Welfare Quality^® for dairy cows: towards a sensor-based assessment

Area of Science:

• Animal Welfare Science
• Agricultural Technology
• Data Science

Background:

• Current Welfare Quality® assessments rely on infrequent farm visits.
• This method can be time-consuming, costly, and subjective.
• There is a need for more objective and continuous welfare monitoring.

Purpose of the Study:

• To explore the transition of Welfare Quality® from visit-based to sensor-based data collection.
• To review Precision Livestock Farming (PLF) technologies for welfare monitoring.
• To propose future technological developments and address associated concerns.

Main Methods:

• Review of existing Precision Livestock Farming (PLF) technologies.
• Identification of Welfare Quality® measures assessable by current technologies.
• Proposal of options for developing technologies for currently unassessable measures.
• Discussion of social implications of digitalization in livestock farming.

Main Results:

• Sensor-based data can provide continuous and objective welfare indicators.
• PLF technologies offer potential for cost and time savings in welfare assessment.
• Gaps exist in current PLF technologies for certain Welfare Quality® measures.
• Future systems require multipurpose, non-invasive technologies to avoid over-artificialization.

Conclusions:

• Transitioning to sensor-based Welfare Quality® assessment is feasible and beneficial.
• Further development of non-invasive PLF technologies is crucial for future dairy farms.
• Addressing social concerns related to digitalization is essential for successful implementation.