X is the wavelength represented in nm (nanometers).
Y is dependent on the state of the toggle buttons you select.
When:
Processed (only): Assumes Beer-Lambert model is valid, and transforms the measured signal to be linear with concentration by doing a log transform and adjusting the result for noise and deviations from the model.
Normalized (only): Performs normalization of the signal. This is meant to compensate for changing measurement conditions (e.g. varied scanning distances) that typically occur from sample to sample. Y axis still means reflectance but in normalized units instead of raw reflectance.
Both Processed and Normalized: First assumes Beet-Lambert model (Processed) and then normalizes the results to compensate for differences in the optical path between samples. This is useful, for example, when there is variation in the thickness of the samples.
Both (log)R))” and Normalized:Similar to Processed and Normalized, uses a more aggressive form of Processed. Adds more noise, but in some cases may be the only way to create a good model.
Typically, different models and types of samples will require different pre-processing methods. You should both choose the pre-processing method to match your experimental setup and optimize the performance of your model. If you planned and gathered your data correctly, these efforts will coincide.
As for comparing with other techniques, there is always some difference between devices, especially if you use different pre-processing methods.
It should be noted that SCiO is a complete system that includes spectrometer, internal illumination source and machine learning algorithms optimized for SCiO. The best way to compare those technique is to try and create chemoemetric models with each technique and evaluate their performance.
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Regards,
Ayelet,
The ConsumerPhysics team
