Abstract
Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) combined with multivariate data analysis have been applied for the discrimination of 15 different Romanian wines (white, rosé and red wines), obtained from different origin-denominated cultivars. Principal component analysis and hierarchical cluster analysis was performed using different regions of FT-MIR spectra for all wines. The general fingerprint of wines was splitted in four characteristic regions, corresponding to phenolic derivatives, carbohydrates, amino acids and organic acids, which confer the wines quality and authenticity. By qualitative and quantitative evaluation of each component category, it was possible to discriminate each wine category, from red, to rosé and white colours, to dry, half-dry and half-sweet flavours. The multivariate data analysis based on absorption peaks from FT-MIR spectra demonstrated a very good, significant clustering of samples, based on the four main components: phenolics, carbohydrates, amino acids and organic acids. Therefore, the ATR-FT-MIR analysis proved to be a very fast, cheap and efficient tool to evaluate the quality and authenticity of wines, and to discriminate each wine category, based on their colour and sweetness, as consequence of their biological (cultivar) specificity.
Highlights
Grapes, grape juices and wines, consumed in moderate quantities, proved to contain a large number of phytochemicals with health benefits promoting effects (German and Walzem, 2000), from essential amino acids, minerals, organic acids, aromas, stilbenes, vitamins, and especially a large variety of pigments as well catechins, procyanidins and phenolic acid derivatives (Jackson, 2008).the quality and authenticity of the varietal origin of grapes and wines is of great interest to both the wine industry and the consumer (Cozzolino et al, 2003; Cozzolino et al, 2009)
The modern analytical methods to evaluate phenolic derivatives are usually based on reversed-phase highperformance liquid chromatography (HPLC), or another separation techniques such as gas chromatography or capillary electrophoresis, followed by ultraviolet (UV), electrochemical (EC), fluorescence (F) or mass spectrometric (MS) detection (Lorrain et al, 2013)
This study aims to investigate the use of mid-infrared (MIR) and multivariate data analysis techniques to classify Romanian wines produced from autochthonous cultivars
Summary
Grape juices and wines, consumed in moderate quantities, proved to contain a large number of phytochemicals with health benefits promoting effects (German and Walzem, 2000), from essential amino acids, minerals, organic acids, aromas, stilbenes (resveratrol), vitamins, and especially a large variety of pigments (flavonoids and anthocyanins) as well catechins, procyanidins and phenolic acid derivatives (Jackson, 2008).the quality and authenticity of the varietal origin of grapes and wines is of great interest to both the wine industry and the consumer (Cozzolino et al, 2003; Cozzolino et al, 2009). The main secondary metabolites found in grapes, with important roles in plant resistance to pathogens, allelopathy, oxidative stress and plant growth regulation, are the phenolic derivatives (Ogbemudia and Thompson, 2014). These derivatives include monophenolic compounds (phenolic acids, as free or derivatized as esters or glucosides, e.g. benzoic and cinnamic acid derivatives), and especially polyphenolics (anthocyanins and flavonoids, catechins, procyanidins, and their derivatives) keybiomarkers of grapes and wines’ quality, having antioxidant, antimutagenic, antiproliferative and antimicrobial properties (Guerrero et al, 2009). For wines direct analysis or solid-phase extraction followed by reversed phase HPLC-UV-VIS or HPLC-MS methods were used to analyze the phenolic
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