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Updated: Jun 19, 2026
07:11
Sampling Soils in a Heterogeneous Research Plot
Published on: January 7, 2019
Grab vs. composite sampling of particulate materials with significant spatial heterogeneity--a simulation study of
Pentti O Minkkinen1, Kim H Esbensen
1ACABS Research Group, Aalborg University, Campus Esbjerg, Niels Bohrs Vej 8, DK-6700, Denmark (AAUE), Finland. Pentti.Minkkinen@lut.fi
Analytica Chimica Acta
|October 6, 2009
Summary
Correct sampling errors stem from material heterogeneity and sampling process factors. Understanding these five key factors is crucial for minimizing total sampling error in diverse scientific and industrial applications.
Area of Science:
- Analytical Chemistry
- Materials Science
- Statistical Modeling
Background:
- Sampling errors are broadly categorized into incorrect and correct sampling errors.
- Correct sampling errors originate from material heterogeneity and sampling process characteristics.
- Existing research has not comprehensively detailed the combined effects of factors influencing sampling variance.
Purpose of the Study:
- To illustrate the combined effects of five dominant factors on sampling variance.
- To provide a detailed analysis of correct sampling errors within the Theory of Sampling framework.
- To present a new simulation facility, SIMSAMP, for analyzing sampling processes.
Main Methods:
- Simulations based on an experimental design varying material heterogeneity (analyte concentration, distributional heterogeneity) and sampling process factors (sample type, sample size, sampling modus).
- Utilizing the SIMSAMP simulation facility to model repeated samplings and analyze total sampling error.
- Expressing effects through lot mean estimates and Root Mean Squared Errors/sampling variances.
Main Results:
- Demonstrated significant interactions between material heterogeneity and sampling process factors.
- Quantified absolute and relative sampling variance levels across various simulated scenarios.
- Illustrated the impact of these factors on lot mean estimates and associated errors.
Conclusions:
- Correct sampling errors are influenced by material heterogeneity and sampling process design.
- The interplay of these factors is critical for accurate non-bias sampling.
- The SIMSAMP facility offers a versatile tool for understanding and mitigating sampling errors in various fields.
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