Sequential sampling: a novel method in farm animal welfare assessment.

Area of Science:

• Animal Welfare Science
• Veterinary Epidemiology
• Statistical Modeling

Background:

• Lameness in dairy cows is a significant animal welfare concern.
• Accurate estimation of herd lameness prevalence is crucial for welfare assessment.
• Current fixed-size sampling methods can be resource-intensive.

Purpose of the Study:

• To develop and evaluate novel sequential sampling schemes for dairy cow lameness.
• To reduce the average sample size required for accurate herd-level lameness classification.
• To compare the performance of new schemes against the established Welfare Quality sampling method.

Main Methods:

• Development of three sequential sampling schemes with increasing complexity.
• Simulation of 100,000 trials for each scheme using data from 80 UK dairy farms.
• Evaluation based on accuracy and average sample size compared to a fixed-size scheme.

Main Results:

• All developed sequential schemes achieved accuracy comparable to the fixed-size Welfare Quality scheme.
• The sequential schemes demonstrated significantly smaller average sample sizes.
• The 'cautious' scheme was identified as the preferred method due to its balance of accuracy and sample size.

Conclusions:

• Sequential sampling offers an efficient alternative for assessing dairy cow lameness prevalence.
• The 'cautious' sequential sampling scheme provides a reliable and resource-efficient approach for welfare assessment.
• Further development is needed to consistently utilize severity of lameness in sampling schemes.