A Multi-Methodological Protocol to Characterize PDO Olive Oils
Simone Circi,
Cinzia Ingallina,
Silvia Vista,
Donatella Capitani,
Andrea Di Vecchia,
Genesio Leonardi,
Giovanni D’Achille,
Luigi Centauri,
Federica Camin,
Luisa Mannina
Affiliations
Simone Circi
Dipartimento di Chimica e Tecnologie del Farmaco, Sapienza Università di Roma, P.le Aldo Moro 5, 00185 Rome, Italy
Cinzia Ingallina
Dipartimento di Chimica e Tecnologie del Farmaco, Sapienza Università di Roma, P.le Aldo Moro 5, 00185 Rome, Italy
Silvia Vista
Dipartimento di Chimica e Tecnologie del Farmaco, Sapienza Università di Roma, P.le Aldo Moro 5, 00185 Rome, Italy
Donatella Capitani
Istituto di Metodologie Chimiche, CNR, Area della Ricerca di Roma 1, Laboratorio di Risonanza Magnetica “Annalaura Segre”, Via Salaria km 29,300, 00015 Monterotondo, Italy
Andrea Di Vecchia
Istituto di Biometeorologia, CNR, Via dei Taurini 19, 00185 Rome, Italy
Genesio Leonardi
Associazione Produttori Olivicoli Latina, via Don Minzoni 1, 04100 Latina, Italy
Giovanni D’Achille
Associazione Produttori Olivicoli Latina, via Don Minzoni 1, 04100 Latina, Italy
Luigi Centauri
Centro Assaggiatori Produzioni Olivicole Latina, via Don Minzoni 1, 04100 Latina, Italy
Federica Camin
Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), via E. Mach 1, 38010 San Michele all’Adige, Italy
Luisa Mannina
Dipartimento di Chimica e Tecnologie del Farmaco, Sapienza Università di Roma, P.le Aldo Moro 5, 00185 Rome, Italy
An analytical approach including Panel Test, Isotope Ratio Mass Spectrometry (IRMS) and Nuclear Magnetic Resonance (NMR) spectroscopy was proposed to characterize Italian “Colline Pontine” PDO olive oils (40 samples) of two consecutive crop years. Our approach has evidenced the high quality of these olive oils. Only 6 of 40 olive oils samples were defined as “defective” by the official Panel Test due to the detection of negative sensory attributes. The low variability of isotopic data monitored by IRMS confirmed that the olive oil samples all came from a limited geographical area. NMR spectra did not evidence any chemical composition anomaly in the investigated samples. In order to assess the influence of harvesting year over the olive oil chemical composition, the NMR analysis was extended to other 22 olive oil samples of a third harvesting year. NMR data were submitted to two different statistical methods, namely, analysis of variance (ANOVA) and principal component analysis (PCA) allowing olive oils of three consecutive harvesting years to be grouped.
