QC of sampling processes- a first overview: from field to test portion

Area of Science:

• Analytical Chemistry
• Environmental Science
• Food Safety

Background:

• Quality control (QC) is crucial for minimizing measurement uncertainty in sampling and analysis.
• Existing QC methods often focus on analysis, neglecting the sampling process.
• Reproducibility and contamination are key sources of error in field-to-analysis pathways.

Purpose of the Study:

• To establish a practical framework for quality control specifically for the sampling process.
• To address error contributions from sampling reproducibility and contamination.
• To provide a systematic approach for estimating and minimizing sampling-related errors.

Main Methods:

• Implementing replication experiments to assess primary sampling and sample processing reproducibility.
• Utilizing a hierarchical or top-down approach for replication experiments.
• Designing QC events to detect and quantify contamination throughout the sampling regimen.
• Calculating the Relative Sampling Variability (RSV) index from replication data.

Main Results:

• Replication experiments provide a quantitative measure (RSV) of total error in the field-to-analysis pathway.
• Contamination can occur at multiple stages and is critical for low-concentration or volatile analytes.
• The framework is applicable to new sampling protocols and materials.

Conclusions:

• A systematic QC framework for sampling is established, integrating reproducibility and contamination assessment.
• This framework enhances the reliability of measurements originating from complex sampling processes.
• The approach is vital for ensuring data integrity in food/feed analysis and protocol development.