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Gy sampling theory in environmental studies. 1. Assessing soil splitting protocols
Author(s) -
Gerlach Robert W.,
Dobb David E.,
Raab Gregory A.,
Nocerino John M.
Publication year - 2002
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.705
Subject(s) - riffle , sampling (signal processing) , statistics , mathematics , stratified sampling , confidence interval , sampling theory , sample size determination , computer science , computer network , streams , filter (signal processing) , computer vision
Five soil sample splitting methods (riffle splitting, paper cone riffle splitting, fractional shoveling, coning and quartering, and grab sampling) were evaluated with synthetic samples to verify Pierre Gy sampling theory expectations. Individually prepared samples consisting of layers of sand, NaCl and magnetite were left layered until splitting to simulate stratification from transport or density effects. Riffle splitting performed the best, with approximate 99% confidence levels of less than 2%, followed by paper cone riffle splitting. Coning and quartering and fractional shoveling were associated with significantly higher variability and also took much longer to perform. Common grab sampling was the poorest performer, with approximate 99% confidence levels of 100%–150% and biases of 15%–20%. Method performance rankings were in qualitative agreement with expectations from Gy sampling theory. Precision results depended on the number of increments, the type of increment, and other factors influencing the probability of selecting a particle at random, and were all much higher than Pierre Gy's fundamental error estimate of 1%. A critical factor associated with good performance for these methods is a low conditional probability of sampling adjacent particles. Accuracy levels were dominated by the sampling process rather than by the analytical method. Sampling accuracy was at least two orders of magnitude worse than the accuracy of the analytical method. Published in 2002 by John Wiley & Sons, Ltd.