Stable isotope ratio analysis of the major bioelements (δ2H, δ13C, δ15N, δ18O, δ34S), considered for the first time as a whole, was used to attempt a geographical characterization of red garlic (Allium sativum L.) cultivated throughout different Italian territories (Abruzzo, Lazio and Sicily). Up to now, no official methods are available to determine the geographical origin of this type of product. In this context, the Isotope Ratio Mass Spectrometry method (IRMS) represents a powerful analytical technique. The characteristic ranges of variability of the five isotope ratios in 56 red Italian garlic samples are here presented as well as their relationships. The geographical origin has some influence over the different ratios, although their data distribution shows some overlap when Principal Component Analysis (PCA) is applied. In spite of the relative closeness of the sampling sites, a model with very good predictive performance of the geographical classification was achieved byLinear Discriminant Analysis (LDA) and k-nearest neighbours (k-NN) method. Moreover, preliminary class modelling based on Soft Independent Modelling of Class Analogy (SIMCA) supports the ability of stable isotope ratios analysis for the geographical traceability of garlic.

Geographical discrimination of garlic (Allium Sativum L.) based on Stable isotope ratio analysis coupled with statistical methods: The Italian case study

Pianezze S.;
2019-01-01

Abstract

Stable isotope ratio analysis of the major bioelements (δ2H, δ13C, δ15N, δ18O, δ34S), considered for the first time as a whole, was used to attempt a geographical characterization of red garlic (Allium sativum L.) cultivated throughout different Italian territories (Abruzzo, Lazio and Sicily). Up to now, no official methods are available to determine the geographical origin of this type of product. In this context, the Isotope Ratio Mass Spectrometry method (IRMS) represents a powerful analytical technique. The characteristic ranges of variability of the five isotope ratios in 56 red Italian garlic samples are here presented as well as their relationships. The geographical origin has some influence over the different ratios, although their data distribution shows some overlap when Principal Component Analysis (PCA) is applied. In spite of the relative closeness of the sampling sites, a model with very good predictive performance of the geographical classification was achieved byLinear Discriminant Analysis (LDA) and k-nearest neighbours (k-NN) method. Moreover, preliminary class modelling based on Soft Independent Modelling of Class Analogy (SIMCA) supports the ability of stable isotope ratios analysis for the geographical traceability of garlic.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1191045
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