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

2. 2 Dioxin and fatty acid data Problem To develop a PLS model that can predict the dioxin concentration (y) in ng/(kg fat) in fish meal samples from fatty acids profiles (X). In total 64 samples were analysed and gas chromatography was used for the determination of 32 fatty acids (including an unidentified group). The results are given in % of all 32 fatty acids. The very expensive and complex dioxin analyses were performed by a German laboratory. Data The dimension of the data structure is 64 objects x 34 variables. The first two variables are the species code (herring, sprat, blue whiting, sand eel etc. in total 15 species) and the dioxin content. Variables 3 to 34 are the chromatographic variables. Source: Rapid dioxin assessment in fish products by fatty acid pattern recognition, Marc Bassompierre, Lars Munck, Rasmus Bro and Søren Balling Engelsen, Analyst, 129, 553-558, 2004.

3. 3 Get the data

4. 4 The data in the WorkBench

5. 5 Select the fatty acid variables Write 3:34 and press [ENTER] or select the fatty acid variables in the Variables listbox

6. 6 Define a variable set

7. 7 Give the set a name, e.g. X

8. 8 Now select dioxin in the listbox The plot window always show the actual selection in the Objects and Variables listboxes

9. 9 Plot dioxin as a function of the objects Click on this icon

10. 10 Define a variable set containing only the dioxin variable

11. 11 Give the set a name, e.g. y

12. 12 Autoscale the X data First select X in the Sets box Then select autoscale

13. 13 The effect is shown instantly in the plot Click Transform to see how the transformation affects the data

14. 14 Make a PLS model Select PLS in the dropdown menu

15. 15 Select the dependent variable(s) First select y in the Sets box Then select y (or click on Dioxin in the listbox)

16. 16 Autoscale y

17. 17 Choose cross validation Select CV: Syst123 (Venetian blinds)

18. 18 Choose the number of segments In this case we use eight segments

19. 19 Calculate the PLS model Press Calculate Then press OK

20. 20 Plot the error

21. 21 RMSEC & RMSECV Select both using CTRL

22. 22 U vs T plot

23. 23 U vs T plot Change the markers & labels TIP: use the arrows keys to change the number of components

24. 24 Plot regression coefficicents

25. 25 Regression coefficients Change the markers & labels TIP: use the arrows keys to change the number of components

26. 26 Plot Actual vs Predicted

27. 27 Actual vs Predicted for six components Change the markers & labels TIP: use the arrows keys to change the number of components THE END