Detection and correction of biased results of individual analytes in multicomponent spectroscopic analysis
1Departament de Química Analítica, Universitat Rovira i Virgili, Pl. Imperial Tarraco, 1, 43005-Tarragona, Spain.
Abstract:
Simultaneous spectroscopic multicomponent analysis based on Beer's law requires the test sample to follow the hard model, independently of whether this model is built with the full spectrum or only with a few sensors selected according to an optimality criterion. We have developed a graphical method based on the net analytical signal concept to detect bias in the predicted results of individual analytes in test samples. When an interference, or other causes which produce bias, are detected, a moving window approach is used to select the subset of sensors that minimize the bias of the predicted results. The method has been validated with UV-vis spectra of binary clorophenol mixtures and of mixtures of four pesticides in water analyzed with a FIA system with diode array detection.
Related Concept Videos
Atomic Absorption Spectroscopy: Interference
Spectral interference occurs when signals from other elements or molecules overlap with the analyte signal, falsely elevating or masking the analyte's absorbance. This interference can be corrected using Zeeman,...
Inductively Coupled Plasma-Mass Spectrometry (ICP-MS): Interferences
Mass Spectrometry: Complex Analysis
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
Tandem Mass Spectrometry
MALDI-TOF Mass Spectrometry
Mass Analyzers: Overview


