Abstract

The aim of this contribution is to demonstrate the transfer of spectra that have been measured on two different laboratory Fourier transform near-infrared (FT-NIR) spectrometers to the format of a handheld instrument by measuring only a few samples with both spectrometer types. Thus, despite the extreme differences in spectral range and resolution, spectral data sets that have been collected and quantitative as well as qualitative calibrations that have been developed thereof, respectively, over a long period on a laboratory instrument can be conveniently transferred to the handheld system. Thus, the necessity to prepare completely new calibration samples and the effort required to develop calibration models when changing hardware platforms is minimized. The enabling procedure is based on piecewise direct standardization (PDS) and will be described for the data sets of a quantitative and a qualitative application case study. For this purpose the spectra measured on the FT-NIR laboratory spectrometers were used as “master” data and transferred to the “target” format of the handheld instrument. The quantitative test study refers to transmission spectra of three-component liquid solvent mixtures whereas the qualitative application example encompasses diffuse reflection spectra of six different current polymers. To prove the performance of the transfer procedure for quantitative applications, partial least squares (PLS-1) calibrations were developed for the individual components of the solvent mixtures with spectra transferred from the master to the target instrument and the cross-validation parameters were compared with the corresponding parameters obtained for spectra measured on the master and target instruments, respectively. To test the retention of the discrimination ability of the transferred polymer spectra sets principal component analyses (PCAs) were applied exemplarily for three of the six investigated polymers and their identification was demonstrated by Mahalanobis distance plots for all polymers.

© 2016 The Author(s)

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