Abstract

This work attempted to interpret the principal component loadings spectra of principal component analysis on large spectral data sets with multi-variables using two-dimensional (2D) correlation analysis. Three examples of visible/near infrared (NIR) spectra of chicken muscles under different conditions were given and discussed. 2D analysis indicated that characteristic bands from loadings spectra are in good agreement with those from a small number of spectra induced by simple external perturbations. Although some advantages of 2D correlation analysis (such as sequential changes in intensity) were not available, it might still be useful for the understanding of large and complex spectral data sets with multi component variations.

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