Wine characterisation according to geographical origin using analysis of mineral elements and rainfall correlation of oxygen isotope values

Abstract

The wine industry has developed rapidly; however, wine fraud is a potential risk for consumers. In China, methods for detecting wine authenticity are far from perfect. To reduce the risk of counterfeit wines, Inductively Coupled Plasma-Mass Spectrometry and Isotope Ratio Mass Spectrometry were used to geographically classify 104 wines from four major production areas. In this paper, the naturally distributed characteristics of thirty-eight mineral elements contents and the effect of rainfall on the oxygen isotope values in wine were investigated. The result of δ 18 O ranged from −13‰ to 7‰. The oxygen isotope of wine water in Northwest China is obviously more positive than that in South China. Linear discriminant analysis (LDA) showed 88.5% classification accuracy in training set and 81.7% in the cross-validation result. An artificial neural network (ANN) model determined origin of the wine with higher accuracy than LDA model. Furthermore, δ 18 O and Sr/Rb are important recognition elements in ANN, and the accuracy of region recognition can reach 90.9%. Thus, mineral elements and isotope ratios are effective in contributing to wine authenticity control in wine origin.

Evaluating the Chemical Hazards in Wine Production Associated with Climate Change

“…The δ 18 O correlated positively with Mg and negatively with the 87 Sr/ 86 Sr isotopic ratio. This positive relationship indicates the ability of Mg to influence the discrimination and classification of wine origins on the basis of maximum content [ 85 ]. A specific relationship was tested between the (D/H) I ratio and several elements associated with the investigation of wine origin and traceability, namely, Cd ( r = −0.41), Mn ( r = −0.50), and 206 Pb/ 207 Pb ( r = −0.40).…”

Dokha brand differentiation by elemental analysis measured by inductively coupled plasma–mass spectrometry

“…Other factors include the absorbability of the plant, chemical state of the soil, climate, microorganism activity, pesticide use, pollution, water, cultivation practices, and processing methods [11]. These elemental differences have been determined using various analytical techniques such as wavelength-dispersive X-ray fluorescence (WDXRF) [12][13][14][15][16][17], inductively coupled-mass spectrometry (ICP-MS) or ICP-optical emission spectrometry (OES) [9,10,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36], isotope ratio-mass spectrometry (IRMS) [23,28,29,31,37,38], and laser ablationinductively coupled-mass spectrometry (LA−ICP−MS) [39] and have been used for geographical origin determination [10,13,14,36,[39][40][41][42][43][44][45]…”