Bias in composite milk samples with unequal milking intervals

Area of Science:

• Dairy Science
• Animal Science
• Analytical Chemistry

Background:

• Accurate milk component analysis is crucial for dairy herd management and economic evaluation.
• Composite milk sampling is a common practice, but potential biases in measurement accuracy exist.
• Variations in milking intervals can influence the representativeness of composite samples.

Purpose of the Study:

• To investigate the potential bias in milk component measurements using composite sampling.
• To compare the accuracy of different composite sampling strategies, including equal portions and milking-interval-based portions.
• To evaluate the impact of sampling methods on fat percentage, protein percentage, and somatic cell count (SCC) measurements.

Main Methods:

• Milk samples from six consecutive milkings were collected and individually weighed and sampled.
• Composite samples were mathematically derived from individual milking data.
• Different composite sampling strategies were applied: equal portions (a.m./p.m.), milking interval portions, DHIA alternate component sampling, and DHIA alternate a.m./p.m. sampling.

Main Results:

• Equal portion composite samples overestimated daily fat percentage by 0.07%.
• Using milking intervals to proportion samples reduced fat percentage bias to -0.02%.
• Protein percentage and SCC measurements showed minimal bias with equal sampling, but were slightly improved with milking interval sampling.

Conclusions:

• Composite milk sampling with equal portions from a.m. and p.m. milkings introduces bias in fat percentage measurements.
• Adjusting sample proportions based on milking intervals significantly reduces bias for fat percentage, protein percentage, and SCC.
• Milking interval-based sampling offers improved accuracy for fat yield determination compared to other DHIA plans, although variations can be greater.