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Characterization of Volatile Compounds in New Cider Apple Genotypes Using Multivariate Analysis

Author:
Pello Palma, JairoUniovi authority; Mangas Alonso, Juan José; Dapena de la Fuente, Enrique; González Álvarez, JaimeUniovi authority; Díez Peláez, JorgeUniovi authority; Gutiérrez Álvarez, María DoloresUniovi authority; Arias Abrodo, PilarUniovi authority
Subject:

Cider apple

Breeding

Chemometric

HS-GC

SPME

Volatile compounds

Publication date:
2016-12
Editorial:

Springer

Publisher version:
http://dx.doi.org/10.1007/s12161-016-0521-7
Citación:
Food Analytical Methods, 9(12), p. 3492–3500 (2016); doi:10.1007/s12161-016-0521-7
Descripción física:
p. 3492–3500
Abstract:

Gas chromatography combined with solid-phase microextraction has been used for the identification of the aromatic profiles of new cider apple genotypes, and a chemometric characterization of these new cider apple genotypes has been carried out using exploratory and modelling techniques. Three breeding targets have been explored: (1) regular bearing and scab resistance, (2) resistance to bio-aggressors and (3) high polyphenol content and late ripening. Exploratory techniques established two genotype groups: those that come from breeding towards targets 1 and 2 with low polyphenol contents and those that come from breeding towards target 3 with high polyphenol contents. Alcohols were related to the genotypes with breeding towards target 3, and compounds such as esters were related to the genotypes with breeding towards targets 1 and 2. Models computed using the soft independent modelling of class analogy (SIMCA) technique presented good sensitivity (93 %), specificity (91 %) and classification hits (96 %). However, the predictions computed by SIMCA (70 %) and the artificial neural network (ANN) (76 %) were low

Gas chromatography combined with solid-phase microextraction has been used for the identification of the aromatic profiles of new cider apple genotypes, and a chemometric characterization of these new cider apple genotypes has been carried out using exploratory and modelling techniques. Three breeding targets have been explored: (1) regular bearing and scab resistance, (2) resistance to bio-aggressors and (3) high polyphenol content and late ripening. Exploratory techniques established two genotype groups: those that come from breeding towards targets 1 and 2 with low polyphenol contents and those that come from breeding towards target 3 with high polyphenol contents. Alcohols were related to the genotypes with breeding towards target 3, and compounds such as esters were related to the genotypes with breeding towards targets 1 and 2. Models computed using the soft independent modelling of class analogy (SIMCA) technique presented good sensitivity (93 %), specificity (91 %) and classification hits (96 %). However, the predictions computed by SIMCA (70 %) and the artificial neural network (ANN) (76 %) were low

URI:
http://hdl.handle.net/10651/39346
ISSN:
1936-9751; 1936-976X
DOI:
10.1007/s12161-016-0521-7
Patrocinado por:

This study was funded by Instituto Nacional de Innovación Agraria (grant number INIA-12-RTA2012-00118-C03-02) and by Ministerio de Economía y Competitividad (Spain) (grant number TIN2015-65069-C2-2-R)

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