About using the Check Cell

NIR Systems Instruments, use to come in some cases with a Check Cell, with some files (.eqa, .std, master.nir,...). Once configure the Check Cell must be used carefully:

Storage:

• Keep it in the box until use at room temperature.
• Handle it carefully (don´t drop it)
• Keep the quartz glass clean.
• Instrument must be warmed-up.

Starting using the Check Cell:

• Scan the check cell three times every day (during two weeks) looking for a reasonable range of variation conditions.
• After this, scan the check cell once a day.

Check Cell interpretation:

• We will keep a file with just the 64 last scans of the check cell, where we have some important statistics:
• Mean for each constituent of previous predictions
• Std of previous predictions
• When analyzed we get the predictions and the T statistic (must be between +/- 3.00).
• If the Check Sample is out of tolerance, suspect of the instrument:
• Is it warmed up?
• Does it pass the diagnostics?.
• Are the lab conditions fine? (temperature,.....)

See the plots:

• Is the instrument drifting continuously overtime?
• Is the instrument drifting dramatically from one day to the other?
• Are all the parameters affected or some of them?
• ..................

Check Cell can be used as a tool to understand better how our instrument is performing and also the variations you have in the lab.

Is important that they are correctly sealed, in order that the variations of the product inside be minimal during those 64 days, if not reduce it to lower number.

You can export the spectra of check cell to a Chemometric Software as Win ISI in order to understand the variation.

 

"Write comments with your experience with the Check Cell. Many users does not use it, others love it,......"

 

There are new check cells more artificial, or more stable to changes, which come with the new instruments.

 

To have the check cell scanned every day will help the technicians a lot, after repairing an instrument to check if the instrument performs like in the past when it was fine.

 

Unscrambler Video: Chemometrics applied to NIR data

It´s nice to see always this kind of videos (software chemometric tools), explaining how to treat and proceed NIR data in this case with Unscrambler software.

How to import a TXT spectra file into Win ISI

I use in this case the Gasoline spectra from R chemometric package PLS.
Now I open in Win ISI the Convert Tool:

I select the file gasoline5.txt, and I put the output format in Win ISI.
Press Begin Conversion.
Answer if sample numbers are in the text file......................YES
Answer if there are constituents and the number..................In this case 0
Answer the total number of data points in the spectra.........401
Answer the number of Segments of the Spectra:
In this case I select two:

          

 One from 900 to 1098 every two nanometers
 Other from 1100 to 1700 every two nanometers

The convertion is completed and a new NIR file appear: gasoline5.nir

Scores and reconstruction

While looking to the first lesson of the algebra course of MIT, I capture this screen shot because it explain, in an easy way, the reconstruction of a spectrum.

The x and y would be the scores of the spectrum (0,3) , and we have to find them, knowing that the 

first loading is (2,-1), and the second (-1,2), so  x and y will be the solutions of the equation:

2x - y = 0

-x + 2y = 3

In this case there is a solution,  and the residual is cero, but in the case of real spectra there are more variables than two and we try to fit as best as possible the solution to the unknown with the linear combinations of the loadings multiplied by the scores, and the residual is the residual vector e.

The loading matrix “P” : a good example of orthogonal matrix

We know that for an orthogonal matrix A:

A^t.A=A.A^t=I

When we calculate the loading matrix during the PCA process, each loading is orthogonal (perpendicular) to all others. So we can check for fun in R, Excel,…., this condition with the loading matrix.

P is a very large matrix, so we will check it with just a few columns (6 loadings or terms) and the same number of files (6 wavelengths):

 

> round(gas.loadings[1:6,1:6],digits=4)
          PC1   PC2   PC3    PC4   PC5    PC6
900 nm -0.011 0.022 0.034 -0.039 0.042 -0.020
902 nm -0.010 0.022 0.031 -0.041 0.039 -0.022
904 nm -0.011 0.022 0.030 -0.042 0.036 -0.021
906 nm -0.012 0.024 0.027 -0.045 0.031 -0.012
908 nm -0.013 0.021 0.025 -0.045 0.035 -0.013
910 nm -0.014 0.023 0.023 -0.046 0.036 -0.018

 

P^t is the transpose, so the columns are the wavelengths and the files the loadings:

 

> round(t(gas.loadings[1:6,1:6]),digits=4)
    900 nm 902 nm 904 nm 906 nm 908 nm 910 nm
PC1 -0.011 -0.010 -0.011 -0.012 -0.013 -0.014
PC2  0.022  0.022  0.022  0.024  0.021  0.023
PC3  0.034  0.031  0.030  0.027  0.025  0.023
PC4 -0.039 -0.041 -0.042 -0.045 -0.045 -0.046
PC5  0.042  0.039  0.036  0.031  0.035  0.036
PC6 -0.020 -0.022 -0.021 -0.012 -0.013 -0.018

Now we multiply the two matrix:

> round((gas.loadings[1:6,1:6])%*% solve((gas.loadings[1:6,1:6])),digits=4)
       900 nm 902 nm 904 nm 906 nm 908 nm 910 nm
900 nm      1      0      0      0      0      0
902 nm      0      1      0      0      0      0
904 nm      0      0      1      0      0      0
906 nm      0      0      0      1      0      0
908 nm      0      0      0      0      1      0
910 nm      0      0      0      0      0      1

 

> round(((solve(gas.loadings[1:6,1:6]))%*%(gas.loadings[1:6,1:6])),digits=4) PC1 PC2 PC3 PC4 PC5 PC6 PC1 1 0 0 0 0 0 PC2 0 1 0 0 0 0 PC3 0 0 1 0 0 0 PC4 0 0 0 1 0 0 PC5 0 0 0 0 1 0 PC6 0 0 0 0 0 1