STATISTICAL METHODS FOR IMPROVING AUTHENTICATION …...Maintenance of databank Wine data Arbitration...

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Climatic and geographical dependence of H, C and O stable

isotope ratios of Italian wine

N. Dordevic, F. Camin, R. Wehrens, M. Neteler, G. J. Postma, L. M. C. Buydens,

Nikola Dordevic

Stable isotope ratios of wine

(D/H)1

(D/H)2

δ13C

δ18O

France

400

Germany

200

Italy

400

Spain

200 U. Kingdom

4

Austria

50

Greece

50

Luxembourg

4

Portugal

50

Wine data Maintenance of databank

Arbitration of disputes

Analysis of samples

Development and

validation of methods

Validation of data

Training

Malta

4

Slovakia

15

Slovenia

20

Hungary

50 Czech Rep.

20

Cyprus

10

Bulgaria

30

Romania

70

Wine Databank EC Reg. Nº 555/2008

Aim of the study

1. To evaluate relationships between wine (D/H)1,

(D/H)2, δ13C and δ18O and climatic and

geographic parameters of provenance areas.

2. To build a model able to explain relationships

between wine isotope ratios and climatic and

geographic parameters of provenance areas.

Materials and methods Variables Data

type Resolution

Source

Date of harvest static day Wine DB

Latitude static point www.findlatitudeandlogitude.com

Longitude static point www.findlatitudeandlogitude.com

Elevation static 20m Italian elevation model

Distance from the sea

static 250m Derived from elevation map in GIS

Amount of precipitation [mm/day]

dynamic 25km ECA&D, http://www.ecad.eu

Maximum daily temperature

dynamic 25km ECA&D

Minimum daily temperature

dynamic 25km ECA&D

Mean daily temperature

dynamic 25km ECA&D

δ18O of precipitation

static 37km Bowen et al. (2005)

δ2H of precipitation

static 37km Bowen et al. (2005)

• Official samples from the

Italian Wine Databank

from 2000 to 2010 are

considered.

• Explorative analyses and

linear modelling

Results (D/H)1

99.33

99.74

100.18

100.52

100.76

101.09

101.3

101.43

101.62

101.67

101.83

102.06

102.07

102.45

102.91

103.12

103.3

103.42

104.12

Results : explorative analyses

(D/H)1

(D/H)2

C13

O18

harvest date

latitude

longitude

elevation

distance

O18 MW

D/H MW

mean T

min T

max T

precipitation

(D/H

)1

(D/H

)2C13

O18

harvest

date

latitude

long

itude

elev

ation

distanc

e

O18

MW

D/H

MW

mea

n T

min T

max

T

prec

ipita

tion

-1.0

-0.5

0.0

0.5

1.0

Results : explorative analyses

-0.06 -0.04 -0.02 0.00 0.02 0.04 0.06

-0.0

6-0

.04

-0.0

20

.00

0.0

20

.04

0.0

6

PC1 (40.1%)

PC

2 (

18

.6%

)

-40 -20 0 20 40

-40

-20

02

04

0

(D/H)1(D/H)2C13

O18

harvest date

latitude

longitude elevation

distance

O18 MW(D/H) MW

meanT

min T

max T

precipitation

Results: linear modelling

Results: linear modelling Regression coefficients for the selected variables

Coefficient_size

Date of harvest

Distance to the sea

Elevation

Latitude

Longitude

Precipitation

Temperature

-0.4 -0.2 0.0 0.2

C13 O18

Date of harvest

Distance to the sea

Elevation

Latitude

Longitude

Precipitation

Temperature

DH1

-0.4 -0.2 0.0 0.2

DH2R2 = 0.42

R2 = 0.71 R2 = 0.24

R2 = 0.30

Conclusions

1. δ18O and (D/H)1 have the strongest relationship with

climate and location.

2. The dominant variables are latitude, δ18O and δ2H

of MW and temperature.

3. Models may be used in wine authenticity

assessments.

• F. Camin, N. Dordevic, R. Wehrens, M. Neteler, L. Delucchi, G.

Postma, L. Buydens (2014) Climatic and geographical

dependence of the H, C and O stable isotope ratios of Italian wine. Analytica Chimica Acta (accepted, in press).

Acknowledgment

Anti-Fraud Department of Italian Ministry of

Agricultural, Food and Forestry Policy, owner of the

Italian wine databank