Creating Value for the Montepulciano D’Abruzzo PDO Chain: A Pilot Study of Supply Chain Traceability Using Multi-Elemental and Chemometrics Analysis of Wine and Soil

**Spårning av vinkvalitet löser autentisering för italiensk PDO-region** Montepulciano d'Abruzzo-producenter kan nu verifiera sitt ursprung genom kemisk fingeravtryck istället för pappersbaserad dokumentation. Forskarteamet analyserade 63 element och isotopförhållanden i vin och jord från Abruzzo-regionen med högupplöst massa-spektrometri. Fyra markörvariabler — molybden, bly-isotoper, fosfor och strontium-isotoper — visade sig kunna klassificera producenter med 100 procents noggrannhet via maskinlärning. Detta möjliggör digital transparens längs värdekedjan utan att förfalska administrativa kriterier. För leverantörsval och compliance-verifiering eliminerar metoden tvister om geografisk ursprungsmärkning. PDO-kollektiv kan implementera systemet för att stärka konkurrenskraft mot massproducerade alternativ. San Raffaele-universitetet i Rom samarbetade med svenska Luleå tekniska universitet för analysen. Pilotprojektet visar vägen för europeiska skyddade beteckningar att digitalisera autentiseringsprocesser.

<p>This study aims to enhance the value of the Montepulciano d’Abruzzo PDO supply chain by integrating multi-elemental and isotopic profiling with chemometric analysis. The objective is to establish a pilot study for origin authentication, supporting strategic, managerial, and regulatory decision-making for stakeholders in the wine sector. Wine and soil samples from producers in the Abruzzo region were analyzed for 63 elements and selected isotopic ratios using HR-ICP-MS and MC-ICP-MS. Exploratory data analysis, including PCA and clustering, was employed to investigate intrinsic data structure. Variable selection techniques identified the most discriminant markers, and multiple classification models were tested to assess producer-level differentiation. The combined elemental and isotopic dataset showed strong intrinsic structure. Four variables—Mo, 208Pb/206Pb, P, and 87Sr/86Sr—emerged as key discriminants. Quadratic Discriminant Analysis and Artificial Neural Networks achieved 100% accuracy in classifying samples by producer. The results demonstrate that integrating multi-elemental and isotopic data with chemometric tools offers a pilot approach to authenticate wine origin and enhance transparency across the PDO supply chain. Beyond scientific innovation, this study provides a pilot decision support model that can strengthen competitive differentiation, regulatory compliance, and sustainable territorial development, highlighting opportunities for digital transformation in PDO management.</p>