Whole products have achieved remarkable success over the years for the growing attention by consumers for the health effects of these foods. In the present study, a multivariate model was developed to characterize durum wheat pasta and whole wheat pasta based on the carotenoid content and to assess the possible influence of the drying process used in pasta manufacturing on the total carotenoid amount. 96 pasta samples were analyzed in HPLC-UV/Vis following an accelerated solvent extraction phase (ASE system) previously optimized using an experimental design approach (CCD, central composite design). A PLS-DA (Partial Least Squares-Discriminant Analysis) method was used for data processing. The resulting classification model showed excellent results (100 % of correct classification for both pasta categories) discriminating the samples based on the semolina used for the production (refined durum wheat vs whole wheat). The findings also highlighted that lutein was present in much larger amounts compared to the other bioactive components in all investigated samples, suggesting that it might be used as a product marker of total carotenoids in pasta.
Comparison of the carotenoid content in durum wheat pasta and wholewheat pasta by multivariate analysis / Giannetti, Vanessa; BOCCACCI MARIANI, Maurizio; Livi, Greta. - (2023), pp. 241-248. - CIRCULAR ECONOMY AND SUSTAINABILITY. [10.1007/978-3-031-28292-8].
Comparison of the carotenoid content in durum wheat pasta and wholewheat pasta by multivariate analysis
Vanessa Giannetti
Primo
;Maurizio Boccacci Mariani;Greta Livi
2023
Abstract
Whole products have achieved remarkable success over the years for the growing attention by consumers for the health effects of these foods. In the present study, a multivariate model was developed to characterize durum wheat pasta and whole wheat pasta based on the carotenoid content and to assess the possible influence of the drying process used in pasta manufacturing on the total carotenoid amount. 96 pasta samples were analyzed in HPLC-UV/Vis following an accelerated solvent extraction phase (ASE system) previously optimized using an experimental design approach (CCD, central composite design). A PLS-DA (Partial Least Squares-Discriminant Analysis) method was used for data processing. The resulting classification model showed excellent results (100 % of correct classification for both pasta categories) discriminating the samples based on the semolina used for the production (refined durum wheat vs whole wheat). The findings also highlighted that lutein was present in much larger amounts compared to the other bioactive components in all investigated samples, suggesting that it might be used as a product marker of total carotenoids in pasta.File | Dimensione | Formato | |
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