Rapid Authentication of White Wines. Part 1: Classification by Designation of Origin
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FOOD ANALYSIS MARÍA J. MARTELO-VIDAL, MANUEL VÁZQUEZ* *Corresponding author University of Santiago de Compostela, Faculty of Veterinary Science, Department of Analytical Chemistry, 27002 Lugo, Spain Manuel Vazquez Rapid authentication of white wines. Part 1: Classification by designation of origin KEYWORDS: designation of origin, UV-VIS, NIR, spectral data, classification Artificial neural networks (ANN) combined with ultraviolet (UV), visible (VIS) and near-infrared (NIR) spectral Abstractanalysis were evaluated as a rapid method to classify wines. Wines belong to Designation of Origin (DO) Rías Baixas, Ribeira Sacra, Monterrei, Ribeiro and Valdeorras (Northwest of Spain) were classified. Classification inside a DO were also studied for subzones of DO Rías Baixas. Results showed that DO Ribeiro, Valdeorras, Monterrei and Ribeira Sacra were 100 percent classified using the ANN architectures developed. Rías Baixas were the DO with a worst classification. Inside DO Rías Baixas, Rosal was 100 percent classified. Results showed the feasibility of applying ANN and UV-VIS-NIR analysis to the authentication of DO. INTRODUCTION ANN can provide capacity of solve supervised and unsupervised problems, such as clustering and modelling of data. There is Wine composition depends of soil, culture conditions, different ANN architectures and strategy of solving data. ANN is microclimate, macroclimate and winemaking techniques (1, a flexible modelling method. They can use linear and non-linear 2). The wine analysis is not an easy task due to its heterogeneity functions in processing units (15). The construction of ANN is not and complexity. The economic value of wine made the wine significantly affected by the sample number in each category authentication or classification an important task worldwide. and data structure (16). The ANN consists of interconnected This importance is related to quality, prevention of adulterations, neurons with input layers, one or more hidden layers and output food safety and control of winemaking process. Wine quality layers (14) and these neurons are developed through one or in import-export markets should be also guaranteed (3). more forms of training (17). Winemakers and consumers demand analytical low-cost and Wine varieties and wines from different regions have been effective tools to determine the quality of wine (4). successfully classified using near-infrared (NIR) spectroscopy The controlled designation of origin (DO) is the name of a and chemometric tools (7). However, there are scarce studies region or place recognized to produce foods with special using UV-VIS-NIR spectroscopic techniques and ANN tools characteristic regarding other places and with different for the classification between wines of close DO or wines of manufacture and/or materials (5, 6). Wines produced in regions subzones inside a DO. with DO have Regulatory Councils that control the growing The aim of this work was to evaluate the feasibility of using UV- and production conditions (2, 7). The authentication of wines VIS-NIR spectroscopic techniques combined with ANN to classify from DO is an important task for DO Regulatory Councils. They wines. As a case of study, it was studied wines from Spanish DO have also the difficult task to determine the origin between the (Rías Baixas, Ribera Sacra, Ribeiro, Valdeorras and Monterrei). production subzones inside a DO (8). The feasibility of classifying wines from subzones of DO Rías Different classification methods have been applied in Baixas (Condado, Salnés, Rosal and Ribeira de Ulla) were also analytical chemistry, such as factor analysis, cluster analysis, evaluated. linear discrimination analysis (LDA) (7, 9), Partial least squares regression (PLS) and soft independent modelling of class analogy (SIMCA) (10, 11). MATERIALS AND METHODS The Artificial Neural Networks (ANN) is a model of a biological neural network and brain functioning for data processing, which Wine samples exhibits the main capabilities of the real neuron system (12). White wines from Galician (northwest of Spanish) were studied. Each neuron is connected to certain neighbours with varying Commercial monovarietal white wines from DO Rías Baixas, coefficients of connectivity that represent the strengths (the Ribeira Sacra, Ribeiro, Valdeorras and Monterrei of 2009 and 2012 weights) of these connections (13-15). vintage obtained from different local markets were analyzed The use of ANN is increasing for many chemical applications. The (Table 1). All samples were stored at 5ºC until analysis (18). 44 Agro FOOD Industry Hi Tech - vol 25(5) - September/October 2014.