Construction of an online reduced-spectrum NIR calibration model from full-spectrum data

Title: Construction of an online reduced-spectrum NIR calibration model from full-spectrum data
Creator: Dodds, Simon A.; Heath, William P.
Relation: Chemometrics and Intelligent Laboratory Systems Vol. 76, Issue 1, p. 37-43
Publisher Link: http://dx.doi.org/10.1016/j.chemolab.2004.09.002
Publisher: Elsevier BV
Resource Type: journal article
Date: 2005
Description: Near infrared (NIR) spectroscopy offers rapid and nondestructive estimation to a wide range of industries, but its acceptance has been slowed by the high costs of long-term use of full-spectrum instrumentation. From examining the terms produced in multivariate calibration of this full-spectrum data, it is possible to identify influential wavelengths, using either the regression vector b or a series of estimation prognostic vectors c, which is proposed in this paper. Once these wavelengths have been identified, the full-spectrum probe can be replaced with a series of monochromators, which is more commercially viable. In this paper, online NIR absorbance data from a pilot scale food extruder is used to estimate downstream product quality attributes (PQAs) via a full-spectrum calibration model followed by a reduced-spectrum model.
Subject: NIR spectroscopy; PCR; prognostic vectors; soft sensors
Identifier: http://hdl.handle.net/1959.13/33969
Identifier: uon:3426
Identifier: ISSN:0169-7439
Language: eng
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