Abstract

This work encompasses the use of 1D multinuclear NMR spectroscopy, namely, 1H NMR and 13C NMR DEPT 45, combined with a multivariate statistical analysis to characterize olive oils produced from nine different varieties: Galega Vulgar, Cobrançosa, Cordovil de Serpa, Blanqueta, Madural, Verdeal Alentejana, Arbequina, Picual and Carrasquenha. Thus, the suitability of an NMR-based spectroscopic tool to discriminate olive oils according to their varietal origin is addressed. The results obtained show that the model based on 13C NMR DEPT 45 data has a stronger performance than the model based on 1H NMR data, proving to be promising in the discrimination of the olive oils under study based on their varietal origin, being particularly relevant for olive oils of the Galega Vulgar variety.

Highlights

  • In the last 15 years, the Alentejo region, located in the south of Portugal, has gained50 thousand hectares of olive orchards and is nowadays responsible for approximately70% of Portuguese olive oil (OO) production

  • The 1 H nuclear magnetic resonance (NMR) spectrum contains several overlapping peaks due to the presence of different multiplet patterns that arise from the spin coupling of different protons, which are condensed into a very narrow spectral window (~15 ppm)

  • In the 1 H NMR spectrum, it is not possible to attribute the positional distribution of the fatty acids in the glycerol backbone, constituting a limitation for its widespread use

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Summary

Introduction

70% of Portuguese olive oil (OO) production Galega Vulgar, Cobrançosa, Cordovil de Serpa and Verdeal Alentejana. Due to the socio-economic relevance of Alentejo’s olive orchards, the valorization of varietal olive oils from the most important traditional cultivars is mandatory, of paramount relevance being the study of olive oils produced from Galega Vulgar, one of the oldest varieties. Few studies related to olive oils produced in Portugal using the typical olive varieties are described in the literature, mainly based on the use of chromatographic and spectroscopic techniques and chemometric tools [1,2,3,4,5,6]. Peres and coworkers [1] used artificial neural networks to achieve a chemometric classification of olive cultivars from Cobrançosa, Cordovil, Madural, Negrinha de Freixo, Santulhana and Verdeal Transmontana from the

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