Classification of red wines using suitable markers coupled with multivariate statistic analysis

•Methodologies for classification of five authentic red wine varieties are reported.•Anthocyanins, organic acids, NMR fingerprints, isotopic variables discriminate wines.•A control wine set was used in order to validate the proposed statistic models.•There is great potential to use this data combina...

Full description

Saved in:
Bibliographic Details
Published in:Food chemistry 2016-02, Vol.192, p.1015-1024
Main Authors: Geana, Elisabeta Irina, Popescu, Raluca, Costinel, Diana, Dinca, Oana Romina, Ionete, Roxana Elena, Stefanescu, Ioan, Artem, Victoria, Bala, Camelia
Format: Article
Language:English
Subjects:
Amino Acids - analysis
Anthocyanins
Anthocyanins - analysis
Butylene Glycols
Carboxylic Acids - analysis
Discriminant Analysis
Humans
Isotopes - analysis
Isotopic ratio
Magnetic Resonance Spectroscopy
Multivariate Analysis
Multivariate statistics
NMR fingerprints
Organic acids
Oxalic Acid
Romania
Vitis - chemistry
Wine - analysis
Wine - classification
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Methodologies for classification of five authentic red wine varieties are reported.•Anthocyanins, organic acids, NMR fingerprints, isotopic variables discriminate wines.•A control wine set was used in order to validate the proposed statistic models.•There is great potential to use this data combination for wine control. Methodologies for chemometric classification of five authentic red wine varieties from Murfatlar wine center, Romania, young and aged are reported. The discriminant analysis based on several anthocyanins, organic acids, 13C/12C, 18O/16O and D/H isotopic ratios, 1H and 13C NMR fingerprints revealed a very satisfactory categorization of the wines, both in terms of variety and vintage, thus illustrating the validity of selected variables for wine authentication purposes. LDA applied to the combined data shows 85.7% classification of wines according to grape variety and 71.1% classification of wines according to vintage year, including a control wine set for each categorization, thus allowing an accurate interpretation of the data. Thereby, anthocyanins, certain anthocyanin ratios, oxalic, shikimic, lactic, citric and succinic acids, sugars like glucose, amino acids like histidine, leucine, isoleucine and alanine, and also 2,3-butanediol, methanol, glycerol and isotopic variables were significant for classification of wines.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2015.07.112