A new IUPAC-consistent approach to the limit of detection in partial least-squares calibration
There is currently no well-defined procedure for providing the limit of detection (LOD) in multivariate calibration. Defining an estimator for the LOD in this scenario has shown to be more complex than intuitively extending the traditional univariate definition. For these reasons, although many a...
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Autores principales: | , |
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Lenguaje: | Inglés |
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American Chemical Society
2018
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Acceso en línea: | http://hdl.handle.net/2133/10469 http://hdl.handle.net/2133/10469 |
Aporte de: |
id |
I15-R121-2133-10469 |
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record_format |
dspace |
institution |
Universidad Nacional de Rosario |
institution_str |
I-15 |
repository_str |
R-121 |
collection |
Repositorio Hipermedial de la Universidad Nacional de Rosario (UNR) |
language |
Inglés |
orig_language_str_mv |
eng |
topic |
Espectroscopía Cromatografía Quimiometría Química Analítica Calibration Least-Squares Analysis Limit of Detection |
spellingShingle |
Espectroscopía Cromatografía Quimiometría Química Analítica Calibration Least-Squares Analysis Limit of Detection Allegrini, Franco Olivieri, Alejandro César A new IUPAC-consistent approach to the limit of detection in partial least-squares calibration |
topic_facet |
Espectroscopía Cromatografía Quimiometría Química Analítica Calibration Least-Squares Analysis Limit of Detection |
description |
There is currently no well-defined procedure for providing the limit of
detection (LOD) in multivariate calibration. Defining an estimator for the LOD in this
scenario has shown to be more complex than intuitively extending the traditional
univariate definition. For these reasons, although many attempts have been made to
arrive at a reasonable convention, additional effort is required to achieve full agreement
between the univariate and multivariate LOD definitions. In this work, a novel approach
is presented to estimate the LOD in partial least-squares (PLS) calibration. Instead of a
single LOD value, an interval of LODs is provided, which depends on the variation of
the background composition in the calibration space. This is in contrast with previously
proposed univariate extensions of the LOD concept. With the present definition, the
LOD interval becomes a parameter characterizing the overall PLS calibration model,
and not each test sample in particular, as has been proposed in the past. The new
approach takes into account IUPAC official recommendations, and also the latest
developments in error-in-variables theory for PLS calibration. Both simulated and real
analytical systems have been studied for illustrating the properties of the new LOD
concept. |
author |
Allegrini, Franco Olivieri, Alejandro César |
author_facet |
Allegrini, Franco Olivieri, Alejandro César |
author_sort |
Allegrini, Franco |
title |
A new IUPAC-consistent approach to the limit of detection in partial least-squares calibration |
title_short |
A new IUPAC-consistent approach to the limit of detection in partial least-squares calibration |
title_full |
A new IUPAC-consistent approach to the limit of detection in partial least-squares calibration |
title_fullStr |
A new IUPAC-consistent approach to the limit of detection in partial least-squares calibration |
title_full_unstemmed |
A new IUPAC-consistent approach to the limit of detection in partial least-squares calibration |
title_sort |
new iupac-consistent approach to the limit of detection in partial least-squares calibration |
publisher |
American Chemical Society |
publishDate |
2018 |
url |
http://hdl.handle.net/2133/10469 http://hdl.handle.net/2133/10469 |
work_keys_str_mv |
AT allegrinifranco anewiupacconsistentapproachtothelimitofdetectioninpartialleastsquarescalibration AT olivierialejandrocesar anewiupacconsistentapproachtothelimitofdetectioninpartialleastsquarescalibration AT allegrinifranco newiupacconsistentapproachtothelimitofdetectioninpartialleastsquarescalibration AT olivierialejandrocesar newiupacconsistentapproachtothelimitofdetectioninpartialleastsquarescalibration |
bdutipo_str |
Repositorios |
_version_ |
1764820408399298563 |