Removal of the 1st order Rayleigh scatter effect

1. Removal of the 1st order Rayleigh scatter effect Åsmund Rinnan

2. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Fluorescence - EEM Excitation Emission

3. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion PARAFAC An extension from PCA X is the EEM a are the scores b are the emissions c are the excitations E is the residual

4. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Light scatter in Fluorescence 1st order Rayleigh Raman 2nd orderRayleigh Excitation Emission

5. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Why is this a problem? X X

6. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion EEM’s with analytes

7. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Ways of treating scatter • Cut off and insert missing • Subtraction of standard • Weights • Modeling of Rayleigh

8. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Subtraction of standard It is not always possible with a standard

9. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Why isn’t onemethod enough!? • The data presented so far is a bit simple  Sugar data 1st order Rayleigh Emission Excitation

10. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Cutting off – inserting zeros Emission loadings Excitation loadings

11. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Weighting - MILES Emission loadings Excitation loadings

12. Introduction Treating scatter Revelation 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)

13. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Band of missing values

14. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Using a band of missing valuesHard weights Emission loadings Excitation loadings

15. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Using a band of missing valuesMILES weights Emission loadings Excitation loadings

16. Introduction Treating scatter Revelation A step back Good 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!

17. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Ways of modeling Rayleigh • Rasmus has tested a Gauss-Lorentz curve fitting method

18. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Modeling Rayleigh

19. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion Fancy doesn’t mean good

20. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion With constraints even better Emission loadings Excitation loadings

21. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion 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