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The wine sector in Italy is a significant contributor to the country's economy. Furthermore, Italy is renowned for producing some of the world's most excellent wines. For these reasons, the wine industry is susceptible to frauds, such as reporting false origin claims in labels. In this context, this paper aims to provide traceability and quality tool to recognise wines from different Italian regions, i.e. Calabria, Piemonte, Sicily and Veneto, from selected winemakers that reach the Top 10% in almost three international rankings. The multi-elemental analysis of soil and wine samples by ICP-MS and their chemometric treatments have identified Ni, Cs, Li, Ca, Ba, Pb, Rb, Sb, Fe and U as the most informative variables to reach optimal classification of samples. The analytical data have been used to develop an original managerial framework to leverage Pareto's Principle for effective brand-land management in the top wine segment. • Soil and wine samples from selected top vinery have been analysed by ICP-MS. • Chemometric treatment (PCA, variables selection, classification) were employed. • Ten variables were identified to recognise samples from geographical origin. • Pareto's Principle was applied on data for top wine management use. [ABSTRACT FROM AUTHOR]