Sampling and Sample Preparation

Sampling and sample preparation obtain a representative portion of a material and convert it to a form suitable for measurement, often the largest sources of analytical error.

Definition

Sampling and sample preparation are the analytical operations that secure a representative sample of a material and transform it into a measurable form, controlling the errors these steps introduce.

Scope

This topic covers the steps that precede measurement: designing a sampling plan, taking and reducing a gross sample to a laboratory and test portion, and preparing it by dissolution, digestion, extraction, clean-up, and preconcentration. It treats sampling statistics and the sampling constant, common preparation techniques such as liquid–liquid and solid-phase extraction, and the control of contamination and analyte loss.

Core questions

• How is a sampling plan designed so the sample represents the whole material?
• How does sampling variance relate to sample size and heterogeneity?
• Which preparation techniques convert a sample to a measurable form without loss or contamination?
• Why do sampling and preparation often dominate total analytical uncertainty?

Key theories

Sampling statistics

The uncertainty contributed by sampling depends on the heterogeneity of the material and the amount taken; sampling theory relates the number and size of increments to the achievable sampling variance, guiding plans that make the sample statistically representative.

Mechanisms

A sampling plan specifies how many increments to take and from where, so that the gross sample reflects the bulk material; the gross sample is then reduced to a homogeneous laboratory sample and a test portion. Preparation converts that portion into a measurable form: dissolving or digesting solids, extracting analytes from matrices, cleaning up interferences, and sometimes preconcentrating trace analytes. Throughout, contamination and analyte loss are controlled because errors here propagate directly into the final result.

Clinical relevance

Sound sampling and preparation are decisive in environmental monitoring, where heterogeneous materials make sampling the largest error source, and in clinical, food, and forensic analysis, where extraction and clean-up determine whether trace analytes can be measured reliably.

History

The theory of sampling heterogeneous materials was placed on a quantitative footing by Pierre Gy in the mid-20th century, while analytical chemists developed an expanding toolkit of preparation methods—from classical digestion and liquid–liquid extraction to solid-phase and microextraction—to handle ever more demanding trace and complex-matrix analyses.

Key figures

• Pierre Gy
• Walter J. Youden

Seminal works

• skoog2014fac
• harris2020
• miller2018

Frequently asked questions

Why can sampling be the biggest source of error?

If a material is heterogeneous, the small portion analyzed may not match the whole, so even a flawless measurement gives a wrong answer for the bulk; careful sampling plans are needed to keep this error acceptably small.

What is the purpose of sample preparation?

It converts the sample into a form the method can measure—dissolving solids, extracting and concentrating analytes, and removing interfering substances—while avoiding contamination or loss of the analyte.