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Antioxidant activity prediction and classification of some teas using artificial neural networks

Author:
Cimpoiu, Claudia, Cristea, Vasile-Mircea, Hosu, Anamaria, Sandru, Mihaela, Seserman, Liana
Source:
Food chemistry 2011 v.127 no.3 pp. 1323-1328
ISSN:
0308-8146
Subject:
antioxidant activity, flavanols, neural networks, prediction, tea
Abstract:
In order to characterise and to classify some teas a simple, rapid and economical method based on composition, antioxidant activity and artificial neural networks (ANNs) is proposed. For these purpose two types of ANN based applications have been developed: one for predicting the antioxidant activity and a second one for establishing the class of the teas. The complex relationship between the total antioxidant activity (AA) depending on the total flavonoids content (F), total catechins content (C) and total methyl-xanthines content (MX) of commercial teas was revealed by the first designed feed-forward ANN. Secondly, using a probabilistic ANN, successful tea classification in various classes (green tea, black tea and express black tea) was also performed.
Agid:
577297