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Artículo

PTR-ToF-MS and data mining methods: a new tool for fruit metabolomics

Cappellin, Luca; Soukoulis, Christos; Aprea, Eugenio; Granitto, Pablo MiguelIcon ; Dallabetta, Nicola; Costa, Fabrizio; Violante, Roberto Antonio; Märk, Tilmann D.; Gasperi, Flavia; Biasioli, Franco
Fecha de publicación: 04/03/2012
Editorial: Springer
Revista: Metabolomics
ISSN: 1573-3882
e-ISSN: 1573-3890
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Biotecnología Agrícola y Biotecnología Alimentaria

Resumen

Proton Transfer Reaction-Mass Spectrometry (PTR-MS) in its recently developed implementation based on a time-of-flight mass spectrometer (PTR-ToF-MS) has been evaluated as a possible tool for rapid non-destructive investigation of the volatile compounds present in the metabolome of apple cultivars and clones. Clone characterization is a cutting-edge problem in technical management and royalty application, not only for apple, aiming at unveiling real properties which differentiate the mutated individuals. We show that PTR-ToF-MS coupled with multivariate and data mining methods may successfully be employed to obtain accurate varietal and clonal fingerprints. In particular, we studied the VOCs emission profile of five different clones belonging to three well known apple cultivars, such as Fuji, Golden Delicious and Gala. In all three cases it was possible to set classification models which can distinguish all cultivars and some of the clones considered in this study. Furthermore, in the case of Gala we also identified estragole and hexyl 2-methyl butanoate contributing to such clone characterization.Beside its applied relevance, no data on the volatile profiling of apple clones are available so far, our study indicates the general viability of a metabolomic approach for volatile compounds in fruit based on rapid PTR-ToF-MS fingerprinting.
Palabras clave: PTRMS , APPLE , CHEMOMETRICS , DATA MINING
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info:eu-repo/semantics/restrictedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/121435
DOI: http://dx.doi.org/10.1007/s11306-012-0405-9
URL: https://link.springer.com/article/10.1007/s11306-012-0405-9
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Articulos(CIFASIS)
Articulos de CENTRO INT.FRANCO ARG.D/CS D/L/INF.Y SISTEM.
Citación
Cappellin, Luca; Soukoulis, Christos; Aprea, Eugenio; Granitto, Pablo Miguel; Dallabetta, Nicola; et al.; PTR-ToF-MS and data mining methods: a new tool for fruit metabolomics; Springer; Metabolomics; 8; 5; 4-3-2012; 761-770
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