ABSTRACT
Climate changes are inducing increased sugar levels of must, which produces negative effects on wine quality, as unbalanced wines with high degrees of alcohol. So, effective strategies to control the increase of sugar levels in must have been studied. One of them is the use of a membrane process, and this is applied in this work. The sugar level of white must from Verdejo (Vitis vinifera variety) was reduced using diverse membrane processes, and the effect of this fact on the volatile composition of the corresponding wines is studied. The study was carried out during three consecutive vintages. An important impact of the reduction of sugar levels of must on the volatile composition of the obtained wines was detected, which was due to some retention phenomena of aromatic and precursor compounds. To minimize the volatile composition modifications, an appropriate selection of the nanofiltration membrane must be done.
Subject(s)
Carbohydrates/analysis , Volatile Organic Compounds/analysis , Wine/analysis , Amino Acids/analysis , Filtration/methods , Food Handling/methods , Fruit/chemistry , VitisABSTRACT
Classical multivariate analysis techniques such as factor analysis and stepwise linear discriminant analysis and artificial neural networks method (ANN) have been applied to the classification of Spanish denomination of origin (DO) rose wines according to their geographical origin. Seventy commercial rose wines from four different Spanish DO (Ribera del Duero, Rioja, Valdepeñas and La Mancha) and two successive vintages were studied. Nineteen different variables were measured in these wines. The stepwise linear discriminant analyses (SLDA) model selected 10 variables obtaining a global percentage of correct classification of 98.8% and of global prediction of 97.3%. The ANN model selected seven variables, five of which were also selected by the SLDA model, and it gave a 100% of correct classification for training and prediction. So, both models can be considered satisfactory and acceptable, being the selected variables useful to classify and differentiate these wines by their origin. Furthermore, the casual index analysis gave information that can be easily explained from an enological point of view.
