title: Cultivar classification of Apulian olive oils: Use of artificial neural networks for comparing NMR, NIR and merceological data.
abstract: The development of an efficient and accurate method for extra-virgin olive oils cultivar and origin authentication is complicated by the broad range of variables (e.g., multiplicity of varieties, pedo-climatic aspects, production and storage conditions) influencing their properties. In this study, artificial neural networks (ANNs) were applied on several analytical datasets, namely standard merceological parameters, near-infra red data and1H nuclear magnetic resonance (NMR) fingerprints, obtained on mono-cultivar olive oils of four representative Apulian varieties (Coratina, Ogliarola, Cima di Mola, Peranzana). We analyzed 888 samples produced at a laboratory-scale during two crop years from 444 plants, whose variety was genetically ascertained, and on 17 industrially produced samples. ANN models based on NMR data showed the highest capability to classify cultivars (in some cases, accuracy>99%), independently on the olive oil production process and year; hence, the NMR data resulted to be the most informative variables about the cultivars.
authors.affiliation: Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Via E. Orabona, 4, 70125 Bari, Italy. Electronic address: giulio.binetti@poliba.it.
authors.forename: Giulio
authors.initials: G
authors.lastname: Binetti
authors.affiliation: Dipartimento di Tecnologie Biologiche ed Ambientali, Università del Salento, Prov.le Lecce-Monteroni, 73100 Lecce, Italy. Electronic address: laura.delcoco@unisalento.it.
authors.forename: Laura
authors.initials: L
authors.lastname: Del Coco
authors.affiliation: Consorzio C.A.R.S.O., Università di Bari, Strada Provinciale Casamassima Km 3, 70010 Valenzano (Bari), Italy. Electronic address: rosaragone@yahoo.it.
authors.forename: Rosa
authors.initials: R
authors.lastname: Ragone
authors.affiliation: Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria-Centro di ricerca per l'Olivicoltura e l'Industria Olearia, Contrada Li Rocchi, 87036 Rende (Cosenza), Italy. Electronic address: samanta.zelasco@crea.gov.it.
authors.forename: Samanta
authors.initials: S
authors.lastname: Zelasco
authors.affiliation: Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria-Centro di ricerca per l'Olivicoltura e l'Industria Olearia, Contrada Li Rocchi, 87036 Rende (Cosenza), Italy. Electronic address: enzo.perri@crea.gov.it.
authors.forename: Enzo
authors.initials: E
authors.lastname: Perri
authors.affiliation: Dipartimento di Biologia e Chimica Agro-Forestale ed Ambientale, Sezione di Genetica e Miglioramento, Università di Bari, via Amendola 165/a, 70126 Bari, Italy. Electronic address: cinzia.montemurro@uniba.it.
authors.forename: Cinzia
authors.initials: C
authors.lastname: Montemurro
authors.affiliation: Oliveti Terra di Bari O.P. Olivicoli Soc. Coop. Agricola, 6/A, Via Brigata 6/A, 70124 Bari, Italy. Electronic address: agrivalent@libero.it.
authors.forename: Raffaele
authors.initials: R
authors.lastname: Valentini
authors.affiliation: Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Via E. Orabona, 4, 70125 Bari, Italy. Electronic address: david.naso@poliba.it.
authors.forename: David
authors.initials: D
authors.lastname: Naso
authors.affiliation: Dipartimento di Tecnologie Biologiche ed Ambientali, Università del Salento, Prov.le Lecce-Monteroni, 73100 Lecce, Italy. Electronic address: fp.fanizzi@unisalento.it.
authors.forename: Francesco Paolo
authors.initials: FP
authors.lastname: Fanizzi
authors.affiliation: Consorzio C.A.R.S.O., Università di Bari, Strada Provinciale Casamassima Km 3, 70010 Valenzano (Bari), Italy. Electronic address: paolo.schena@uniba.it.
authors.forename: Francesco Paolo
authors.initials: FP
authors.lastname: Schena
mesh_terms: D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D016571:Neural Networks, Computer; D000069463:Olive Oil / Q000737:chemistry* / Q000145:classification*
chemical_list: D000069463:Olive Oil
keywords: Artificial neural networks; Cultivar classification; Merceological analysis; Near-infra red spectroscopy; Nuclear magnetic resonance spectroscopy; Olive oil