Two-dimensional (2D) correlation of near-infrared (NIR) and Raman spectra was carried out for mixtures of protein (lysozyme) and sugar (sucrose) to investigate the potential of this technique for qualitative NIR spectral interpretation. Cross-correlation by least-squares was employed to assess changes in both sets of spectra which result from changes in the set of sample spectra. Fourier transform (FT) NIR and NIR-excited FT-Raman spectra were measured for each of the samples under the same conditions, and point-for-point 2D cross-correlation was calculated. In this technique, each wavenumber in the NIR region gives rise to a sliced Raman spectrum where each data point is correlated to the NIR wavenumber, while each wavenumber in a Raman spectrum provides a sliced NIR spectrum in which each data point is correlated to the Raman wavenumber. For example, choosing NIR wavenumbers 7272, 6960, 6324, and 4812 cm−1 gives sliced Raman spectra with features attributable to sucrose, while choosing NIR wavenumbers at 8424, 5148, 5052, and 4584 cm−1 provides slices with distinct lysozyme features. Therefore, the technique permits the determination of the most probable origin of NIR signals by connecting NIR spectra, which have rather broad and overlapped bands, to Raman spectra consisting of sharp and clearly separated bands. It is also possible to produce sliced NIR spectra of lysozyme and sucrose by properly selecting wavenumbers in their Raman spectra. The NIR slices explain which wavenumbers in the NIR region are correlated to lysozyme or to sucrose. Thus, 2D correlation spectroscopy helps explain the reasons why certain wavenumbers are selected in a chemometric calibration model.
Method Superior to Traditional Spectral Identification: FT-NIR Two-Dimensional Correlation Spectroscopy Combined with Deep Learning to Identify the Shelf Life of Fresh Phlebopus portentosus
