From Sampling to Analysis: How to Achieve the Best Sample Throughput via Sampling Optimization and Relevant Compound...

Area of Science:

• Analytical Chemistry
• Food Science
• Statistics

Background:

• Optimizing volatile sampling is crucial in analytical chemistry for accurate sample analysis.
• Traditional methods for determining optimal sampling procedures can be time-consuming and inefficient.

Purpose of the Study:

• To introduce and evaluate a novel non-parametric statistical method, the sum of ranking differences (SRD), for determining optimal volatile sampling procedures.
• To compare the efficiency of different adsorbents and sampling times for volatile collection from lettuce (Lactuca sativa).

Main Methods:

• Application of the sum of ranking differences (SRD) statistical method.
• Volatile collection from lettuce samples using three adsorbents: Porapak Q, HayeSep Q, and Carbotrap.
• Evaluation of four sampling times: 1, 2, 4, and 6 hours.

Main Results:

• The SRD method identified 6-hour sampling as the optimal procedure for volatile collection.
• Shorter sampling times (1 or 4 h with HayeSep Q; 2 h with Carbotrap) were found to be sufficiently efficient, offering a trade-off between time and optimization.
• SRD significantly decreased the evaluation time for determining optimal sampling conditions.

Conclusions:

• The sum of ranking differences (SRD) is a novel and efficient statistical tool for optimizing volatile sampling procedures in analytical chemistry.
• SRD facilitates quicker identification of optimal sampling parameters, reducing experimental evaluation time.
• The study provides practical insights into efficient volatile sampling strategies for lettuce analysis.