In integration, you can refine the data, and detect peaks.
The view is made of three main parts:
Peaks table (top)
Profiles view (bottom)
It display all your profiles data as tree, ordered by TLC 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 TLC step / instrument
If you need to use two or more steps, you should create new evaluation tab for the other steps.
You can either select a whole TLC 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 to
For Visualizer step, you need first to generate profile data in The Data View , if not already done, the step will be marked with .
Right of the track number, the type of sequence is displayed, for reference and for sample. The icons have tooltips displaying the application in details.
The Profiles viewer is 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 have usually some noise, which can biasing the peak detection. With smoothing, you can remove this noise.
Savitzky Golay (SG)
Moving average (MA)
For each algorithm, a window or width can be adjusted to specify the amount of noise filtered.
Most plate don’t have a perfect background, you should remove this baseline for better result.
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 . It is possible to remove one segment with and clear the whole list with .
Optional Quadratic Interpolation (OQI)
Peak detection with both algorithms can be adjusted for Separation, Sensitivity and Threshold.