Volatile compounds, physicochemical and sensory attributes of four sweet cherry cultivars (Canada giant, Ferrovia, Lapins and Skeena) grown in Northern Greece were determined. Eighteen volatile compounds were identified and semi-quantified in cherries using solid phase micro extraction in combination with gas chromatography/mass spectrometry (SPME-GC/MS). Carbonyl compounds were the most abundant in sweet cherry aroma, followed by alcohols, esters and hydrocarbons/terpenes. Cherry cultivars in order of increasing amounts of volatiles were: Lapins < Canada giant < Ferrovia < Skeena. Physicochemical parameters determined included: titratable acidity (TA), pH, total soluble solids (TSS), maturity index (MI) and total phenolic content (TPC). TA ranged between 0.21 and 0.28 g malic acid/100 g fresh weight (FW). The pH ranged between 3.81 and 3.96. TSS ranged between 13.00 and 16.00 °Brix. MI ranged between 51.8 and 75.0. TPC ranged between 95.14 and 170.35 mg gallic acid equivalents (GAE)/100 g FW. Sensory evaluation showed that cherry colour, in order of increasing intensity, was: Canada giant < Ferrovia < Lapins < Skeena. Respective order for cherry firmness was: Canada giant < Lapins ≤ Ferrovia < Skeena and for flavour: Lapins < Canada giant < Skeena ≤ Ferrovia. Correlation of volatiles to physicochemical and sensory attributes showed varying trends.

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The present study comprises the second part of an ongoing study focusing on olive oil from five less well‐known Greek cultivars for three of which there are no data available in the literature regarding their chemical composition. A total of 74 olive oil samples were collected during the harvesting periods 2012–2013 and 2013–2014. Headspace‐solid phase microextraction was applied to determine the olive oil volatile profile. Fifty‐six compounds were identified and semi‐quantified by CG–MS. Furthermore, fatty acid composition, conventional quality parameters and color parameters were determined in an effort to characterize and differentiate olive oils according to cultivar. All samples were characterized as extra virgin olive oils. Data obtained showed significant differences between the cultivars. Multi‐element analysis in combination with chemometrics resulted in a high classification rate of 86.5 % for the combination of volatiles plus color, 89.2 % for the combination of VC plus FA, and 91.9 % for the combination of FA composition plus color plus CQP.

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The present study focused on the possibility of differentiating fresh-unprocessed orange juice according to botanical origin (variety), based on the use of conventional physico-chemical parameters, flavonoids, and volatile compounds, in combination with chemometrics. For this purpose, oranges from seven different varieties were collected during the harvest years of 2013–2014 and 2014–2015 from central and southern Greece. The physico-chemical parameters that were determined included: electrical conductivity, acidity, pH, and total soluble solids. The flavonoids: hesperidin, neohespseridin, quercetin, naringin, and naringenin were determined using high-performance liquid chromatography (HPLC-DAD). Finally, volatile compounds were determined using headspace solid-phase micro-extraction in combination with gas chromatography-mass spectrometry (HS-SPME/GC-MS). Statistical treatment of data by multivariate techniques showed that orange juice variety had a significant (p < 0.05) impact on the above analytical parameters. The classification rate for the differentiation of orange juice according to orange variety using multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) was 89.3%, based on the cross-validation method.