6 qualification method development, 1 introduction, 2 qualification methods and types of thresholds – Metrohm Vision Manual User Manual
Page 114: Qualification method development, Introduction, Qualification methods and types of thresholds
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4.6
Qualification Method Development
4.6.1
Introduction
Qualification is the final step in the analysis. Qualification method helps to confirm the identity of the
unknown, and to establish if the quality of the sample fits the method’s criteria.
Each product in the library may have its own qualification method with a different threshold.
Methods have to be created separately for each product.
It is strongly recommended that each library product contain at least 30 sample spectra when
qualification by Mahalanobis Distance or Residual Variance is attempted.
4.6.2
Qualification Methods and Types of Thresholds
There are four qualification methods available: Mahalanobis distance in Principal Component space,
Residual Variance in Principal Component space, maximum distance in wavelength space, and
correlation in wavelength space.
For Mahalanobis distance and Residual Variance methods it is possible to calculate the probability
that a given spectrum belongs to the distribution represented by the product spectra. Therefore, for
those methods, Vision offers two kinds of thresholds: match value (the actual number representing
distance or residual variance), and the probability level. For the two remaining methods, only the
match value type of threshold is possible.
Any combination of available math pre-treatments can be applied to the spectra with each of the
methods.
Mahalanobis Distance in Principal Component space
In this method, the local Principal Component model is calculated for the product. During the
analysis, the unknown spectrum PC scores are calculated from the identified product model
and Mahalanobis distance is calculated. The unknown is qualified as the product when the
Mahalanobis distance is within the threshold value. The default threshold is 0.5 for match
value and 0.95 for probability level.
Residual Variance in Principal Component space
In this method, the local Principal Component model is calculated for the product. The
product’s Principal Component model is used to reconstruct the unknown spectrum. The
difference between original and reconstructed spectrum is used to calculate the residual
variance. The unknown is qualified as the product when the residual variance for the
product’s Principal Component model is within the threshold value. The default threshold is
2.5 for match value and 0.95 for probability level.
Maximum Distance in Wavelength Space
Maximum Distance belongs to the group of wavelength methods. For each product, the
training set of spectra is used to calculate the mean product spectrum and the inflated
standard deviation spectrum. During the analysis, the identified spectrum is subtracted from
the mean product spectrum and divided by the standard deviation spectrum at each
wavelength. The sample is qualified when the maximum value is within threshold limits for
the product. The default threshold is 3.
Correlation in Wavelength Space