A capillary sieving electrophoretic method for protein analysis and molecular weight determination was used to characterize ciders from Asturias, northern Spain. The total protein content (Bradford method) and the foam parameters (Bikerman method) were also analyzed to complete this characterization. The polypeptide profile, based on the molecular weight, together with exploratory and classification techniques, that is, principal component analysis (PCA) or linear discriminant analysis (LDA), allowed ciders to be differentiated on the basis of their foam assessment and the apple juice extraction technology used in the cidermaking process. In addition, the application of correlation analysis, that is, canonical correlations (CCA) or partial least-squares (PLS), revealed that the proteins with higher molecular weight were more relevant with respect to cider foamability. PLS analysis also provided a mathematical equation that is able to predict the stabilization time of foam from the polypeptide profile of the cider, because this is the foam parameter most influenced by these compounds.
A chromatographic method for the separation of volatile compounds in Asturian cider apple juices has been developed. For this separation purpose, a monocationic imidazolium-based ionic liquid bearing a reactive terminal iodine atom was synthesized by a quaternization-anion exchange chemical sequence. Next, the gas chromatography (GC) stationary phase was prepared by covalently linking the imidazolium monolith to the reactive silanol groups of the inner capillary wall at 70 °C. This coated GC column exhibited good thermal stability (290 °C), as well as good efficiency (2000 plates/m) in the separation of volatile compounds from Asturian apple cider juices, and was characterized using the Abraham solvation parameter model. The intra-day and inter-day precision of the chromatographic method was evaluated, obtaining relative standard deviations from 3.7 to 12.9% and from 7.4 to 18.0%, respectively. Furthermore, recoveries from 82.5 to 122% were achieved. Graphical Abstract Covalent bonding of an ionic liquid to inner column wall led to a great improvement of the separation efficiencies of stationary phases in gas chromatography.
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.
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