An authentication study based on two different instrumental techniques, headspace solid-phase microextraction/ gas chromatography-mass spectrometry and mid-/near-infrared spectroscopies, was performed with a set of 75 samples representative of traditional Italian spirit “Grappa Geographical Indication (GI)” and other Italian spirits obtained by distillation of fruits or cereals. Chemometric classification methods were applied to the collected fingerprint profiles to build models which could allow differentiating GI Grappa from other distillates produced in the same geographical areas. Samples were classified by Sequential and Orthogonalized Partial Least Squares- Linear Discriminant Analysis (SO-PLS-LDA) and Sequential and Orthogonalized Covariance Selection-Linear Discriminant Analysis (SO-CovSel-LDA). The total classification rate of 100% obtained by SO-PLS-LDA highlighted that targeted analysis of flavour profiles combined with IR analysis could be used to assess the authenticity of GI Grappa samples. Hence, it indicates multi-block strategies may help to protect the Geographical Indication products from possible label frauds by verifying whether samples comply with statements concerning the origin as stated in the product specification.

Grappa and Italian spirits: Multi-platform investigation based on GC–MS, MIR and NIR spectroscopies for the authentication of the Geographical Indication

Biancolillo, Alessandra
2020

Abstract

An authentication study based on two different instrumental techniques, headspace solid-phase microextraction/ gas chromatography-mass spectrometry and mid-/near-infrared spectroscopies, was performed with a set of 75 samples representative of traditional Italian spirit “Grappa Geographical Indication (GI)” and other Italian spirits obtained by distillation of fruits or cereals. Chemometric classification methods were applied to the collected fingerprint profiles to build models which could allow differentiating GI Grappa from other distillates produced in the same geographical areas. Samples were classified by Sequential and Orthogonalized Partial Least Squares- Linear Discriminant Analysis (SO-PLS-LDA) and Sequential and Orthogonalized Covariance Selection-Linear Discriminant Analysis (SO-CovSel-LDA). The total classification rate of 100% obtained by SO-PLS-LDA highlighted that targeted analysis of flavour profiles combined with IR analysis could be used to assess the authenticity of GI Grappa samples. Hence, it indicates multi-block strategies may help to protect the Geographical Indication products from possible label frauds by verifying whether samples comply with statements concerning the origin as stated in the product specification.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/145916
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