Multivariate Analysis of 1H‐NMR Spectra of Genetically Characterized Extra Virgin Olive Oils and Growth Soil Correlations

Abstract

AbstractMono‐varietal extra virgin olive oils were micro‐extracted from drupes that were selectively collected from 28 trees distributed in five different Southern Italian Apulian areas. Nuclear Magnetic Resonance (NMR) profiles of these oil samples were correlated to the genetic (young green material) and soil (samples collected within the foliage projection) data of the tree of origin. Genetic analysis, performed on the samples using SSRs (Simple Sequence Repeats) by 9 microsatellite loci, confirmed the specific cultivar assignment (among Cima di Mola, Coratina, Ogliarola, and Oliva Rossa cultivars). Chemometric methods applied to 1H‐NMR spectroscopic data were used for cultivar and geographical origin discrimination of the studied extra virgin olive oils. Linear Discriminant Analysis (LDA) afforded a high reliability degree for discriminating cultivars (almost 90% of prediction ability), and a good assigning ability for the geographical origin (Ogliarola and Coratina samples used as subsets). Soil analyses were performed for each tree. Regression analysis was applied to soil composition in order to correlate available nutrients and total metals with the content of fatty acids and minor components present in monovarietal extra virgin olive oils. In the case of oleic and linoleic fatty acids, and for some terpenes, B, Cr, Mn, Zn were found to give significant correlations. Zn and Mn were the most significant trace elements for all the correlations found (p < 0.01). The results obtained (genetic, spectroscopic and soil analyses) are discussed as a multidisciplinary approach for setting up a strategy for a cultivar and/or geographic origin certification committed database construction.