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Analysis of total phenolic, flavonoids, anthocyanins and tannins content in Romanian red wines: prediction of antioxidant activities and classification of wines using artificial neural networks.
Food Chem. 2014 May 01; 150:113-8.FC

Abstract

Wine is one of the most consumed beverages over the world containing large quantities of polyphenolic compounds. These compounds are responsible for quality of red wines, influencing the antioxidant activity, astringency, bitterness and colour, their composition in wine being influenced by the varieties, the vintage and the wineries. The aim of the present work is to build software instruments intended to work as data-mining tools for predicting valuable properties of wine and for revealing different wine classes. The developed ANNs are able to reveal the relationships between the concentration of total phenolic, flavonoids, anthocyanins, and tannins content, associated to the antioxidant activity, and the wine distinctive classes determined by the wine variety, harvesting year or winery. The presented ANNs proved to be reliable software tools for assessment or validation of the wine essential characteristics and authenticity and may be further used to establish a database of analytical characteristics of wines.

Authors+Show Affiliations

Babeş-Bolyai University, Faculty of Chemistry and Chemical Engineering, 11 Arany Janos, 400082 Cluj-Napoca, Romania.Babeş-Bolyai University, Faculty of Chemistry and Chemical Engineering, 11 Arany Janos, 400082 Cluj-Napoca, Romania.Babeş-Bolyai University, Faculty of Chemistry and Chemical Engineering, 11 Arany Janos, 400082 Cluj-Napoca, Romania. Electronic address: ccimpoiu@yahoo.com.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

24360427

Citation

Hosu, Anamaria, et al. "Analysis of Total Phenolic, Flavonoids, Anthocyanins and Tannins Content in Romanian Red Wines: Prediction of Antioxidant Activities and Classification of Wines Using Artificial Neural Networks." Food Chemistry, vol. 150, 2014, pp. 113-8.
Hosu A, Cristea VM, Cimpoiu C. Analysis of total phenolic, flavonoids, anthocyanins and tannins content in Romanian red wines: prediction of antioxidant activities and classification of wines using artificial neural networks. Food Chem. 2014;150:113-8.
Hosu, A., Cristea, V. M., & Cimpoiu, C. (2014). Analysis of total phenolic, flavonoids, anthocyanins and tannins content in Romanian red wines: prediction of antioxidant activities and classification of wines using artificial neural networks. Food Chemistry, 150, 113-8. https://doi.org/10.1016/j.foodchem.2013.10.153
Hosu A, Cristea VM, Cimpoiu C. Analysis of Total Phenolic, Flavonoids, Anthocyanins and Tannins Content in Romanian Red Wines: Prediction of Antioxidant Activities and Classification of Wines Using Artificial Neural Networks. Food Chem. 2014 May 1;150:113-8. PubMed PMID: 24360427.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Analysis of total phenolic, flavonoids, anthocyanins and tannins content in Romanian red wines: prediction of antioxidant activities and classification of wines using artificial neural networks. AU - Hosu,Anamaria, AU - Cristea,Vasile-Mircea, AU - Cimpoiu,Claudia, Y1 - 2013/11/04/ PY - 2012/07/24/received PY - 2013/10/15/revised PY - 2013/10/26/accepted PY - 2013/12/24/entrez PY - 2013/12/24/pubmed PY - 2014/8/26/medline KW - Antioxidant activities KW - Artificial neural networks KW - Romanian red wines KW - Total anthocyanins content KW - Total flavonoids content KW - Total phenolic content KW - Total tannins content SP - 113 EP - 8 JF - Food chemistry JO - Food Chem VL - 150 N2 - Wine is one of the most consumed beverages over the world containing large quantities of polyphenolic compounds. These compounds are responsible for quality of red wines, influencing the antioxidant activity, astringency, bitterness and colour, their composition in wine being influenced by the varieties, the vintage and the wineries. The aim of the present work is to build software instruments intended to work as data-mining tools for predicting valuable properties of wine and for revealing different wine classes. The developed ANNs are able to reveal the relationships between the concentration of total phenolic, flavonoids, anthocyanins, and tannins content, associated to the antioxidant activity, and the wine distinctive classes determined by the wine variety, harvesting year or winery. The presented ANNs proved to be reliable software tools for assessment or validation of the wine essential characteristics and authenticity and may be further used to establish a database of analytical characteristics of wines. SN - 1873-7072 UR - https://www.unboundmedicine.com/medline/citation/24360427/Analysis_of_total_phenolic_flavonoids_anthocyanins_and_tannins_content_in_Romanian_red_wines:_prediction_of_antioxidant_activities_and_classification_of_wines_using_artificial_neural_networks_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0308-8146(13)01602-6 DB - PRIME DP - Unbound Medicine ER -