Joint NMR and Solid-Phase Microextraction–Gas Chromatography Chemometric Approach for Very Complex Mixtures: Grape and Zone Identification in Wines

1H NMR to analyse the lipid profile in the glyceride fraction of different categories of Iberian dry-cured hams

The extraordinary organoleptic qualities of Iberian ham derive from the singular producing pig breed and from the traditional rearing conditions, both of which define its lipid content and composition. In this work ¹H NMR spectroscopy is used for the first time to analyse the lipid profile of Iberian hams as determinant of quality. Quantification of fatty acids is readily obtained from the spectra, with the monounsaturated fatty acids standing out, especially in the higher quality hams. Unprecedently, triacylglyceride hydrolysis products formed during the curing process can also be directly detected and quantified. Furthermore, chemometric analysis of the NMR data allows to classify Iberian hams according to the pig's crossbreed and feeding regime. Principal component analysis shows fatty acid unsaturation and triacylglyceride hydrolysis as discriminating variables. ¹H NMR spectroscopy has thus revealed as a convenient and powerful tool for the lipid analysis and classification of Iberian hams and for detection of fraud.

Verification of imported red wine origin into China using multi isotope and elemental analyses

Multi-isotope and multi-elemental analyses were performed on 600 red wine samples imported into China from 7 different countries and compared with Chinese wine. Carbon and oxygen isotopes and 16 elements were used to determine origin traceability. Our goal was to build a classification tool using data modeling that can verify the geographic origin of wines imported into China. Multivariate analyses of the isotopic and elemental data revealed that it is possible to determine the geographical origin for most imported wines with a high level of confidence (>90%). The results show that Artificial Neural Network method had a high discrimination accuracy and is more suitable than Discrimination Analysis and Random Forest methods when it comes to classifying wine origin on a global scale. In conclusion, stable isotope and trace element analyses followed by multivariate processing of the data is a fast and efficient technique suitable for global wine traceability.