As
we know a NIR instrument is costly to calibrate. Laboratory reference analysis
are expensive, and it requires a long time to get the necessary variability, for
a certain product, to get a calibration we can trust to start analyzing in
routine, that is the reason why some users buy the NIR instruments with a
calibration package for different products.
Anyway
we have to test this calibration with “our own test set” to check the
performance of the calibration, and check if we have a bias, or slope and
intercept problems.
In
this case to get a good test set is important. It has to cover the variability
of our suppliers (raw ingredients) or the variability of our final product.
One
way to do it is to analyze all the income samples we are receiving for some
time, storing the spectra, and after keep these samples in plastic bags or
containers. We can analyze also samples
of our process (at the start, in the middle or at the end of the batch, several
batches,) and store the samples and the spectra.
After
15 or 30 days we can have more than 100 samples, for example, so now we can
send to the Lab the samples with more variability per product.
The
way to do it is to create a Principal Component Space for these samples and
select the spectra with more variability. We can look also to the spectra
looking for the bands of water, protein, stark or fat and try to find some
relation between the scores and the spectra.
Win
Isi has a function to select the number of samples with more variability, that
is the one I show you, but sure other programs have similar tools. We can
analyze again the selected samples in the NIR instrument, and send them immediately
to the Lab.
This
way we can evaluate better the calibrations we have acquired with the
instruments and make better adjustments.
With the 100 spectra create the PCA and LIB files with the function "Create a Score File from a Spectra File".....after use the function "Select Samples from a Spectra file", and as Input use the 100 samples NIR file and in Options, say to the software that we are looking for 10 (or more) samples with most variability. In the output file we get this file telling us which samples we have to send to the Lab.
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