In integration, you can refine the data, and detect peaks.


The view is made of three main parts:

  • Overview (left)

  • Peaks table (top)

  • Profiles view (bottom)


It displays all your profiles data as a tree, ordered by HPTLC step / instrument and by wavelength (or illumination). You can select which step and wavelength you want to use in the evaluation.


It is only possible to select one HPTLC step / instrument

If you need to use two or more steps, you should create new evaluation tabs for the other steps.

You can either select a whole HPTLC step / instrument, or only some of the wavelengths.


Only selected data will be available in the next evaluation steps.

It is also possible to hide a specific track of the different profile view of evaluation: switch the track from imgTrackOn to imgTrackOff


For the Visualizer step, you need first to generate profile data in Data View , and if not already done, the step will be marked with imgVisuWarn .

To the right of the track number, the type of sequence is displayed, imgReference for reference and imgSample for sample. The icons have tooltips displaying the application in details.

Profiles view

The Profiles viewer can be used here in both 2D and 3D, for one or several tracks.

On the right, you have the different integration tools. They follow the easy/expert rule:

  • On/Off: Check the box to activate the tool

  • Easy: Select the algorithm

  • Expert: Change the parameters of the algorithm



Bounds will allow you to only use the data between the start and end bound (in Rf unit).

  • Clip outside: will also hide the data outside bounds


Profile raw data usually have some noise, which can adversely affect the peak detection. With smoothing, you can remove this noise.

  • Savitzky Golay (SG)

  • Moving average (MA)

  • Gauss

For each algorithm, a window or width can be adjusted to specify the amount of noise filtered.


Most plates don’t have a perfect background, therefore you should remove this baseline for better results.

You can display the detected baseline with the Display baseline checkbox.

  • Lower slope (LS): Automatic baseline detection, works on most data

  • Interactive: You need to manually add baseline segments with btnBsAdd . It is possible to remove one segment with btnBsRemove and clear the whole list with btnBsClear .

Dual Wavelength

In some rare cases, it can be interesting to subtract a wavelength from another. When choosing a wavelength/illumination in the combobox, its track are subtracted from each track of the current step.


  • Optional Quadratic Interpolation (OQI)

  • Gauss

Peak detection with both algorithms can be adjusted for Separation, Sensitivity and Threshold.