Weighted parallel factor analysis for calibration of HPLC-UV/Vis spectrometers in the presence of Beer's law deviations

Andersson, Greger; Dable, Brian K.; Booksh, Karl S.

doi:10.1016/s0169-7439(99)00040-4

Cited by 29 publications

(13 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Scatter can be considered as outlying elements or outliers of the second type, because this scatter does not contain any chemically relevant information and does not follow the tri-linear model. Several ways to handle scatter in relation to PARAFAC modeling can be found in the literature [7,11,[15][16][17][18][19][20][21] but treating scatter as outlying elements leads in Engelen et al [2] to the construction of the automated scatter identification method. The approach can handle both first and second order Rayleigh scatter as well as Raman scatter and require no a priori information about the scatter itself, like for example the placement or the width of the scatter ridges.…”

Section: Introductionmentioning

confidence: 99%

A fully robust PARAFAC method for analyzing fluorescence data

Engelen

Frosch

Jørgensen

2009

Journal of Chemometrics

View full text Add to dashboard Cite

Parallel factor analysis (PARAFAC) is a widespread method for modeling fluorescence data by means of an alternating least squares procedure. Consequently, the PARAFAC estimates are highly influenced by outlying excitation-emission landscapes (EEM) and element-wise outliers, like for example Raman and Rayleigh scatter. Recently, a robust PARAFAC method that circumvents the harmful effects of outlying samples has been developed. For removing the scatter effects on the final PARAFAC model, different techniques exist. Newly, an automated scatter identification tool has been constructed. However, there still exists no robust method for handling fluorescence data encountering both outlying EEM landscapes and scatter. In this paper, we present an iterative algorithm where the robust PARAFAC method and the scatter identification tool are alternately performed. A fully automated robust PARAFAC method is obtained in that way. The method is assessed by means of simulations and a laboratory-made data set.

show abstract

Section: Introductionmentioning

confidence: 99%

A fully robust PARAFAC method for analyzing fluorescence data

Engelen

Frosch

Jørgensen

2009

Journal of Chemometrics

View full text Add to dashboard Cite

show abstract

“…Furthermore does PARAFAC have difficulty in modeling the specific structure of the data, which contains many zeros after mean centering due to correlations that are invariant across environmental conditions. Techniques like weighted PARAFAC [35], maximum likelihood PARAFAC [36] or MILES [37] might help in dealing with this specific structure in the data.…”

Section: Discussionmentioning

confidence: 99%

Multi‐way analysis of flux distributions across multiple conditions

Verouden

Notebaart

Westerhuis

et al. 2009

Journal of Chemometrics

View full text Add to dashboard Cite

“…EEM fluorescence spectra typically contain contributions from both Rayleigh and Raman scatter, greatly complicating PARAFAC analysis as the scattering is dependent on the excitation wavelength and therefore does not fulfill the trilinearlity constraint [33]. A number of methods have been developed to in order to minimize the influence of Rayleigh and Raman scatter on the analysis [30,[33][34][35][36][37][38][39], including interpolation of the regions including Rayleigh and Raman scattering after removal of the aforementioned scattering effects [36], modeling the Rayleigh and Raman scattering as a separate component [35], using maximum likelihood PCA as a pretreatment method [38], and weighted PARAFAC [30,33,39].…”

Section: Theorymentioning

confidence: 99%

Application of EEM fluorescence in combination with PARAFAC analysis to simultaneously monitor quercetin in its deprotonated, aggregated, and protein bound states

Simpson

Burke

JiJi

2010

Journal of Chemometrics

View full text Add to dashboard Cite

Flavonoids, a group of naturally occurring polyphenols, attract great interest due to their many apparent health benefits including their anti-oxidant properties and anti-amyloidogenic properties. However, the behavior of flavonoids in aqueous environments can be unpredictable due to the potential formation of aggregates and hydrolysis products. A better understanding of the complex behavior of flavonoids is needed before flavonoid-based therapies can be developed. Employing excitation-emission matrix (EEM) fluorescence in combination with weighted-parallel factor analysis (WPARAFAC), a series of aqueous quercetin solutions were characterized at varying pH values and concentrations. Distinct pH and concentration-dependent fluorophores were observed with emission maxima of 540 and 600 nm, respectively. However, the excitation maxima of the two species were broad and highly overlapped ranging from 350 to 400 nm. In addition, the fluorescence of quercetin was characterized in the presence and absence of bovine serum albumin (BSA). Interaction with BSA resulted in a dramatic red-shift of the excitation maximum to 445 nm, while the emission maximum of the BSA-quercetin complex was slightly blue-shifted to 535 nm. Coupling of WPARAFAC and EEM fluorescence enabled simultaneous detection of multiple fluorescent quercetin species in solution at a wide range of conditions.

show abstract

Weighted parallel factor analysis for calibration of HPLC-UV/Vis spectrometers in the presence of Beer's law deviations

Cited by 29 publications

References 22 publications

A fully robust PARAFAC method for analyzing fluorescence data

A fully robust PARAFAC method for analyzing fluorescence data

Multi‐way analysis of flux distributions across multiple conditions

Application of EEM fluorescence in combination with PARAFAC analysis to simultaneously monitor quercetin in its deprotonated, aggregated, and protein bound states

Contact Info

Product

Resources

About