Classification of Spanish DO white wines according to their elemental profile by means of support vector machines
► Elemental contents as chemical descriptors to differentiate Spanish white wines. ► The elemental profile was determined by ICP-AES. ► Backward stepwise LDA selected chromium, silicon, sodium, strontium and manganese as the most discriminant variables. ► SVM allows 100% efficiency in the differenti...
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Veröffentlicht in: | Food chemistry 2012-12, Vol.135 (3), p.898-903 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | ► Elemental contents as chemical descriptors to differentiate Spanish white wines. ► The elemental profile was determined by ICP-AES. ► Backward stepwise LDA selected chromium, silicon, sodium, strontium and manganese as the most discriminant variables. ► SVM allows 100% efficiency in the differentiation between the considered appellations of origin.
Spanish white wines from four production areas protected by Appellation Control laws have been analysed by inductively coupled plasma optical emission spectrometry to determine the contents of aluminium, barium, boron, calcium, chromium, copper, iron, magnesium, manganese, nickel, phosphorous, potassium, silicon, sodium, strontium, sulphur and zinc. These elements were used as chemical descriptors in order to differentiate wines from different brands certified of origin. Kruskal–Wallis test was applied to highlight significant differences between the four considered classes and pattern recognition methods were applied to construct classification models. In this way, principal component analysis was used to visualise data trends and backward stepwise linear discriminant analysis was applied in order to reduce the number of input variables. The concentrations of chromium, manganese, silicon, sodium and strontium were used to construct a support vector machine classification model, obtaining a 100% of classification performance. |
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ISSN: | 0308-8146 1873-7072 |
DOI: | 10.1016/j.foodchem.2012.06.017 |