## POSTER Session 2
The targeted analysis experiments were performed in negative electrospray ionization mode with an Agilent 6530 Quadrupole Time of Flight LC-MS system (QTOF LC-MS), coupled with an Agilent 1290 Infinity UHPLC system and an autosampler (Agilent Technologies, Santa Clara, CA, USA). Nucleoshell Bluebird RP 18, particle size: 2.7 \(\upmu\)m, length: 100 mm, and ID: 4.6 mm, was used as a column and the mobile phase consisted of a gradient (A: acetonitrile/0.1% acetic acid; B: H\({}_{2}\)O/0.1% acetic acid). Phenolic acids were mainly identified in olive oil samples from Peloponnese and Central Greece, such as syrigenic acid, \(p\)-coumaric acid, caffeic acid, protocatechuric acid, \(p\)-hydroxybenzoic acid, cinnamic acid, and hydroxyytrosol acetate. In Megaritiki olive oil from Attica, the phenolic alcohol hydroxyytrosol, the flavones apigenin and luteolin, the secoriidoids oleacea, oleocanthal, and oleuropein aglycon, and various phenolic acids were identified. The identification was performed using commercially available standards and the publicly available databases ReSpect for phytochemicals and human metabolome database (HMDB). This study serves as a valuable contribution for a deeper investigation of the understudied Greek olive oil Megaritiki cultivar and will contribute to the enhancement of its commercial value. Volatile Compound Characterization of Olive Oil from Koroneiki Cultivar by SPME-GC/MS and Differentiation According to Geographical Origin  
**P. K. Revelou, M. Xagoraris, E. Xera, C. Kanakis, C. Pappas and P. Tarantilis *  
Chemical Laboratories, Agricultural University of Athens, 10431 Athens, Greece  
* Correspondence: ptara@aua.gr  
Solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC/MS) is a well-established technique for the study of volatile compounds of olive oil. The authentication of geographical origins of olive oil is crucial as it affects its commercial value. In this study, 41 olive oil samples from three Greek regions (12 from Heraklion, 10 from Lakonia, and 19 from Messinia) were analyzed using a divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber (Supelco, Bellefonte, PA, USA) and a Thermo GC-TRACE ultra, interfaced to a Thermo Mass Spectrometer DSQ II (Thermo Scientific Inc., Waltham, MA, USA). Statistical analysis was performed with XLSTAT ver. 2020.3.1.0 software (Addinsoft Deutschland, Andernach, Germany). Forty-seven volatile compounds were identified and semi-quantified using b-ionone as an internal standard. Subsequently, the olive oil samples were divided into three groups (Heraklion, Lakonia, and Messinia) and the forward stepwise algorithm was applied for the identification of the most discriminating variables (volatiles) for the geographical differentiation of samples. Two chemometric models were developed for the classification of olive oil samples using the linear discriminant anal ysis (LDA) and quadratic discriminant analysis (QDA). The chemometric models were validated utilizing the cross-validation method. Five volatiles, namely tetradecane, 1-penten-3-ol, 2-hexenal, 1-pentanol, and 2-hexanone, were selected by the stepwise algorithm for the discrimination of olive oil samples. Using these volatiles as explanatory variables, LDA was performed where correct classification and cross validation were 90.2% and 85.4%, respectively. Applying the QDA algorithm, 90.2% of the samples were correctly classified, while after the cross-validation method this percentage was lower, at 70.7%. The above results indicate the high potential of the SPME-GC/MS technique in combination with the forward stepwise algorithm as well as the LDA and QDA algorithms for the differentiation of olive oil according to geographical origin.