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Repositorio de la Universidad de Oviedo. > Producción Bibliográfica de UniOvi: RECOPILA > Artículos >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/39346

Title: Characterization of Volatile Compounds in New Cider Apple Genotypes Using Multivariate Analysis
Author(s): Pello Palma, Jairo
Mangas Alonso, Juan José
Dapena de la Fuente, Enrique
González Álvarez, Jaime
Díez Peláez, Jorge
Gutiérrez Álvarez, María Dolores
Arias Abrodo, Pilar
Keywords: Cider apple
Breeding
Chemometric
HS-GC
SPME
Volatile compounds
Issue date: Dec-2016
Publisher: Springer
Publisher version: http://dx.doi.org/10.1007/s12161-016-0521-7
Citation: Food Analytical Methods, 9(12), p. 3492–3500 (2016); doi:10.1007/s12161-016-0521-7
Format extent: 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
URI: http://hdl.handle.net/10651/39346
ISSN: 1936-9751
1936-976X
Sponsored: 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)
Project id.: INIA-12-RTA2012-00118-C03-02
TIN2015-65069-C2-2-R
Appears in Collections:Química Física y Analítica
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