Dynamic orthogonal projection. A new method to maintain the on-line robustness of multivariate calibrations. Application to NIR-based monitoring of wine fermentations

Zeaiter, Magida; Roger, Jean‐Michel; Maurel, Véronique Bellon

doi:10.1016/j.chemolab.2005.06.011

Cited by 110 publications

(69 citation statements)

References 26 publications

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“…• For each spectrum x i of X, an ideal spectrum x i was calculated by means of a kernel centred on its y i value and applied on the other samples, like explained in [15]. Then, δx ss was estimated as the di erence between x i and 12…”

Section: Estimation Of Termsmentioning

confidence: 99%

A new formulation to estimate the variance of model prediction. Application to near infrared spectroscopy calibration

Fernández-Ahumada

Roger

Palagós

2012

Analytica Chimica Acta

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Section: Estimation Of Termsmentioning

confidence: 99%

A new formulation to estimate the variance of model prediction. Application to near infrared spectroscopy calibration

Fernández-Ahumada

Roger

Palagós

2012

Analytica Chimica Acta

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“…Note that the analyte concentrations need not be known explicitly for drift-space estimation. Furthermore, mean-centering in Equation (19) can potentially cause rank deficiency, thereby removing one factor of the drift subspace for each sample. For example, if the drift is a sample-invariant constant baseline, this drift is not captured inD since Equation (14) and thus Assumption A2 do not hold.…”

Section: Type 1: Operator a Deduced From Knowledge Of X Mmentioning

confidence: 99%

“…In Reference [19], an alternate way for capturing the drift subspace is proposed. It uses n d on-line measurements X s together with the corresponding concentrations Y s,k that are either measured by reference analytics or known a priori (e.g.…”

Section: Type 2: Operator a Computed From Knowledge Of Y Mkmentioning

confidence: 99%

“…component correction (CC) [13], independent interference reduction (IIR) [14], generalized least squares (GLS) [15,16], external parameter orthogonalization (EPO) [17], calibration transfer by orthogonal projection (TOP) [18], dynamic orthogonal projection (DOP) [10,19,20], difference correction of prediction spectra (DCPS) [21], error removal by orthogonal subtraction (EROS) [22], and orthogonal independent component regression (O-ICR) [29]. Confronted with a choice from this alphabet soup of ECMs only adds to the confusion of a practitioner.…”

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confidence: 99%

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Framework for explicit drift correction in multivariate calibration models

Gujral

Amrhein

Wise

et al. 2010

Journal of Chemometrics

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Latent-variable calibrations using principal component regression and partial least-squares regression are often compromised by drift such as systematic disturbances and offsets. This paper presents a two-step framework that facilitates the evaluation and comparison of explicit drift-correction methods. In the first step, the drift subspace is estimated using different types of correction data in a master/slave setting. The correction data are measured for the slave with drift and computed for the master with no drift. In the second step, the original calibration data are corrected for the estimated drift subspace using shrinkage or orthogonal projection. The two cases of no correction and drift correction by orthogonal projection can be seen as special cases of shrinkage. The two-step framework is illustrated with four different experimental data sets. The first three examples study drift correction on one instrument (temperature effects, spectral differences between samples obtained from different plants, instrumental drift), while the fourth example studies calibration transfer between two instruments.

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“…1 The effective solution to this problem is of tremendous practical importance since it is encountered in many areas such as monitoring polymerization [2][3][4][5] and fermentation 6,7 processes and in medical diagnostics 8 . Spectroscopic measurements have the potential for providing such information and would be preferable, because they are fast, cheap, compatible with fibre optics and multifunctional.…”

Section: Introductionmentioning

confidence: 99%

Extraction of Chemical Information of Suspensions Using Radiative Transfer Theory to Remove Multiple Scattering Effects: Application to a Model Two-Component System

Steponavičius

Thennadil

2009

Anal. Chem.

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This version is available at https://strathprints.strath.ac.uk/13703/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Extraction of Chemical Information of Suspensions RECEIVED DATE (to be automatically inserted after your manuscript is accepted if requiredaccording to the journal that you are submitting your paper to) ABSTRACTAn approach for removing multiple light scattering effects using the radiative transfer theory (RTE) in order to improve the performance of multivariate calibration models is proposed. This approach is then applied to the problem of building calibration models for predicting the concentration of a scattering (particulate) component. Application of this approach to a simulated four component system showed 1 that it will lead to calibration models which perform appreciably better than when empirically scatter corrected measurements of diffuse transmittance (T d ) or reflectance (R d ) are used. The validity of the method was also tested experimentally using a two-component (Polystyrene-water) system. While the proposed method led to a model that performed better than that built using R d , its performance was worse compared to when T d measurements were used. Analysis indicates that this is because the model built using T d benefits from the strong secondary correlation between particle concentration and pathlength travelled by the photons which occurs due to the system containing only two components.On the other hand, the model arising from the proposed methodology uses essentially only the chemical (polystyrene) signal. Thus this approach can be expected to work better in multi-component systems where the pathlength correlation would not exist.

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Dynamic orthogonal projection. A new method to maintain the on-line robustness of multivariate calibrations. Application to NIR-based monitoring of wine fermentations

Cited by 110 publications

References 26 publications

A new formulation to estimate the variance of model prediction. Application to near infrared spectroscopy calibration

A new formulation to estimate the variance of model prediction. Application to near infrared spectroscopy calibration

Framework for explicit drift correction in multivariate calibration models

Extraction of Chemical Information of Suspensions Using Radiative Transfer Theory to Remove Multiple Scattering Effects: Application to a Model Two-Component System

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