Wine grapes are food products of considerable commercial value for several countries.In the framework of project “Recupero del Germoplasma Viticolo Pugliese”(Re.Ge.Vi.P.), with the aim to valorize Apulian grape biodiversity, we used 1H NMRspectroscopy to obtain the metabolic fingerprinting of wine grape juices, belonging to 10 representative Apulian cultivars (Primitivo, Negroamaro, Verdeca, Bianco D'Alessano, Bombino Bianco, Minutolo, MalvasiaNera, Uva Di Troia, Susumaniello, Bombino Nero).Grape samples were collected in three years (2013, 2014, 2016); they were harvested at similar level of ripening. Different approaches of multivariate statistical analysis were applied to spectral data in order to find specific metabolites discriminating for variety and/or year(Fig. 1). In this presentation, metabolic profiling of winegrapes from different cultivars along with multivariate statistical analysis and performances of classification models will be shown.

Metabolic profiling of autochthonous apulian wine grape juices

R. Ragone
;
V. Gallo;P. Mastrorilli;M. Latronico;A. Rizzuti;S. Todisco
2017-01-01

Abstract

Wine grapes are food products of considerable commercial value for several countries.In the framework of project “Recupero del Germoplasma Viticolo Pugliese”(Re.Ge.Vi.P.), with the aim to valorize Apulian grape biodiversity, we used 1H NMRspectroscopy to obtain the metabolic fingerprinting of wine grape juices, belonging to 10 representative Apulian cultivars (Primitivo, Negroamaro, Verdeca, Bianco D'Alessano, Bombino Bianco, Minutolo, MalvasiaNera, Uva Di Troia, Susumaniello, Bombino Nero).Grape samples were collected in three years (2013, 2014, 2016); they were harvested at similar level of ripening. Different approaches of multivariate statistical analysis were applied to spectral data in order to find specific metabolites discriminating for variety and/or year(Fig. 1). In this presentation, metabolic profiling of winegrapes from different cultivars along with multivariate statistical analysis and performances of classification models will be shown.
46th National Congress on Magnetic Resonance
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/223058
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