When viewing the scans of a data collection, the preprocessing options allow you to view your data collection spectrum with different algorithms applied. These can help you identify outliers, inaccurate scans and reveal possible relationships in your data.

Within the graphs SCiO Lab Mobile presents:

• Nothing is selected: Raw reflectance spectrum
• 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. You can learn more about Beer-Lambert here: http://www.chemguide.co.uk/analysis/uvvisible/beerlambert.html
• 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.