Short-wave near-infrared (NIR) spectra of raw milk have been analyzed in the 800-1100 nm region by two-dimensional (2D) correlation spectroscopy. In this study, we have used both the well-known generalized 2D correlation spectroscopy method, which yields correlation coefficients among spectral variances on all the wavelength points (wavelength-wavelength correlation), and a novel sample-sample correlation spectroscopy method, which gives correlation coefficients among the concentration dynamics of the species in the system. The sample-sample correlation spectroscopy develops correlation maps with the samples on the axes. First, a set of 34 spectra was ordered according to increasing fat content, while all other milk components varied freely. Both synchronous and asynchronous wavelength-wavelength correlation maps have shown strong baseline changes despite the use of multiplicative scatter correction as a pretreatment. Bands at 930 and 970 nm due to fat and water, respectively, have been found to be the most significant spectral features. The synchronous sample-sample correlation map was calculated from the original data matrix and was compared with the outer product of the fat concentration vector. The comparison has revealed that the main spectral variances in the raw milk spectra in the short-wave NIR region are due to fat. The same procedure was repeated for a set of 15 samples that contained a constant fat content and were ordered according to increasing protein content. Poor agreement was found between the outer product of the protein concentration vector and the synchronous sample-sample correlation map. This result suggests that the spectral variances in raw milk spectra that have a constant fat content are due not exclusively to proteins but also due to other milk components. Comparisons of partial least-squares (PLS) regression analysis of fat and proteins and both sample-sample and wavelength-wavelength 2D correlation analyses of raw milk spectra have been made.

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