removal of the 1st order rayleigh scatter effect Åsmund rinnan
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Removal of the 1st order Rayleigh scatter effect
Åsmund Rinnan
Fluorescence - EEM
Excita
tion
Emission
IntroductionTreating scatter
Revelation
A step back
Good reasons
Model scatter
Conclusion
PARAFAC
ijk
F
fkfjfifijk ecbax
1
X is the EEMa are the scoresb are the emissionsc are the excitationsE is the residual
An extension from PCA
ij
F
fjfifij eptx
1
IntroductionTreating scatter
Revelation
A step back
Good reasons
Model scatter
Conclusion
Light scatter in Fluorescence
Excita
tion
Emission
2n
d o
rder
Rayle
igh
1st
ord
er
Rayle
igh
Ram
an
IntroductionTreating scatter
Revelation
A step back
Good reasons
Model scatter
Conclusion
Why is this a problem?X
X
IntroductionTreating scatter
Revelation
A step back
Good reasons
Model scatter
Conclusion
EEM’s with analytes
IntroductionTreating scatter
Revelation
A step back
Good reasons
Model scatter
Conclusion
Ways of treating scatter
•Subtraction of standard
•Cut off and insert missing
•Weights•Modeling of Rayleigh
Introduction
Treating scatterRevelation
A step back
Good reasons
Model scatter
Conclusion
Subtraction of standardIt is not always possible with a standard
Introduction
Treating scatterRevelation
A step back
Good reasons
Model scatter
Conclusion
Why isn’t onemethod enough!?
• The data presented so far is a bit simple Sugar data
Excitation
Emission 1st o
rder
Ray
leig
h
Introduction
Treating scatterRevelation
A step back
Good reasons
Model scatter
Conclusion
Cutting off – inserting zeros
Emission loadings Excitation loadings
Introduction
Treating scatterRevelation
A step back
Good reasons
Model scatter
Conclusion
Weighting - MILES
Emission loadings Excitation loadings
Introduction
Treating scatterRevelation
A step back
Good reasons
Model scatter
Conclusion
So now everybody says
• We need a new model to take care of this
• Hold your horses (a bit longer)
Introduction
Treating scatter
RevelationA step back
Good reasons
Model scatter
Conclusion
Band of missing values
Introduction
Treating scatter
Revelation
A step backGood reasons
Model scatter
Conclusion
Using a band of missing valuesHard weights
Emission loadings Excitation loadings
Introduction
Treating scatter
Revelation
A step backGood reasons
Model scatter
Conclusion
Using a band of missing valuesMILES weights
Emission loadings Excitation loadings
Introduction
Treating scatter
Revelation
A step backGood reasons
Model scatter
Conclusion
Another method?Why, why, why?
• The Rayleigh scatter width has to be estimated quite accurately
• The band width of missing data should also be correct
• What about an automatic method of removing the Rayleigh scatter, that was not so prone to the estimation of the width of the Rayleigh scatter?
• Modeling the Rayleigh is the answer!
Introduction
Treating scatter
Revelation
A step back
Good reasonsModel scatter
Conclusion
Ways of modeling Rayleigh
• Rasmus has tested a Gauss-Lorentz curve fitting method
Introduction
Treating scatter
Revelation
A step back
Good reasons
Model scatterConclusion
Modeling Rayleigh
Introduction
Treating scatter
Revelation
A step back
Good reasons
Model scatterConclusion
Fancy doesn’t mean good
Introduction
Treating scatter
Revelation
A step back
Good reasons
Model scatterConclusion
With constraints even better
Emission loadings Excitation loadings
Introduction
Treating scatter
Revelation
A step back
Good reasons
Model scatterConclusion
Conclusion
• Modeling is less sensitive to the estimated Rayleigh peak
• Give good models, even without constraints or other modifications of the data (band of missing values)
• The shifting method is relatively fast
Introduction
Treating scatter
Revelation
A step back
Good reasons
Model scatter
Conclusion