Literature DB >> 25214133

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

Claudia Cimpoiu1, Vasile-Mircea Cristea2, Anamaria Hosu2, Mihaela Sandru2, Liana Seserman2.   

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.
Copyright © 2011 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Antioxidant activity; Artificial neural networks; Catechins; Flavonoids; Methyl-xanthines; Tea

Year:  2011        PMID: 25214133     DOI: 10.1016/j.foodchem.2011.01.091

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


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