Differentiation of 'two Andalusian DO 'fino' wines according to their metal content from ICP-OES by using supervised pattern recognition methods

被引:58
作者
Alvarez, Mercedes
Moreno, Isabel M.
Jos, Angeles
Camean, Ana M.
Gustavo Gonzalez, A.
机构
[1] Univ Seville, Fac Pharm, E-41012 Seville, Spain
[2] Univ Seville, Fac Chem, E-41012 Seville, Spain
关键词
metal content; fino wines; artificial neural networks; linear discriminant analysis; Spain;
D O I
10.1016/j.microc.2007.05.007
中图分类号
O65 [分析化学];
学科分类号
070302 [分析化学]; 081704 [应用化学];
摘要
The metal content (Ca, Mg, Sr, Ba, K, Na, P, Fe, Al, Mn, Cu and Zn) of several 'fine' wines belonging to two Andalusian Denomination of Origin (DO) was determined by ICP-OES. Metal concentrations were selected as chemical descriptors for discrimination, because they play a primary role in the discrimination due to its correlation with soil nature, geographical origin and grape variety. The two studied Andalusian DO were the Jerez-Xeres-Sherry & Manzanilia-Sanlucar de Barrameda (class D) and the Condado de Huelva (class C). Linear Discriminant Analysis (LDA) and procedures based on Artificial Neural Networks (ANN) leads to a perfect separation of classes, especially when applying Multi Layer Perceptrons ANN trained by back-propagation. (C) 2007 Published by Elsevier B.V.
引用
收藏
页码:72 / 76
页数:5
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