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Analysis of port wines using the electronic tongue

Analysis of port wines using the electronic tongue. Alisa Rudnitskaya 1 , Ivonne Delgadillo 2 , Andrey Legin 1 , Silvia Rocha 2 , Anne-Marie Da Costa 2 , Tomás Simoes 3 1 Chemistry Department, St. Petersburg University, Russia; www.elecronictongue.com

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Analysis of port wines using the electronic tongue

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  1. Analysis of port wines using the electronic tongue Alisa Rudnitskaya1, Ivonne Delgadillo2, Andrey Legin1, Silvia Rocha2, Anne-Marie Da Costa2, Tomás Simoes3 1Chemistry Department, St. Petersburg University, Russia; www.elecronictongue.com 2Chemistry Department, University of Aveiro, Portugal3Instituto do Vinho do Porto, Porto, Portugal

  2. Port wine making procedure A. Rudnitskaya et al St. Petersburg University

  3. Port wine producing region A. Rudnitskaya et al St. Petersburg University

  4. Port wine producing region A. Rudnitskaya et al St. Petersburg University

  5. Port wine styles Ruby Bottle aged Tawny Cask aged Tawny, Tawny reserve (min 6 years in the cask) Ruby, Ruby reserve (2-3 years in the cask) Tawny with an Indication of Age (10, 20, 30 or 40 years in the cask) LBV (4-6 years in the cask) Colheita (min 7 years in the cask) Vintage (2-3 years in the cask) A. Rudnitskaya et al St. Petersburg University

  6. Purpose of the study Development of the rapid analytical methodology for the assessment of the port wine age • Evaluation of the electronic tongue multisensor system (ET) for the determination of the port wine age • Comparison between ET and conventional chemical analysis data for the determination of the port wine age • Evaluation of the orthogonal signal correction for the data filtering A. Rudnitskaya et al St. Petersburg University

  7. Samples 146 samples of port wine, in particular, wines aged in oak casks for 10, 20, 30 and 40 years, Vintage, LBV and Colheita (harvest) wines of age varying from 2 to 70 years. All port wine samples together with chemical analysis results were obtained from Instituto do Vinho Do Porto Measurements Electronic tongue Sensor array of 28 potentiometric chemical sensors with both chalcogenide glass and polymeric membranes Direct measurements without sample preparation Chemical analysis using conventional analytical techniques (provided by Instituto de Vinho de Porto) 32 parameters including content of sugar (ºBé), ashes, reducible sugar, total SO2 and sulphates, tartaric and malic acids, alcohols (ethanol, methanol, glycerol, 1 and 2-butanol, 1-propanol, isopropanol, amyl and allyl alcohols), ethanal, ethyl acetate, volatile and total acidity, Foline index, density, dry extract, etc. Experimental A. Rudnitskaya et al St. Petersburg University

  8. ExperimentalData processing • PCA • Recognition of samples and data exploration • PLS regression • Calibration models for prediction of port wine age • ET and chemical analysis data • Raw and OSC filtered data • Test set validation, 1/3 of the samples were used as tests • OSC • Applied for filtering of ET and chemical analysis data • Software used • Unscrambler v. 7.8 by CAMO AS • SIMCA-P v.11.0 by Umetrics A. Rudnitskaya et al St. Petersburg University

  9. Orthogonal Signal Correction • Wold S, Antti H, Lindgren F, Öhman J, Chemometrics Intell Lab. Syst. 44 (1998) 175-185 • Aim – removal of variation in X that is not correlated with Y prior to modeling • to = Xwo, which is orthogonal to Y AND provides good modeling and prediction of X po' = to‘X XOSC = X – Σto*po‘ A. Rudnitskaya et al St. Petersburg University

  10. PCAChemical analysis data • Good correlation between chemical analysis data and port wine age • Clustering according to port wine type – good separation between blended tawnies and LBV and vintage wines A. Rudnitskaya et al St. Petersburg University

  11. PCAET data • No good separation of port wines according to their age • Clustering according to port wine type • Significant temporary drift in the data A. Rudnitskaya et al St. Petersburg University

  12. PCs in the model - 4 RMSEC 4.8 RMSEP 5.8 Prediction of the port wine agePLS regression on the raw data ET Chemical analysis PCs in the model - 2 RMSEC 5.3 RMSEP 5.4 A. Rudnitskaya et al St. Petersburg University

  13. OSC filtering of the data A. Rudnitskaya et al St. Petersburg University

  14. OSC filtering of the dataRMSEP ET data Chemical analysis data A. Rudnitskaya et al St. Petersburg University

  15. Effect of OSC filtering of ET data A. Rudnitskaya et al St. Petersburg University

  16. Effect of OSC filtering on ET data A. Rudnitskaya et al St. Petersburg University

  17. Conclusions • Port wine age can be predicted using both electronic tongue and conventional chemical analysis data with the same precision of about 5 years. • Electronic tongue response has shown a temporary drift in port wines, especially pronounced during first days of measuring session • Data pretreatment using OSC was favorable for ET data successfully removing time dependence and producing improved calibration models • Port wine sample can be separated according to their types using both ET and conventional chemical analysis data. A. Rudnitskaya et al St. Petersburg University

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