In the left side of the previous plots, you can see NIT spectra of wheat kernels, that I have download from the database available at:
This web page is very interesting and also the YouTube Chanel where Rasmus Bro (Professor, Dept. of Food Science, University of Copenhagen) explain PCA and PLS concepts with Unscrambler apart from other Chemometric Lessons.
The data is in Matlab and I have to play with it to import it to Unscrambler. Once in Unscrambler I check the option to look to the scatter effects that I saw in an Unscrambler Camo video in YouTube. The video use the new Unscrambler X, but I have the 9.1, and this function to check the scatter effects is also in this old version.
So in the left side we can see the scatter effect for every sample, and it is clear that we have an add effect that we have to remove.
We want to see the chemical effects and not the physical effects like the scatter. So I apply the S. Golay math treatment and look to the effects again and I see this plot:
and something curious happen, because we continue seeing scatter effects in a multiplicative way from the center to the extremes, so SG could help to improve the correlation with the constituent of interest, but not the scatter removal, so I add to the SG transformation the MSC transformation and we can see how the scatter is almost removed.