FOSS CALIBRATOR: Tutorial - 003

In  the Sample menu, apart to see the spectra we have the option to inspect the samples in a principal components space looking for GH outliers. In this case after changing the default configuration by the one I choose in the previous videos I decide to remove the samples with a GH higher tha 4.00.

These samples are marked as spectral outliers, and we can see them in red color merged with the rest of the spectra, so we can inspect possible reason for those GH values.

We can recalculate the PCs again once these samples are remove, but we will do that in the Model Menu in next videos. This time the idea was to remove what we can consider clear spectral outliers.

In the sample menu we have the option to run PLS to have an idea about how the calibration will work and to check if we have clear reference outliers, taht in the case that the values are not correctly typed we can edit them and change to the correct value.

PCA and PLS will be treated specially in the Models menu, where we use the validation set and we will get the performance statistics in the case of PLS or MPLS Models.

FOSS CALIBRATOR: Importing lab values into a ".nir" file 
FOSS CALIBRATOR: Tutorial 001
FOSS CALIBRATOR: Tutorial 002 

FOSS CALIBRATOR: Tutorial 002

In this second tutorial, we continue looking with more detail to the spectra looking for noise that can be due to the sample presentation or other causes. Unless that noisy area has important information we can remove it for the calculation of outlier models and prediction models.

 Use a higher degree of derivative or lower gaps can help to the detection of noise. 

If there are important information, in the noisy area try to use higher gaps or lower derivative to see if there is an improvement in the spectra shape.

In the case that we are discriminating we have to check if the bands of interest are clearly higher than the noise.

Other tutorials:
FOSS CALIBRATOR: Importing lab values into a ".nir" file 
FOSS CALIBRATOR: Tutorial 001

FOSS CALIBRATOR: Tutorial 001

After importing the "nir" file into the project and link to it the ".csv" file with the lab values, we have generated three logical sets (the total, the training and the validation sets). 

Random split was choose and a warning advice that the validation set is not cover by the training set. We can recalculate or choose other split method, but we continue with these ones.

Without generating any outliers models yet we explore the data into the PCA and PLS space looking for reference or spectral outliers.

Other tutorials:
 FOSS CALIBRATOR: Tutorial 002
 FOSS CALIBRATOR: Importing lab values into a ".nir" file 

FOSS CALIBRATOR: Importing and adding lab values to a ".nir" file

As you see in the video a project is created in Foss Calibrator and a cocoa nir file is imported.

This file can not be divided into a training and test set until a parameter is created and the lab values are imported from a ".csv" file.

Other tutorials:
 FOSS CALIBRATOR: Tutorial 002
 FOSS CALIBRATOR: Tutorial 001