Madeira wine ageing prediction based on different analytical techniques: UV-vis, GC-MS, HPLC-DAD

摘要

The present work aims to analyze the feasibility of different analytical measurement procedures for Madeira wine ageing prediction. In order to properly identify and quantify the chemical compounds qualified for characterizing wine evolution during the ageing period, chromatographic and spectroscopic analyses were carried out. Twenty-six samples, representative of ten harvest years and covering an ageing period of 20 years, were analyzed in terms of their volatile and phenolic composition, as well as characterized in terms of absorbance measurements in the UV and Visible region. Then, multivariate prediction models were established by applying PLS regression to each chemical data set, after which they were compared in terms of their ageing prediction ability. The optimum number of PLS dimensions to consider in each estimated model was obtained based on the minimization of the root mean squared error of Monte Carlo validation. With such estimated models, the prediction interval estimates based on the bootstrap percentile approach were also computed for the available samples, in order to test model's prediction ability, once each sample is successively removed from the data set. Our analysis shows that Madeira wine age, produced from a known grape variety, can be predicted with good accuracy from its volatile and phenolic composition, as well as from UV-vis absorbance measurements. The PLS models estimated are able to predict wine age with a root mean square error of 0.9, 1.1, and 1.4 years, respectively. The sample-specific prediction intervals computed also allowed for the analysis of differences between observed and predicted values, and confirmed the interesting wine age prediction abilities of the proposed methodologies. A compromise between model accuracy and cost of analysis can be established in order to decide which methodology to use, according to the particular application scenario, as the more time-consuming and complex techniques (GC-MS and HPLC-DAD) are also those leading to more accurate results, but UV-vis also enabled us to come up with acceptable age predictions.