Effect of Sample Complexity on Quantification of Analytes in Aqueous Samples by Near-Infrared Spectroscopy

Authors

Mark R. Riley, University of Nebraska-LincolnFollow
Mark A. Arnold, University of Iowa, Iowa City, IowaFollow
David W. Murhammer, University of Iowa, Iowa City, IowaFollow

Date of this Version

2000

Citation

APPLIED SPECTROSCOPY Volume 54, Number 2, 2000

Comments

Copyright 2000 Society for Applied Spectroscopy

Abstract

This study was undertaken to quantitate the impact of increasing sample complexity on near-infrared spectroscopic (NIRS) measurements of small molecules in aqueous solutions with varying numbers of components. Samples with 2, 6, or 10 varying components were investigated. Within the 10-component samples, three analytes were quantified with errors below 6% and seven of the analytes were quantified with errors below 10%. An increase in the number of varying components can substantially increase the error associated with measurement. A comparison of measurement errors across sample sets, as gauged by the standard error of prediction (SEP), reveals that an increase in the number of varying components from 2 to 6 increases the SEP by approximately 50%. An increase from 2 to 10 varying components increases the SEP by approximately 340%. While there appear to be no substantial correlations between the presence of a specific analyte and the errors associated with quantification of another analyte, several analytes do display a small degree of sensitivity to varying concentrations of certain background components. The analysis also demonstrates that calibrations containing an overestimation of the numbers of varying components can substantially increase measurement errors and so calibrations must be constructed with an accurate understanding of the number of varying components that are likely to be encountered.