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

被引：67
|
作者：
Cimpoiu, Claudia [1 ]
Cristea, Vasile-Mircea [1 ]
Hosu, Anamaria [1 ]
Sandru, Mihaela [1 ]
Seserman, Liana [1 ]
机构：
[1] Univ Babes Bolyai, Fac Chem & Chem Engn, Cluj Napoca 400082, Romania
来源：
FOOD CHEMISTRY | 2011年 / 127卷 / 03期
关键词：
Tea; Flavonoids; Catechins; Methyl-xanthines; Antioxidant activity; Artificial neural networks; CAFFEINE; CATECHINS; GREEN; BLACK; WINES; HPLC; CHROMATOGRAPHY; POLYPHENOLS; THEOBROMINE; SUPPORT;
D O I：
10.1016/j.foodchem.2011.01.091
中图分类号：
O69 [应用化学];
学科分类号：
081704 ;
摘要：
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. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1323 / 1328
页数：6
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