A Classification Model for Wines Based on Elements Distribution and Geographical Origin

doi:10.7506/spkx1002-6630-201402041

Abstract

Abstract:

In this study, efforts were made to address the difficulty in identifying the geographic origin of imported wines to
China due to the complex sources. Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect the contents
of 41 elements in 100 samples of imported wines from Australia, Chile, France, Italy and Spain. Furthermore, analysis of
the experimental data by partial least squares (PLS) method and cluster analysis was carried out to establish a classification
model for tracing the geographical origin of the wines. After variable dimension expansion and variable selection, the PLS
model without redundant or non-significant variables showed a good correlation coefficient of cross validation with an
identification accuracy above 96%. For 110 additional new wine samples, including 99 from the five countries and 11 from
South Africa, satisfactory identification results were obtained when applying the analytical data to the model.

Key words: wine, elements, classification model, geographical origin

CLC Number:

TS261.7
O657

WANG Bing-tao, CHEN Bo, TU Xiao-ke, YAN Zhi, JIN Bao-hui, LIN Yan-kui, XIE Li-qi. A Classification Model for Wines Based on Elements Distribution and Geographical Origin[J]. FOOD SCIENCE, 2014, 35(2): 213-216.

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