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Artificial neural networks: a promising tool to evaluate the authenticity of wine

Author(s): G. Astray | J.X. Castillo | J.A. Ferreiro-Lage | J.F. Gálvez | J.C. Mejuto

Journal: Ciencia y Tecnología Alimentaria
ISSN 1135-8122

Volume: 8;
Issue: 1;
Start page: 79;
Date: 2010;
Original page

Keywords: Artificial neural networks | multilayer perceptron | DOC wine | sensory and physico | chemical parameters

Artificial Neural Networks (ANNs) have demonstrated to be a good tool to characterise, model and predict a great quantity of non-linear processes. In this article, we have used ANNs in the classification of different wine-making processes of the variety Vinhao (Vitis vinifera) for crops between the years 2000 and 2004. After being trained employing the data corresponding to years from 2000 to 2004, the ANNs demonstrated a root mean square error (RMSE) index between the real data and the calculated ones always lower than 0.14. Furthermore, their operation has been verified by using the previously reserved data of 10 famous wines. As a result, a RMSE index between observed and calculated data always lower than 0.17 was obtained for all of them, confirming the capacity of the ANN as a model of prediction of wine processes for this variety.
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