Use of Lead Isotopic Ratios as Geographical Tracer for Lambrusco PDO Wines

Tracing geographical origin of Lambrusco PDO wines using isotope ratios of oxygen, boron, strontium, lead and their elemental concentration

Wine identification is one of the most important aspects in the classification of wines and consumer protection. In particular, assuring wine authenticity is a crucial issue on which researchers are focusing on. This study aims to evaluate the feasibility of using chemical (B, Pb and Sr concentration) and isotopic compositions (δ¹¹B, ^20yPb/^20xPb, ⁸⁷Sr/⁸⁶Sr and δ¹⁸O) of wine samples to trace their geographic origins. Different PDO Lambrusco wines coming from a confined area of northern Italy were analyzed and all the isotopic systematics were monitored by using a multi collector inductively coupled plasma mass spectrometer (MC-ICP/MS).

The obtained results showed that boron isotope ratio measurements led to a satisfactory degree of accuracy and precision (measured value, n = 28, ¹¹B/¹⁰B of NIST SRM 951a equal to 4.04343 ± 0.00178, (u = 2s) with a certified value of 4.04362 ± 0.00136 (u = 2s). Furthermore, in the present study, it has been possible to highlight significant differences among samples by means of one-way analysis of variance (ANOVA) and post hoc Tukey-Kramer test. Finally, Principal Component Analysis (PCA) was also carried out in order to evaluate to which extent the different PDOs can be distinguished from each other, taking into account the whole set of geographical origin descriptors. Although δ¹¹B provided more sensitive information, the obtained results highlighted the important to consider the synergistic combination of all the investigated parameters to trace the different samples and the need to combine the obtained values with the same parameters evaluated in the soil, water and fertilizer as well.

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Multi-parameter approach was used to assess wine geographical origin.

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Validation of ¹¹B/¹⁰B measurements was accomplished by multicollector ICP/MS.

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¹¹B/¹⁰B, ⁸⁷Sr/⁸⁶Sr, ^20yPb/^20xPb, ¹⁸O/¹⁶O, and relative elemental content, were measured in Lambrusco PDO wines.

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Anova, Tukey-Kramer and multivariate (PCA) analysis was employed to investigate differences and similarities among samples.

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Geographic differentiation of PDO wines resulted to be based more on B and Sr variables than Pb and O ones.

Special Issue "Isotopic Techniques for Food Science"

Today, the analytical verification of food safety and quality together with authenticity and traceability plays a central role in food analysis [...].

13C NMR-Based Chemical Fingerprint for the Varietal and Geographical Discrimination of Wines

A fast, economic, and eco-friendly methodology for the wine variety and geographical origin differentiation using ¹³C nuclear magnetic resonance (NMR) data in combination with machine learning was developed. Wine samples of different grape varieties cultivated in different regions in Greece were subjected to ¹³C NMR analysis. The relative integrals of the ¹³C spectral window were processed and extracted to build a chemical fingerprint for the characterization of each specific wine variety, and then subjected to factor analysis, multivariate analysis of variance, and k-nearest neighbors analysis. The statistical analysis results showed that the ¹³C NMR fingerprint could be used as a rapid and accurate indicator of the wine variety differentiation. An almost perfect classification rate based on training (99.8%) and holdout methods (99.9%) was obtained. Results were further tested on the basis of Cronbach's alpha reliability analysis, where a very low random error (0.30) was estimated, indicating the accuracy and strength of the aforementioned methodology for the discrimination of the wine variety. The obtained data were grouped according to the geographical origin of wine samples and further subjected to principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The PLS-DA and variable importance in projection (VIP) allowed the determination of a chemical fingerprint characteristic of each geographical group. The statistical analysis revealed the possibility of acquiring useful information on wines, by simply processing the ¹³C NMR raw data, without the need to determine any specific metabolomic profile. In total, the obtained fingerprint can be used for the development of rapid quality-control methodologies concerning wine.