Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity

Abstract

Five Balkan paprika varieties at physiological maturity were investigated by means of Raman spectroscopy in order to discriminate the differences which stemmed from their genetic variability since the plants were grown under the same experimental conditions. The spectra were obtained using the 532 nm wavelength. In an effort to find the best classification power, several pre-processing methods were applied: 1) baseline correction, unit vector normalization; 2) baseline correction, unit vector normalization and first Savitzky-Golay derivative; 3) baseline correction, unit vector normalization and second Savitzky-Golay derivative; 4) baseline correction, unit vector normalization and third Savitzky-Golay derivative. All of the pre-processing methods were followed by making PCA-LDA (Principal Component Analysis-Linear Discriminant Analysis), QDA (Quadratic Discriminant Analysis), and PLS-DA (Partial Least Square - Discriminant Analysis) classification models. QDA showed the best discrimination power (83.87–100% and 89.47–100% for the training and the test data, respectively), then PCA-LDA (0.00–100 and 0.00–100% for the training and the test data, respectively) and PLS-DA (19.35–100% and 0.00–100.00% for the training and the test data, respectively). The results pointed out the applicability of chemometric modeling associated with Raman spectroscopy in the assessment of nutritionally similar samples, such as the studied red paprika varieties.