1. Quick guide to pre-processing Use [Alt-Tab] to go to LatentiX (if running) Press [Page Down] or [Enter] to continue Press [ESC] to end the show

2. 2 Sugar mixture data Purpose To show how to use pre-processing in LatentiX. A PCA model will be developed on near infrared (NIR) spectroscopy measurements on 231 mixtures of three constituents: glucose, fructose and sucrose. The sample set was made according to a mixture design where the concentrations of all three constituents are varied between 0% (w/w) and 100% (w/w): The crystalline samples were measured in a NIR Systems 6500 instrument (reflection) furnished with a sample cup (3 cm in diameter). The spectral range covered is 1100 nm to 2496 nm (every 4th nm); in total 350 data points per spectrum. Data The dimension of the data structure is 231x350 variables. Three classes (as well as labels) are assigned the concentrations of fructose, glucose and sucrose.

3. 3 Plot the spectra Select the predefined sets: Samples and NIR spectra

4. 4 Use wavelengths as the x-axis First click on Variable number Then select Wavelengths (nm) and click OK

5. 5 Now the x-axis is in nm

6. 6 Mean center the data

7. 7 Calculate a PCA model

8. 8 Plot the scores

9. 9 Color according to fructose First select Continuous Then select Fructose

10. 10 Name the PCA model Click on Name Then type name and click OK

11. 11 Make an SNV transformation Note: you can select Show plot to see the effect on the data

12. 12 Calculate a PCA model

13. 13 Name the model Click on Name Then type name and click OK

14. 14 Plot the scores

15. 15 Scores plot – color by fructose concentration First select Continuous Then select Fructose

16. 16 Scores plot – color by glucose concentration Then select Glucose

17. 17 Scores plot – color by sucrose concentration Then select Sucrose

18. 18 Remove SNV transformation

19. 19 Make an MSC transformation

20. 20 Calculate a PCA model

21. 21 Name the model Click on Name Then type name and click OK

22. 22 Remove MSC transformation

23. 23 Calculate first derivatives

24. 24 Input to first derivatives Window size Polynomial order Derivative calculated

25. 25 Calculate PCA model

26. 26 Name the model Click on Name Then type name and click OK

27. 27 The four models with different pre-processing can now be investigated and compared THE END