Characterization of cider apple fruits according to their degree of ripening. A chemometric approach.

A chemometric study was carried out in order to typify cider apples according to their degree of ripening. Several chemical variables (sugars, organic acids, amino acids, polyphenols, and pectins) were analyzed using HPLC and FIA methods. Univariate data treatment was not sufficient to allow the apple varieties to be differentiated according to their stage of ripening. Two linear combinations of original variables, ascertained by principal component analysis (PCA), provided an adequate data structurization. To classify apples by their degree of ripening, a mathematical decision rule was established with a prediction capacity of 85% using a LDA method; the most relevant variables in the canonical function ascertained by LDA were sugars, pectins, malic acid, glycine, serine, valine, and glutamic acid. The use of the PLS-2 algorithm demonstrated the influence of the ripening process on the chemical composition of the fruits (R2: 91.7%) and furthermore allowed authors to differentiate apple varieties according to their degree of ripening