11. Prediction of wine sensorial quality by routinely measured chemical propertiesAdriána Bednárová, Roman Kranvogl, Darinka Brodnjak-Vončina, Tjaša Jug, 2014, original scientific article Abstract: The determination of the sensorial quality of wines is of great interest for wine consumers and producers since it declares the quality in most of the cases. The sensorial assays carried out by a group of experts are time-consuming and expensive especially when dealing with large batches of wines. Therefore, an attempt was made to assess the possibility of estimating the wine sensorial quality with using routinely measured chemical descriptors as predictors. For this purpose, 131 Slovenian red wine samples of different varieties and years of production were analysed and correlation and principal component analysis were applied to find inter-relations between the studied oenological descriptors. The method of artificial neural networks (ANNs) was utilised as the prediction tool for estimating overall sensorial quality of red wines. Each model was rigorously validated and sensitivity analysis was applied as a method for selecting the most important predictors. Consequently, acceptable results were obtained, when data representing only one year of production were included in the analysis. In this case, the coefficient of determination (R2) associated with training data was 0.95 and that for validation data was 0.90. When estimating sensorial quality in categorical form, 94 % and 85 % of correctly classified samples were achieved for training and validation subset, respectively.
Keywords: overall sensorial quality, prediction, Slovenian wine, artificial neural networks, multivariate data analysis
Published in DKUM: 03.04.2017; Views: 1602; Downloads: 403
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12. Characterization of Slovenian wines using multidimensional data analysis from simple enological descriptorsAdriána Bednárová, Roman Kranvogl, Darinka Brodnjak-Vončina, Tjaša Jug, Ernest Beinrohr, 2013, original scientific article Abstract: Determination of the product's origin is one of the primary requirements when certifying a wine's authenticity. Significant research has described the possibilities of predicting a wine's origin using efficient methods of wine components' analyses connected with multivariate data analysis. The main goal of this study was to examine the discrimination ability of simple enological descriptors for the classification of Slovenian red and white wine samples according to their varieties and geographical origins. Another task was to investigate the inter-relations available among descriptors such as relative density, content of total acids, non-volatile acids and volatile acids, ash, reducing sugars, sugar-free extract, $SO_2$, ethanol, pH, and an important additional variable - the sensorial quality of the wine, using correlation analysis, principal component analysis (PCA), and cluster analysis (CLU). 739 red and white wine samples were scanned on a Wine Scan FT 120, from wave numbers 926 $cm^{–1}$ to 5012 $cm^{–1}$. The applied methods of linear discriminant analysis (LDA), general discriminant analysis (GDA), and artificial neural networks (ANN), demonstrated their power for authentication purposes.
Keywords: wine authentication, enological descriptors, classification techniques, ANN
Published in DKUM: 10.07.2015; Views: 2903; Downloads: 67
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13. GRAPE ANTIOXIDANTS - INFLUENCE OF PROCESSING PARAMETERS ON THEIR CONTENT AND ACTIVITYIva Ružić, 2012, dissertation Abstract: Grapes and wine production residuals, containing grape skins, seeds and stems, represent important sources of phenolic compounds. Red wines are rich in phenolic antioxidants while white wines generally show lower (poly)phenolic content and antioxidant activity. The main difference in the production of white and red wines is the fermentation step. The fermentation of red grapes includes maceration, i.e. it takes place in both liquid and solid parts of the grape. In the case of white wines, the must is clarified before the fermentation starts, cultured yeasts are added to convert the must to wine and antioxidant sulfur dioxide is inserted to protect the wine.
The objective of the PhD research was to study antioxidant potential of white grape phenolics both in raw material and fermentation products. First, the standards of phenolic compounds commonly found in white grapes and wines were tested for their antioxidant and antiradical activity. All tested compounds except apigenin showed strong antioxidant and antiradical properties. Afterwards, conventional solid-liquid extraction (CE) and pressurized liquid extraction (PLE) of phenolic compounds from grape seeds were performed. The optimal extraction conditions were investigated and extracts were analyzed in order to determine their total phenolic content, individual phenolic compounds and antiradical potential. Two different drying methods (hot air and freeze drying) were applied to the seeds. Solvent efficiencies of water, ethanol and water-ethanol mixtures were compared at different temperatures. In addition, supercritical fluid extraction (SFE) with CO2 was investigated as the technique for the recovery of phenolic compounds and for the pretreatment of white grape seed samples. Both CE and PLE gave extracts rich in phenolic compounds with good antiradical properties and, generally, the best results were obtained with PLE at 130°C. At the end, the influence of maceration process on the content and the activity of grape phenolic antioxidants in white wines was studied. For such a purpose, six commercially available macerated white wines from Italy and Croatia were analyzed. In addition, eight non-macerated wines from the same region and variety were studied and compared to macerated wines. The experiments have shown that the maceration process increases the total phenolic content and antiradical activity of the wine. It enables the production of white wines rich in phenolic compounds and with strong antiradical properties in completely natural way using only the grapes and without addition of any chemical agents.
Keywords: white grapes, white wine, maceration, antioxidant activity, polyphenols, extraction, PLE, SFE.
Published in DKUM: 05.04.2012; Views: 2968; Downloads: 182
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