Cider apple pomace as a source of nutrients: Evaluation of the polyphenolic profile, antioxidant and fiber properties after drying process at different temperatures.

Apple pomace, the by-product of the cider industry, contains a high content of antioxidant compounds and dietary fiber. Drying would allow its preservation for a later use. The aim of this study was to evaluate the effect of the drying temperature on the drying kinetics, antioxidant properties and the fiber characteristics. For this, drying experiments were performed at different temperatures (40-120 °C). The increase in temperature enhanced the drying rate, as was shown by the effective diffusivity and mass transfer coefficient identified by modelling. The influence of temperature was quantified through the activation energy (38.21 kJ/mol). Regarding the retention of antioxidant properties, the best results were found at 80-100 °C while 40-60 °C was the best temperature range for the fiber characteristics. Therefore, 80 °C could be an adequate temperature for drying of cider apple pomace, as it represents a good balance between kinetics, and antioxidant and fiber properties.

Chemical characterization of asturian cider.

Ninety-four samples of Asturian natural cider were analyzed for titratable and volatile acidities, pH, alcoholic, total polyphenol, and acidic polysaccharide contents, nonvolatile acids, polyalcohols, residual sugars, and major volatile compounds. A partial least-squares regression analysis (PLR-1) was performed to correlate the chemical composition and the origin of the raw material, the cider samples being grouped into two categories: an "odd" class, cider made from foreign apples (1995 and 1997), and an "even" class, ciders made from Asturian apples (1996 and 1998). The mathematical model has a multiple linear correlation coefficient of 80%.

Study of the phenolic profile of cider apple cultivars at maturity by multivariate techniques.

Phenolic compounds in 46 Spanish cider apple varieties were determined by RP-HPLC with direct injection. Several pattern recognition procedures, including principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares (PLS-1), were applied to the data in an attempt to classify the samples into bitter and nonbitter categories. Reliable decision rules were obtained by both LDA and PLS-1. LDA achieved 91.3 and 85.7% correct classification respectively, for internal and external evaluation of the model.

Analysis of polysaccharides in cider: their effect on sensory foaming properties.

A feasible spectrophotometric method for determining acidic and neutral polysaccharides in cider is described, and the advantages of this method are examined with respect to precision, accuracy, and detection and quantitation limits. The concentration of nonvolatile and volatile components in cider, together with chemometric techniques such as principal component analysis (PCA), soft independent modeling of class analogy (SIMCA), and partial least squares (PLS), allowed us to typify the ciders on the basis of their foaming properties. Acidic polysaccharide and 1-propanol were the most relevant variables for this purpose.