Looking to the scatter effects with Unscrambler

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:

http://www.models.life.ku.dk/datasets

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.

Importing WinISI data into Unscrambler

I use the Win ISI "demo.cal" data to export it as an ASCII file, and I tried to import it into the 9.1 Unscrambler version which has the option to import from ASCII, and a window appears to configure how the ASCII file exported from Win ISI is designed.

This way, I have all data in place so I can start to configure the sample and variable sets.

This is a well known sample set so it is quite interesting for a tutorial of Unscrambler.