Shenk-Westerhaus method

Shenk-Westerhaus method, one particular standardization method patented by Shenk and Westerhaus in 1989,79,80 has seen high utility in NIR food and agricultural applications. This method involves a wavelength axis shift correction, followed by an intensity correction. The steps in this standardization method are as follows  

More details on the operation of this method can be found in Bouveresse etal.79 

Like other standardization methods, the effectiveness of this method depends greatly on the relevance of the standardization samples. In many cases, this method uses a set of 

The advantages of this method are that it explicitly addresses both intensity shifts and wavelength axis shifts. In addition, it can handle cases where the nature of the interinstrument variability varies with wavelength. It is also relatively simple to explain. Like the PDS method mentioned above, it requires the analysis of all standardization samples on all analyzers. One must also be careful to choose standardization samples that sufficiently convey the magnitude and nature of inter-instrument effects in the particular application. In an ideal case, relatively few standardization samples will be required for this purpose. However, this can be determined only by testing the standardization method using standardization sample sets of varying size and membership. 

Like other standardization methods, the effectiveness of this method depends greatly on the ability of the standardization samples to assess instrumental biases that affect prediction. In many cases, this method uses a set of sealed transfer standards that are relevant to the specific application. In one study [112], it was found that the effectiveness of this method depended greatly on whether the standardization samples sufficiently cover the spectral intensity ranges that are to be experienced in the on-line process data. 

The advantages of this method are that it explicitly addresses both intensity shifts and wavelength axis shifts. In addition, it can handle cases where the nature of the inter-instrument variability varies with wavelength. It is also relatively simple to explain. Like the PDS method mentioned above, it requires the analysis of all transfer standards on all analyzers. 

There are additional transfer/standardization methods that can be particularly useful for PAT applications. Some of these are discussed below  

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How many standardization samples are available for standardization An important point to consider is the number of standardization samples necessary to estimate the transfer parameters. Some methods based either on univariate local corrections (Shenk-Westerhaus algorithm) or on multivariate local correction (PDS, standardization in the wavelet domain, etc.) can be performed with a reduced number of standardization samples. However, multivariate methods based on the whole spectral range (direct standardization, two-block PLS) usually require more standardization samples to obtain a good and stable estimation of the standardization parameters [21]. 

All other approaches try and relate the child spectra to the parent spectra. In the patented method of Shenk and Westerhaus [41 Sh], in its simplest form, one first applies a wavelength correction and then a correction for the absorbance. Each wavelength channel i of the parent instrument is linked to a nearby wavelength channel j(i) in the child instrument, namely the one to which it is maximally correlated. Then, for each pair of wavelengths, i for the parent and j i) for the child, a simple linear regression is carried out, linking the pair of measured absorbances... 

Another issue is that of transferability of the calibration model among instruments. This has been a significant obstacle to more widespread use of NIR methods. Transferability is especially important to multisite facilities, because it is needed to avoid time-consuming recalibration procedures. Calibration errors may occur among instruments because of slight differences in instrument response, especially if full-spectrum multivariate models are used. Shenk and Westerhaus addressed the problem and proposed a standardization algorithm, which was modified by others. ... 

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