NIR spectroscopy-multivariate analysis for discrimination and bioactive compounds prediction of different Citrus species peels

Near Infrared (NIR) method combined with chemometrics was utilized to achieve the target of deeper insight into the chemical diversity and to discriminate the different species and chemovarieties of Citrus peels. Unsupervised principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used for comparing of samples. A clear separation among the eight investigated species and cultivars was revealed, except for the red and white C. paradisi peels samples. Furthermore, fingerprint-bioflavonoids content relationship was modeled by partial least squares regression. A practical approach based on reflectance NIR measurements and partial least squares regression (PLSR) was demonstrated for quantitative determination of the bioflavonoids hesperidin and diosmin and compared to other reported methods. The regression coefficients (R-2) between predicted values and predetermined hesperidin and diosmin content were >0.98, indicating the possibility to simultaneously quantify hesperidin and diosmin in Citrus samples directly from NIR measurements using an adequate PLS regression. Citrus sinensis followed by Citrus reticulate samples were found the most enriched in the bioflavonoids hesperidin and diosmin. NIR-multivariate analysis can therefore be used for discrimination of different varieties and selection of citrus species with desired amounts of specific bioflavonoids which could successfully be analyzed in such complex plant matrices which can prove useful for further pharmaceutical implementation. (C) 2019 Elsevier B.V. All rights reserved.