Abstract

Non-representative sampling of materials, lots and processes intended for NIR analysis is often fraught with hidden contributions to the full Measurement Uncertainty MU_total = TSE + TAE_NIR. The Total Sampling Error (TSE) can dominate over the Total Analytical Error TAE_NIR by factors of 5 to 10 to even 25 times, depending on the degree of material heterogeneity and the specific sampling procedures employed to produce the minuscule aliquot, which is the only material actually analysed. Part 1 presented a brief of all sampling uncertainty elements in the “lot-to-aliquot” pathway, which must be identified and correctly managed (eliminated or reduced maximally), especially the sampling bias, as a prerequisite to achieve fully representative sampling. The key for this is the Theory of Sampling (TOS), which is presented in two parts in a novel compact fashion. Part 2 introduces (i) application of TOS to process sampling, specifically addressing and illustrating how this manifests itself in the realm of PAT, Process Analytical Technology, and (ii) an empirical safeguard facility, termed the Replication Experiment (RE), with which to estimate the effective sampling-plus-analysis uncertainty level (MUtotal) associated with NIR analysis. The RE is a defence against compromising the analytical responsibilities. Ignorance, either caused by lack of awareness or training, or by wilful neglect, of the demand for TSE minimisation, is a breach of due diligence concerning analysis QC/QA. Part 2 ends with a special focus on: “What does all this TOS mean specifically for NIR analysis?”. The answer to this question will perhaps surprise many. There is nothing special that need worrying NIR analysts relative to professionals from all other analytical modalities; all that is needed is embedded in the general TOS framework. Still, this review concludes by answering a set of typical concerns from NIR practitioners.

© 2022 The Author(s)

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