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

Elisabeta Irina Geana; Raluca Popescu; Diana Costinel; Oana Romina Dinca; Roxana Elena Ionete; Ioan Stefanescu; Victoria Artem; Camelia Bala

doi:10.1016/j.foodchem.2015.07.112

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

Food Chem. 2016 Feb 1:192:1015-24. doi: 10.1016/j.foodchem.2015.07.112. Epub 2015 Jul 23.

Authors

Elisabeta Irina Geana¹, Raluca Popescu², Diana Costinel², Oana Romina Dinca², Roxana Elena Ionete², Ioan Stefanescu², Victoria Artem³, Camelia Bala⁴

Affiliations

¹ National R&D Institute of Cryogenics and Isotopic Technologies - ICSI Rm. Valcea, 4 Uzinei St., 240050 Rm. Valcea, Romania; Department of Analytical Chemistry, University of Bucharest, 4-12 Regina Elisabeta Blvd., 030018 Bucharest, Romania.
² National R&D Institute of Cryogenics and Isotopic Technologies - ICSI Rm. Valcea, 4 Uzinei St., 240050 Rm. Valcea, Romania.
³ Research Station for Viticulture and Oenology Murfatlar, Murfatlar, Romania.
⁴ Department of Analytical Chemistry, University of Bucharest, 4-12 Regina Elisabeta Blvd., 030018 Bucharest, Romania; LaborQ, University of Bucharest, 4-12 Regina Elisabeta Blvd., 030018 Bucharest, Romania. Electronic address: camelia.bala@g.unibuc.ro.

PMID: 26304442
DOI: 10.1016/j.foodchem.2015.07.112

Abstract

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, (13)C/(12)C, (18)O/(16)O and D/H isotopic ratios, (1)H and (13)C 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.

Keywords: 2,3-Butanediol (PubChem CID: 262); Alanine (PubChem CID: 5950); Anthocyanins; Beta-d-glucose (PubChem CID: 64689); Citric acid (PubChem CID: 611); Histidine (PubChem CID: 6274); Isotopic ratio; Leucine (PubChem CID: 6106); Malvidin-3-O-glucoside (PubChem CID: 5464047); Multivariate statistics; NMR fingerprints; Organic acids; Shikimic acid (PubChem CID: 8742); Succinic acid (PubChem CID: 1110); Wine classification.

Publication types

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

MeSH terms

Amino Acids / analysis
Anthocyanins / analysis
Butylene Glycols
Carboxylic Acids / analysis
Discriminant Analysis
Humans
Isotopes / analysis
Magnetic Resonance Spectroscopy
Multivariate Analysis*
Oxalic Acid
Romania
Vitis / chemistry
Wine / analysis*
Wine / classification*

Substances

Amino Acids
Anthocyanins
Butylene Glycols
Carboxylic Acids
Isotopes
2,3-butylene glycol
Oxalic Acid