perceived consumer benefits and social pressure play minor roles. Farmers are more inclined to share productivity and housing data, whereas health and behavioral data are probably perceived as more sensitive and thus less likely to be shared. Furthermore, farmers prefer private schemes over public authorities. These insights suggest that transparent data-governance rules and demonstrable farm-level advantages are pivotal levers for unlocking PLF data flows. Embedding such enabling conditions in animal welfare programs could streamline documentation, cut audit costs, increase farmer participation, strengthen consumer confidence in animal welfare labels, and provide guidance for policy and program design.
PMID:41176269 | DOI:10.3168/jds.2025-27382