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Chemometric evaluation of the antioxidant properties and phenolic compounds in Italian honeys as markers of floral origin

Tipo de material: TextoTextoSeries ; European Food Research and Technology, 248, p.991-1002, 2022Trabajos contenidos:
  • Preti, R
  • Tarola, A. M
Tema(s): Recursos en línea: Resumen: Italian honeys from different floral sources (acacia, orange, honeydew, chestnut, strawberry tree, sulla, eucalyptus, dandelion, linden, polyfloral)were analysed in terms of colour, total phenolic content, in vitro antioxidant capacity and content of 15 phenolic compounds. Physicochemical parameters were also examined to assess the overall quality of honey. Dark honeys demonstrated to have the highest content in bioactive compounds and in antioxidant activity with the highest values in strawberry tree and honeydew honeys. Data were processed using principal component analysis (PCA), hierarchical cluster analysis (HCA)and linear discriminant analysis (LDA). The overall classification capacity for the 9 unifloral honey varieties obtained by LDA was 100.00 percent , with a very low level of prediction misclassification in cross validation (less than 5 percent ). This study demonstrates the strong relation between honey floral origin and bioactive compounds profile and amount, together with the importance of colour attributes as a simple approach for a preliminary evaluation of the antioxidant properties and floral origin discrimination.
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Italian honeys from different floral sources (acacia, orange, honeydew, chestnut, strawberry tree, sulla, eucalyptus, dandelion, linden, polyfloral)were analysed in terms of colour, total phenolic content, in vitro antioxidant capacity and content of 15 phenolic compounds. Physicochemical parameters were also examined to assess the overall quality of honey. Dark honeys demonstrated to have the highest content in bioactive compounds and in antioxidant activity with the highest values in strawberry tree and honeydew honeys. Data were processed using principal component analysis (PCA), hierarchical cluster analysis (HCA)and linear discriminant analysis (LDA). The overall classification capacity for the 9 unifloral honey varieties obtained by LDA was 100.00 percent , with a very low level of prediction misclassification in cross validation (less than 5 percent ). This study demonstrates the strong relation between honey floral origin and bioactive compounds profile and amount, together with the importance of colour attributes as a simple approach for a preliminary evaluation of the antioxidant properties and floral origin discrimination.

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